THE CULTURAL CONSTRUCTION OF INTERDISCIPLINARITY: DOCTORAL STUDENT SOCIALIZATION IN AN INTERDISCIPLINARY NEUROSCIENCE PROGRAM
by Karri A. Holley
A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (EDUCATION)
May 2006
Copyright 2006
Karri A. Holley
UMI Number: 3237168
Copyright 2006 by Holley, Karri A. All rights reserved.
UMI Microform 3237168 Copyright 2007 by ProQuest Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code.
ProQuest Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, MI 48106-1346
ii DEDICATION To Richard, Jonah, and Jacob
iii TABLE OF CONTENTS
DEDICATION
ii
LIST OF TABLES
v
LIST OF FIGURES
vi
ABSTRACT
vii
CHAPTER ONE: Interdisciplinary culture
1
CHAPTER TWO: (Inter) disciplinarity and socialization
23
CHAPTER THREE: Research methodology
66
CHAPTER FOUR: Constructing interdisciplinarity
98
CHAPTER FIVE: Understanding interdisciplinary socialization
180
REFERENCES
216
APPENDIX A: List of students who participated in the study
231
APPENDIX B: Student consent form
234
APPENDIX C: Faculty consent form
239
iv APPENDIX D: Student interview protocol
244
APPENDIX E: Faculty interview protocol
246
v LIST OF TABLES
Table 1: Dimensions of socialization
35
Table 2: Classification of the disciplines
48
Table 3: Characteristics of the academic disciplines
50
Table 4: Typology of interdisciplinary knowledge
60
Table 5: Research methodologies utilized in dissertation
85
Table 6: Characteristics of disciplinary/interdisciplinary doctoral student socialization
202
vi LIST OF FIGURES Figure 1: Linear model of doctoral student socialization
37
Figure 2: Cultural perspective of doctoral student socialization
43
Figure 3: Additive model of interdisciplinarity
63
Figure 4: Interdisciplinarity and doctoral student socialization
101
vii ABSTRACT Using the methodologies of individual and group interviews, observation, and document analysis, this dissertation examines the experiences of doctoral students enrolled in an interdisciplinary neuroscience program. A framework drawn from theories of organizational socialization is employed to understand the influence of an interdisciplinary program on doctoral student socialization. While abundant previous literature exists in regards to the socialization of doctoral students, such literature largely concentrates the disciplinary experience. The escalating import of globalization and shifting fiscal realities place new demands on Ph.D. programs and doctoral students to work as part of collaborative research teams, produce interdisciplinary knowledge, and integrate theory and practice. The increasing influence of such factors requires a new focus on interdisciplinarity and the changing Ph.D. The goal of this dissertation is to expand the existing framework of socialization by documenting the influence of such obstacles on knowledge acquisition, identity development, and professional investment. This study focuses on how interdisciplinary identities are constructed by doctoral students through individual interaction with the social environment and cultural context. Particular attention is given to the structural and cultural obstacles that doctoral students must negotiate as they navigate an interdisciplinary program. The study expands on the previous literature regarding doctoral student socialization by focusing on identity development, specifically a student’s symbolic identity as a
viii neuroscientist, a student’s disciplinary identity (related to her professional background and undergraduate experiences), and a multi-disciplinary identity that allows for connections across disciplinary boundaries. In contrast to the traditional concepts of identity which focus on boundaries and differences as an inherent part of self-definition, the structure of identity advanced here instead explores what factors connect individuals who are working in different areas of study. Faculty and peers perform important roles in this process, by modeling the relevance of collaborative research and engaging students in multi-disciplinary conversation.
1 CHAPTER ONE INTERDISCIPLINARY CULTURE It is late on a February afternoon, and the winter rain clouds have slowly rolled in, casting shadows across Jennifer Casey’s laboratory. Jennifer, a first-year Ph.D. student in the neuroscience program at Glenhaven University,1 is working alone at a small desk, oblivious to the encroaching darkness. Instead, she concentrates on a small mouse wiggling between her fingers, his feet furiously rotating in the air, and injects him with clear fluid from a syringe. Her ultimate goal, she will later tell me, is to use mice to determine the role of testosterone in the progression of Parkinson’s disease. I ask her what it is like to research Parkinson’s disease. “On a day-to-day basis,” she replies, “what do you really accomplish? And the answer is nothing, really. Today, I have no data to show, and I discovered nothing about Parkinson’s. But it takes the kind of person who will look at it over the long-term. Hopefully, at the end of five years here, my goal is to make some contribution to the literature about Parkinson’s, and if I can do that, I would be really excited.” It is early March. Alex Hagler, another first-year Ph.D. neuroscience student, begins what will be a long day sitting in front of a computer, using his skills in programming to construct a model of the human eye. Alex is a non-traditional student in the neuroscience program. He is in his early thirties, and spent several
1
The names of the students, faculty, and university have been altered to ensure confidentiality.
2 post-undergraduate years considering various career options. During an earlier interview, he explained his research interest—using computer modeling to construct a replica of a retinal prosthetic for patients who have suffered vision degeneration. What type of knowledge, I asked, is necessary to conduct his research? His list is long: cellular biology, biophysics, computational theory, computer modeling, and clinical biology—among others. “It requires all these different types of knowledge, and you end up being a jack of all trades, in some respects,” he concluded. It is now June. The air conditioner in Jonathan Anderson’s dented Honda spews out cold air erratically, doing little to assuage the stifling heat. Quickly wiping his brow, he concentrates on parking in a narrow space in front of a small, nondescript home near Glenhaven’s main campus. In his fourth year of the neuroscience Ph.D. program, Jonathan’s research documents how brain degeneration, caused by Alzheimer’s disease, results in semantic deficits—the loss of particular forms of language. He travels frequently to visit Alzheimer’s patients, all of whom are treated through the university’s Alzheimer Disease Research Center. Jonathan monitors individual responses to a variety of speech perception exercises, returning to campus late in the evening to input the data on his computer. “Ultimately, our use of language is dependent on the structure of the brain,” he tells me during a conversation. “Working with these patients, we understand how the [language] system operates, and how it is falling apart.”
3 Interdisciplinary doctoral degrees, such as those awarded through Glenhaven’s neuroscience program, are uncommon in the contemporary research university. Although critics of Ph.D. education maintain that doctoral students are taught too narrowly in a subspecialty of a single discipline, leaving individuals illequipped to work within broader, related connections (COSEPUP, 1995; Golde & Gallagher, 1999), the standard for doctoral education is still to demonstrate detailed mastery of knowledge within a traditionally-defined disciplinary area of study. Ultimately, doctoral students “learn to frame questions that are significant to their chosen fields, investigate those questions systematically, and do so in ways that contribute to the thought and practice of others” within their discipline (Hutchings & Clarke, 2004, p. 161). Jennifer, Alex, and Jonathan, however, represent a new type of doctoral student. They are three of the 80 Ph.D. students2 enrolled in the interdisciplinary neuroscience graduate program at Glenhaven University. Their diverse interests are situated within the broad category of neuroscience. Their research reflects GU’s five formal areas of study: cellular and molecular neurobiology, behavioral and systems neurobiology, cognitive neuroscience, computational and engineering neuroscience, and the neuroscience of aging. Neuroscience draws on the expertise, knowledge, and
2
At the time of this dissertation, 80 neuroscience doctoral students were enrolled at Glenhaven University. I use doctoral student, Ph.D. student, and graduate student interchangeably to refer to those individuals enrolled in the neuroscience Ph.D. program at Glenhaven. Conversely, Ph.D. education is also referred to as graduate or doctoral education. All terms refer to the Ph.D. and those students enrolled in a Ph.D. program.
4 methods from multiple traditional disciplines. At Glenhaven, affiliated neuroscience faculty represent seven traditional departments—biology, gerontology, biomedical engineering, psychology, linguistics, kinesiology, and computer science—as well as the schools of medicine and pharmacy. The departments and schools are located on multiple campuses. The imperative to “balance the deep learning of the disciplinary doctorate with the variety of interdisciplinary challenges” (Wilson, 2001) requires a detailed understanding of doctoral student experiences and the knowledge with which they work. Considering the increasing demand to provide Ph.D. education that is socially responsive, broad, and flexible, this study explores the culture of an interdisciplinary neuroscience Ph.D. program from the socialization experiences of Jennifer, Alex, Jonathan, and their peers. In the remaining sections of the chapter, I detail the purpose and research questions guiding this study. I then further outline the context for this work by considering the interdisciplinary characteristics of neuroscience. I conclude with a framework for subsequent chapters. Statement of purpose I focus on a Ph.D. program in neuroscience to understand how doctoral students became socialized in an interdisciplinary environment. I utilize a cultural perspective that defines doctoral students, faculty, and administrators as active interpreters and actors within the institutional culture. Using this lens of cultural analysis, interdisciplinary studies can best be defined as a process, inspired by a need
5 for knowledge that traditional academic disciplines cannot (or do not) produce. I seek to extend the literature on doctoral student socialization by documenting the perspectives of individuals experiencing this unique process. Glenhaven University is a well-regarded, nationally recognized research university. The context, role, and structure of Ph.D. education at such American universities have been the focus of much scrutiny over the past decade. “Doctoral education,” concluded Bowen and Rudenstine (1992), “occupies a particularly critical place in… higher education because it is the training ground for almost all those who become faculty members, as well as for many who pursue other vocations of broad import” (p. xv). Calls to understand and improve the doctoral education process have been wide-ranging: from educational policy foundations and institutional initiatives to federal government agencies and educational researchers. The Pew Charitable Trust, for example, funded the Re-envisioning the Ph.D. Initiative, which analyzed the doctoral degree in terms of its capacity to meet the social demands of the new century (Nyquist & Woodford, 2000). The Carnegie Initiative on the Doctorate has focused on the need for doctoral programs to create stewards of the discipline; the Initiative also has supported enabling doctoral students to cross disciplinary boundaries in their research (Carnegie, 2005). The conclusions of the Responsive Ph.D. project noted that “the doctorate must be [more] open to the world and engage social challenges more generously” (Woodrow Wilson, 2005, p. 1). In addition, the Committee on Science, Engineering, and Public Policy
6 (COSEPUP) of the National Academy of Sciences issued its influential Re-Shaping the Education of Scientists and Engineers (1995), calling for more flexible, engaged, and timely doctoral programs. Research Questions Considering the perceived conflict between the disciplinary learning of the doctorate and the increased demand for research, knowledge, and scholarship that crosses disciplinary boundaries, I explore the following three questions: 1) How do doctoral students in an interdisciplinary program define their professional identity? 2) How do these doctoral students navigate disciplinary cultures to engage in interdisciplinary scholarship? 3) What skills, beliefs, and attitudes does interdisciplinary work in a doctoral program foster? Knowledge production is an essential component of socialization. As an individual is socialized to the norms of a disciplinary community, she participates in (and in part, creates) a culture with preferred epistemologies, paradigms, and methodologies. The definition of knowledge is related to social and cultural norms. This dissertation ultimately explores how knowledge is culturally classified, organized, and produced by doctoral students who are working across disciplinary boundaries. I consider that “the way disciplines define knowledge is constantly reinterpreted and redefined” (Tierney, 1991, p. 204). The legitimacy and authority of
7 scientific knowledge has been debated at great length (for example, Harding, 1991; Labinger & Collins, 2001; Rorty, 1998; Ross, 1996; and Shapin, 1996). In recent decades, the purely positivist approach to understanding science, which analyzed the process as objective and rational, has been increasingly challenged by a more postmodern perspective. While acknowledging the contested nature of science and related social factors, I instead focus on the organization of knowledge as experienced by doctoral students within a degree program in higher education—a cultural understanding of the process. Disciplines represent a particular ordering of knowledge designed to explore specific areas of inquiry. These “bodies of knowledge” are related to the structure and culture of the community from which they are produced (Mansilla & Gardner, 2003). Although the categories of interdisciplinarity reveal multiple ways and forms of producing such knowledge, for the purposes of this dissertation, I assume that interdisciplinary work is the integration of multiple bodies of knowledge. This integration results in a unique professional and intellectual community formed from individuals with distinctive socialization experiences in a variety of disciplines. Such a community is the center of this study. Understanding what Ph.D. students should know regarding their respective fields and how that knowledge contributes to social, political, economic, and human needs is invariably connected to issues of socialization. The definition of socialization that I employ in this study to understand doctoral student experiences
8 refers to a dynamic, non-linear social process where an individual’s beliefs, perceptions, actions, and skills are influenced by the organization while conversely influencing their organizational environment (Antony, 2002; Tierney & Rhoads, 1994). Drawing from sociological and organizational theories, this socialization framework assumes that individuals develop a professional identity congruent to their perception of the community. Knowledge acquisition is an essential component of socialization; developing sufficient depth, proficiency, and expertise in the field encourages role competency and professional expertise, and allows the individual to assume the identity of a specialist within their field. Doctoral students complete a dissertation as a means to demonstrate their epistemological and methodological competencies relevant to a particular area of inquiry. The quality of the dissertation is assessed by senior members of the community—typically professors within the student’s discipline. Conceptualizing the disciplines I am perched atop a rickety stool in the basement of Glenhaven’s primary neuroscience facility, in the research lab of Jonathan Anderson, the fourth-year Ph.D. student who researches Alzheimer’s disease and language. There are no windows to let in the abundant summer sunshine. Instead, the gaze of G. Stanley Hall, a noted psychologist, coolly appraises me from a black-and-white photograph hanging haphazardly on the wall. Beside the photo dangles a faded cartoon drawing—“Why do neurons like email? They get to send and receive a lot of messages.” Jonathan’s
9 intellectual journey over the past four years has been laborious, leading him first into Glenhaven’s linguistics Ph.D. program, followed by a complicated administrative transfer into neuroscience. Jonathan has finally found his niche, he explains, by being able to construct his research interest from various disciplinary segments, including linguistics, psychology, and biological science. Jonathan’s habit is to slowly run his fingers across his beard as he contemplates his response to my questions. But when I ask him about interdisciplinarity and his work, I am startled by his sudden change in demeanor. Pushing his glasses high on his nose, he quickly leans forward with his elbows balanced on his knees. The words rush out: I have this belief, probably passed down from my advisor that the answers are in the interface somewhere. People are starting to realize that the answers are not in these compartmentalized structures. Having this perspective of being trained in linguistics and now in neuroscience, I see the good it can do… That really, there are so many answers there, but a lot of it is the explosion of research that has gone on in the last few hundred years, and it is getting exponentially greater, and we are filling out those corridors, and the questions are largely solved or unsolvable, so now we are pushing into these issues that are—what used to be in the periphery, and what used to be looked at not so much. But they are now the places to go. His comments would stay with me in the weeks and months after our interview, as I gathered additional data for this study. The neuroscience program at Glenhaven is, in many ways, the institutional embodiment of “the places to go” in search of interdisciplinary knowledge. No clear consensus exists regarding the definitions of a disciplinary area of study or relevant canons to be mastered by
10 doctoral students. Mastery of the discipline is determined by the faculty within a student’s respective department, and is also influenced by the academic, disciplinary, and institutional community. “Knowledge is a discourse constantly reconstructed over time and place,” offered Tierney. “The production of knowledge cannot be separated from contingencies and continuous reconstructions of culture” (1991, p. 201). In terms of culture, Jonathan’s perspective regarding knowledge defines intellectual trajectories as influenced by the structural context of the university. Disciplines can be understood in two ways: first, as an intellectual context and second, as a cultural construct situated within the postsecondary institution (Becher & Trowler, 2001). First, disciplines are “thought domains—quasi-stable, partially integrated, semi-autonomous intellectual conveniences—consisting of problems, theories, and methods of investigation” (Aram, 2004, p. 380). Klein defined disciplines as “tools, methods, procedures, exempla, concepts, and theories that account coherently for a set of objects” (1990, p. 104). As I previously argued, knowledge is a socio-cultural construct, and the tools, methods, and other components utilized to further knowledge are shaped by human interaction. The discipline as a cultural construct mediates our view of the world, and consequently shapes the ways in which practitioners define problems. The discipline is “created” because individuals with a shared interest exchange and develop knowledge. Doctoral students advance through degree programs, in part, by mastering prescribed disciplinary paradigms.
11 Disciplines also provide a community of practice, a network of individuals sharing interest and expertise in specific knowledge domains. This perspective views the discipline as a “community … a heterogeneous social system composed of individuals with varying commitments to ideas, beliefs, and methodologies—and each other” (Lattuca, 2001, p. 25). The shared culture creates social norms regarding behavior and scholarship. The disciplinary community does not exist in isolation. Disciplines are invariably intertwined with the academic profession and the institution as well as broader social, economic, and political demands (Austin, 1990; Weiland, 1995). These broader influences can often prompt the reconfiguration of knowledge. In essence, the disciplinary community is bound in time and context (Valimaa, 1998). Mourad (1997) defined three characteristics of the disciplines as an intellectual formation situated within the university structure. First, the traditional disciplines—consisting of the natural and social sciences, and the humanities—are generally considered to comprise the foundation of the university. The disciplines also pursue what Mourad labeled “the theoretical knowledge of reality,” or a progressive accumulation of knowledge regarding a particular phenomenon (p. 81). Finally, disciplines serve as the “prescribed structure for intellectual activity,” since theories are situated, expressed, and pursued in disciplinary terms (p. 81). These characteristics are significant for understanding the structure of the contemporary university and the manner in which research is conducted. Conceptualizing the
12 university without a disciplinary structure is difficult, if not impossible. Because of this connection, disciplines are often viewed as absolute. Mourad concluded, “Therefore, ‘knowledge of reality’ is, in practice, a reality that is composed of the disciplines” [emphasis added] (p. 129). For faculty, the discipline is generally considered to be the central source of identity (Becher, 1987; Lattuca, 2001). Early socialization, beginning during graduate studies and continuing into the faculty career, offers exposure to the shared social norms which guide individual behavior within the discipline. This Foucauldian perspective of the disciplines considers the social contexts and constructs that influence knowledge production. According to Foucault (1970), knowledge is historical, or responsive to the time and context of its production, and not defined by autonomous characteristics. The power of the disciplines derives from the sense of community and the social norms produced, a “master norm” that through socialization produces compliance from members. The result is that disciplinary members are members of a contextually bound community structured by power and influences both internal and external to the university. Disciplinary knowledge is a valuable commodity for new members of the community, such as doctoral students. Students are formally exposed to such knowledge through a defined curriculum, and are expected to demonstrate increased mastery of that knowledge as they progress through the program. The value given to particular areas of inquiry and the methods by which scholarship is pursued and
13 acknowledged is directly related to an individual’s perception of the attitudes and expectations within the community. Doctoral students gain what Bourdieu (1986) labeled “cultural capital,” or forms of knowledge that give an individual increased status within a community. Students acquire formal knowledge related to the curriculum and topics of inquiry. They also collect “practical, almost subconscious, knowledge or competence that the departmental elite fully masters” (Gerholm, 1990). Jonathan’s definition of interdisciplinary knowledge as a natural result of the rapid growth of knowledge, however, represents a conflict between disciplinary structures and social/cultural knowledge. The former is related to the processes of the institutional system; the disciplinary structure is an inherent component of the contemporary university. Yet the argument that knowledge can be strictly confined within disciplinary boundaries is dubious. Neuroscience is a result of such a conflict. When I began my study of the interdisciplinary structure of neuroscience, a GU professor affiliated with the neuroscience program grandly proclaimed, “Neuroscience would be the perfect example of [interdisciplinarity], probably the best example you could pick.” I briefly provide the reader with a summary of the interdisciplinary foundation of neuroscience as an introduction to the doctoral student experiences presented later in this dissertation.
14 Understanding neuroscience Neuroscience is a component of the life sciences that deals with the anatomy, physiology, biochemistry, or molecular biology of the brain and nervous system. A special focus is given to the relation to behavior and learning. Neuroscience includes “the study of brain development, sensation and perception, learning and memory, movement, sleep, stress, aging and neurological and psychiatric disorders” (SfN, 2004). The field also studies the molecules, cells and genes responsible for nervous system functioning (SfN, 2004). While an academic journal (The Journal of Neuroscience) and a professional association (the Society for Neuroscience) for the field do exist, scholars and faculty within the field are drawn from a wide array of disciplines: biology, chemistry, cognitive science, psychology, linguistics, and computer science, among others. Neuroscience is an operationally interdisciplinary field of study. The human brain and nervous system have long been the focus of human inquiry. By the 1800s, for example, researchers determined that different locations within the brain controlled different types of behavior and thought. Harvey Cushing practiced anesthesiology and neural brain surgery in the early 1900s, defining the field of neurology; the 1932 Nobel Prize was awarded for the “discoveries of chemical transmissions relating to nerve impulses” (Afifi & Bergman, 1998). The concept of neuroscience is not unique to the twentieth century. With the evolution of the contemporary research university, however, and the organization of disciplines as
15 defined areas of study, neuroscience was a fragmented area of the life sciences found within multiple disciplines. There was no single field of study defined as neuroscience. The history of the professional association, the Society for Neuroscience, reveals much about the maturity of neuroscience as an organized area of inquiry. The association enabled individuals with similar interests to form a shared network. Formed in 1970 in recognition of the “tremendous potential for the study of the brain and nervous system as a separate field,” the Society currently boasts some 36,000 members and is the world’s “largest organization dedicated to the study of the brain” (SfN, 2004). These members include “basic researchers studying the many neuroscience disciplines and clinicians specializing in neurology, neurosurgery, psychiatry, ophthalmology and related fields” (SfN, 2004). The association’s goals include: “advancing the understanding of the brain and the nervous system by bringing together scientists of diverse backgrounds, providing professional development activities, promoting public information, and informing legislators… about new scientific knowledge and recent developments in neuroscience research” (SfN, 2004). Along with a guiding professional association, neuroscience has increasingly become located as a structural field of inquiry within the university. For example, the University of California, Irvine created the first independent neuroscience department in 1964. Today, some 300 neuroscience training programs exist at American colleges and universities (SfN, 2005).
16 Additionally, neuroscience is a particularly well-funded area of study within research universities in the United States. Neuroscience research is a priority of federal funding. Within the National Science Foundation, neuroscience is funded from a variety of organizational units, including the Directorates for Biological Sciences; Social, Behavioral, and Economic Sciences; Engineering; and Mathematical and Physical Sciences. Due to neuroscience’s interdisciplinary structure, additional funding comes from such agencies as the National Institute for Health, the National Institute on Aging, and the National Institute on Drug Abuse. The nature of neuroscientific knowledge relates to the multiple issues associated with the human brain and nervous system, which encourages such broad funding. The knowledge orientation and high degree of funding fosters an environment for graduate students where research is emphasized. Finally, although neuroscience exhibits many disciplinary characteristics, such as a professional association and a research journal, the curriculum still represents multiple disciplines. The challenge for neuroscientists is to gain adequate knowledge and training from various fields of study. One option is that “every successful doctoral trainee must have mastered at least one constituent discipline… from among those that contribute to neuroscience: systems neuroscience, physiology, or the like” (Hyman, 2004, p. 7). Doctoral students in neuroscience are expected to gain familiarity with the body of knowledge that constitutes the field, but also to be fluent in the language of a particular area, such as biology, genetics, or psychology
17 (Hall, 2004). Accordingly, neuroscientists are members of both a disciplinary community and a larger, interdisciplinary community of neuroscientists. Of particular relevance for this study, therefore, is how doctoral students are socialized to the field of neuroscience. How do they process and engage in the collected interdisciplinary knowledge relevant for research on the brain to become experts in the field? Given the multiple perspectives fostered by neuroscience, how do doctoral students develop their identities? Just as traditional academic disciplines vary in structural and intellectual organization, neuroscience cannot be seen as an organized, uniform area of inquiry across all universities. While neuroscience is generally defined as the study of the human brain and nervous system, the structural manifestations of doctoral education in neuroscience vary widely. Some programs such as the one at Glenhaven University offer the Ph.D. in neuroscience, while others offer a Ph.D. in a traditional discipline with an emphasis on neuroscience. At some campuses, neuroscience programs are housed within the school of medicine; others can be found in departments of biology or as free-standing research institutes. Doctoral students may be housed within a department of psychology with an emphasis on cognitive psychology. Other doctoral students may enroll in a Ph.D. program in pharmacology with a special interest in how drugs affect the brain. Within neuroscience, there are multiple areas of focus, such as cognitive neuroscience, or artificial neural networks and computer technology. Distinct research institutes for neuroscience exist,
18 studying (for example) neural engineering, cellular and molecular neurobiology, behavioral neurobiology, the neuroscience of aging, computation and neural systems, neuroethology, and psychophysics—a seemingly endless array of foci. The very nature of the field encourages such diversity in research and knowledge production. Neuroscience is therefore both among the academic disciplines, yet apart from them. While studies regarding the brain were peripheral in the biological and psychological sciences at the beginning of the 20th century, neuroscience “now occupies a central position in each discipline” (Kandel & Squire, 2001, p. 118). Its unique interdisciplinary nature calls into question our understanding of knowledge and its institutional organization. My point here is to emphasize that there is no single definition of neuroscience or a single way for institutions to offer doctoral training in neuroscience. Because the topic cuts across multiple and diverse disciplines, the study of neuroscience is manifested in multiple and diverse ways. The goal of neuroscience Ph.D. programs is to produce “a new kind of investigator, fluent in several disciplines, and easily able to incorporate them into a single research program organized around a problem, rather than a technological approach” (Hall, 2004, p. 1). Yet such a goal diverges from our traditional understanding of the academic discipline and doctoral education, instead immersing students in the midst of several disciplines. Doctoral students have traditionally been trained as disciplinary experts bound by a shared epistemology—or within professional fields such as education, as scholars positioned to bridge the gap
19 between theory and practice. Consider the neuroscience students at Glenhaven. Alex, the doctoral student who works on an artificial human retina, calls upon theories and techniques from cellular biology and computer engineering in his work. Jonathan seeks to understand how the biological structure of the brain is related to speech and aging. Some students focus on the molecular structure of particular areas of the brain; others, on how brain structure is related to particular behaviors, such as dyslexia. How does such an approach affect the socialization, training, and identity development of doctoral students? How should disciplinary boundaries be conceptualized when knowledge is not contained by such structures? I offer additional details regarding the Glenhaven neuroscience program in chapter three; I situate the program within the larger interdisciplinary field of neuroscience here. The Ph.D. neuroscience program at Glenhaven does not represent a single discipline, or even a single department. Instead, Jonathan and his student colleagues study, work, and socialize within an elaborate, intricate interdisciplinary program that spans multiple institutional levels. The program has long garnered financial support from Glenhaven’s administration. Neuroscience students assume teaching assistantships in undergraduate biology, engineering, and psychology courses. While the program is officially housed in a sleek, contemporary, six-floor building near the middle of campus, specifically constructed for neuroscience research, doctoral neuroscience students frequently find their homes in labs across campus, including the engineering, biological sciences, gerontology, and psychology
20 complexes. A significant number of doctoral students work at Glenhaven’s medical school, ten miles away from the main campus. A shuttle service connects the two campuses. Doctoral students also have research positions at a non-profit organization that studies the cellular and molecular nature of the auditory system and is formally affiliated with the school of medicine. Within these labs, where the students spend the bulk of their graduate school experience, their peers are frequently students from other Ph.D. programs at Glenhaven. Doctoral students in the neuroscience commonly work alongside Ph.D. students from biology, engineering, gerontology, psychology, and linguistics. Most doctoral neuroscience students attend the annual conference of the Society for Neuroscience, a meeting of some 30,000 researchers with an interest in neuroscience. But they also travel to a diverse array of other academic conferences, with topics ranging from aphasia to anorexia, and publish in a wide range of academic journals. Other than a two-semester required core course and various seminars and events throughout the year, Ph.D. students in the neuroscience program have little structured occasion to interact with other students or program faculty. Summary and framework for dissertation “The right model for thinking about the nature of science,” sociologist Trevor Pinch has argued, “… [is] as a body of expertise carried out by human practitioners” (2001, p. 25). My goal is to determine how students interpret and navigate the program culture in neuroscience, and what effect such experience has on the
21 socialization process. Understanding the experiences of Jonathan and his student colleagues enrolled in Glenhaven’s interdisciplinary neuroscience program requires an understanding of the student interpretation of the program culture. Culture relates to the process of meaning making by individuals within a specific community (Spillman, 2002). The goal of studying a culture is to “understand the process of meaning making, to account for different meanings, and to examine their effects in social life” (Spillman, p. 4). Culture offers a variable and contingent framework to understanding individual and group behavior according to the context. In my dissertation, a cultural understanding of the nature of interdisciplinarity focuses on contexts such as space, time, location, and communication (Valimaa, 1998), which are explored through such processes as socialization and decisionmaking. As a member of a disciplinary community (or in the case of the students in this study, an interdisciplinary program), doctoral students become “part of a project in interpretation and social relations both within and beyond the university” (Weiland, 1995, p. 270). This cultural approach, inspired in part by Foucault (1970), concentrates on the social and contextual production of knowledge, not the knowledge itself. An understanding of individual identity is gained by studying the program culture—how doctoral students define their professional self, make meaning of their environment, and interact within its unique confines. Understanding the motivations, activities, and goals which shape academic work in the academy requires a greater understanding of how researchers pursue
22 knowledge production. In the subsequent chapters, I explore the socialization of doctoral students within the interdisciplinary neuroscience program at Glenhaven University. I detail their experiences, supplemented through interviews with program faculty and administrators as well as observation of such events as program meetings, seminars, dissertation defenses, and laboratory interactions. In chapter two, I outline theories of socialization, specifically related to doctoral students, and examine the relationship between knowledge production, interdisciplinarity, and socialization. Chapter three includes the methodological framework of the study. Chapter four situates student experiences in relation to theories of socialization presented in chapter two. In chapter five, I offer discussion and a summative analysis of the data, and implications of interdisciplinarity for the theoretical conceptualization of doctoral student socialization.
23 CHAPTER TWO (INTER) DISCIPLINARITY AND SOCIALIZATION “So, tell me a little about your advisor and the lab where you work,” I ask Christopher as we sit in an empty conference room in Glenhaven’s neuroscience building. A small wooden table stands between us; on it, Christopher has scattered a mountainous book bag, handfuls of loose-leaf paper, and a single textbook. I squint to make out the title—Modeling Human Information Processes. Its subtitle is concealed by a half-empty bottle of water that Christopher keeps nervously picking up and then putting back down. “Well, my lab is big,” he quickly responds. “My advisor has a Ph.D. in physics, but now he mainly works in psychophysics, which is related to neuroscience. He’s also very interested in the design of computational models associated with the brain and how it functions. But he’s appointed in psychology and biomedical engineering. And the other students… let’s see…” Christopher’s voice trails off as he quietly inventories his lab colleagues, unconsciously counting on his fingers. “There are two of us from neuroscience, one from psychology, two from cognitive and brain science, which is affiliated with psychology—oh, and an undergrad who is going to optometry school in the fall.” I sit for a few seconds trying to sort through the long list of people. “Can you tell me again what the lab is studying?” I finally ask, somewhat confused. Christopher laughs, and then launches into a long explanation. “Brain imaging,” he states, “and visual deficits related to dyslexia and Alzheimer’s disease... and of
24 course the neuropsychological study of sensory perception. And a general interest in creating computational models of the brain.” He stops to pick up his water bottle again, tapping it against his leg. “And I would say my area of interest and hopefully soon-to-be expertise is psychophysics, and in particular something called signal detection theory. It’s an area that developed from work with sound amplifiers, in engineering, but eventually people took that and thought of the brain as a signal processor. If your sensory systems are there to give you information about the world, how do you use that information, how do you extract the useful information and ignore the noise?” At the onset of our interview, Christopher explained that he recently graduated from St. John’s College, a small, liberal arts institution that focuses on a Great Books curriculum. He correctly concluded, “My background is probably different than any of the other students you may have spoken with.” Christopher spent four years reading the works of Aristotle and Plato, duplicating the historical scientific experiments of Newton, and deciphering the mathematical principles of Euclid. All students graduate from St. John’s with a liberal arts degree. “In my senior year,” Christopher recounts, “I emailed a lot of schools to see if I should even bother applying to neuroscience programs, since I didn’t have a traditional background in science. Most of them said no. But here [at Glenhaven], they said my test scores and grades were the most important, and they’d be able to figure out if I was smart from my application.” The Glenhaven faculty obviously decided in his favor. In the span
25 of two short years, Christopher has gone from considering the philosophical implications of Plato to being a self-described “cognitive scientist” researching how the brain processes noise and external stimuli. “Interdisciplinarity,” noted Klein, “is neither a subject matter nor a body of content. It is a process for achieving an integrative synthesis, a process that usually begins with a problem, question, topic, or issue” (1990, p. 188). Interdisciplinarity is achieved through the engagement of cooperative networks. The research in Christopher’s laboratory seeks to understand how perception and cognition occur in the brain. The process includes computational modeling, brain imaging, and Christopher’s interest, psychophysics, all in a concentrated effort to decipher cognition. His lab is just one of many in Glenhaven’s neuroscience program, all working under the interdisciplinary umbrella of neuroscience with the goal of grasping the mechanisms of the human brain. There is no one way to accomplish interdisciplinarity. The interaction of cooperative networks “can be performed in a variety of ways with an equal variety of results” (Becker, 1984, p. 5). All knowledge is located in a socio-cultural context; that is, the production and organization of knowledge according to the “discipline” is one influenced by behavior, action, and thought (Knorr Cetina, 1999; Pickering, 1992; Traweek, 1988). “Life is a neutral assortment of phenomena that are ordered through human thought and action,” wrote Klein (1996, p. 12). Within the university, knowledge is ordered by the arrangement of disciplines and their relationship to each other. Ultimately, the
26 boundaries that divide and control knowledge (such as Christopher’s work in brain imaging, drawn from such disciplines as physics, psychology, mathematics, engineering, and computer science) are artificial, structured, and reinforced through interpretation. The process of understanding the discipline (and by consequence, disciplinary boundaries) occurs through socialization. As part of the socialization process, individuals assume “the knowledge, skills and dispositions that make them more or less able members of society’’ (Brim & Wheeler, 1966, p. 3). As doctoral students progress through a degree program, they acquire fluency in the requisite knowledge of the respective discipline. Knowledge acquisition and production play a significant role in how individuals come to understand culture. Gaining the necessary knowledge and skills is crucial to an individual’s advancement within the community. For example, Christopher’s emerging area of expertise, signal detection theory, fits uniquely into the psychophysics research of his laboratory. He is gradually developing knowledge in an area that provides him with increased cultural capital and status. Yet the processes and structure of the laboratory are also cultivating his skills. Christopher is developing expertise and knowledge in a manner that allows him to become a productive member of his laboratory community. This dissertation focuses on the socialization of doctoral students within an interdisciplinary program. Socialization has emerged as an increasingly common method of framing the experiences of doctoral students (Antony, 2002; Austin,
27 2002b; Golde, 1996, 2000; Nyquist et al., 1999; Weidman, Twale, & Stein, 2001). Research regarding doctoral student socialization parallels studies of faculty socialization (Johnson & Harvey, 2002; Tierney & Bensimon, 1996; Tierney & Rhoads, 1994; Trowler & Knight, 1999). These theories draw from the concepts of organizational socialization and development (Becker & Strauss, 1956; Blau, 1955; Lortie, 1975; Merton, 1957; Van Maanen & Schein, 1979). Socialization involves the adoption of a cultural perspective that can be brought to bear on organizational events (Van Maanen & Schein, 1979). In this chapter, I examine the relationship between socialization and the disciplines. I specifically focus on how disciplinary contexts within the university influence doctoral student socialization. First, I summarize previous concepts of socialization. I then concentrate on the significance of the discipline, and conclude with a discussion of interdisciplinarity and its relationship to doctoral student socialization and knowledge production. The framework of organizational socialization Theories of socialization focus on the intersection between the individual (the student) and the organization (the university). The traditional concept of socialization assumes a linear, finite development on the part of the student; the process ends with a new role identity and occupational status (i.e., the Ph.D. degree, and membership in the academic profession). For the student, then, socialization theories encompass the experiences immediately preceding and during graduate studies. Three questions
28 structure the socialization process: 1) How are skills gained and utilized? 2) What is the appropriate behavior for individuals in a specific field? and 3) How is role identity assumed and understood by others? (Antony, 2002; Daresh & Playko, 1995; Weidman, Twale, & Stein, 2001). Socialization is a process embedded within the specific culture of a social system; it is a process shaped by human interaction. Merton, Reader, and Kendall, in a study of the student physician, argued, “Socialization takes place primarily through social interaction with people who are significant for the individual...probably with faculty members above most others, but also with fellow-students” (1957, p. 287). These interactions are structured, repetitive, and designed to influence the development of the entering student. I first outline how socialization has been conceptualized as a process, and then compare two perspectives regarding socialization and organizational culture. The dimensions of socialization Organizational socialization is generally assumed to occur through a series of structured and controlled efforts. Such efforts orient new members to institutional practices and cultural expectations. These structured efforts are considered necessary to ensure congruence between the individual and the organization; the goal of socialization, from this perspective, is organizational homogeneity (Lindholm, 2003; Rosch & Reich, 1996). Generally, structural socialization theorists consider how the organization affects individual choices and development. Van Maanen and Schein
29 (1979) offered six tactical dimensions of socialization through which the experiences of newcomers are structured by the organization. The dimensions are generally arranged along a structural standpoint. The focus is on “various forms and results of socialization as they occur when persons move across hierarchical, functional, and exclusionary boundaries” (Van Maanen & Schein, p. 34). I briefly summarize the dimensional aspects of socialization in the context of doctoral student experiences. First, students experience either collective or individual socialization. Consider the training of medical students. Entering medical students undergo a highly structured curriculum designed to provide the core skills needed to practice medicine. All students typically take the same courses, progressing through the curriculum as a cohort. Opportunities for specialization occur much later in their training. Becker, Geer, Hughes, and Strauss (1961) found that such experiences resulted in a “group consciousness.” Peer influences are extremely significant with such relationships. In contrast, doctoral students in certain disciplines in the humanities experience a more individual, independent socialization. These students have less structured opportunities to interact with their peers and faculty. The interests and motivation of individual students typically define research opportunities and course selections. Second, “formal socialization refers to those processes in which a newcomer is more or less segregated from regular organizational members while being put through a set of experiences tailored explicitly for the newcomer” (Van Maanen &
30 Schein, 1979, p. 44). These formal processes clearly signify that the newcomer is not a full-fledged member of the community. For medical school students, their progress through the curriculum is marked by such ceremonial events as the White Coat Ceremony, where students grandly don the mantle of their profession (the white coat) and recite the Hippocratic Oath in a group rite of passage. Van Maanen and Schein further noted that formal socialization is common in organizations “where the work involved is complex, difficult, and usually entails a high penalty for making a mistake” (p. 48). A perceived organizational need exists for rigorous and highly structured training. Informal socialization involves a “learning by doing” orientation; the newcomer is not readily distinguished as such, but instead is considered “at least a provisional member of the work group” from the onset (Van Maanen & Schein, p. 44). Informal socialization is more laissez-faire, where new roles are learned through trial and error. An important component of informal socialization for doctoral students is that of the peer culture, where interaction with student colleagues provides individuals with considerable knowledge. David, a neuroscience student at Glenhaven, speaks of informal socialization in regards to his connection to a student in the doctoral program who works in a different lab: “Kacey, she is taking a look at acetylcholine receptors…the technique she uses, it’s very similar [to the one I use]…the receptors I study structurally and functionally are similar to the ones she studies. I am familiar enough with her receptor that I can go around and bounce off
31 ideas with her, things like that.” Kacey is David’s peer and colleague—even though they work in different laboratories, she is also a knowledge resource for David. The dimensions of formality and the collective nature of socialization are structural. Such dimensions are “associated with major boundary passages, with basic orientation activities, and with the initial entry of the recruit into the organization” (Van Maanen & Schein, 1979, p. 50). Yet the organization of these “passages” is also significant. The third dimension of socialization speaks to the organization of events. Sequential socialization offers students a well-defined sequence of discrete steps leading to degree completion. For these students, the steps must be negotiated in a specific, distinct order. Law students are required to complete a three-year curriculum; individuals interested in business can finish a traditional, highly structured MBA curriculum in two years. At Glenhaven, doctoral neuroscience students must collectively enroll in a series of first-year core courses. In contrast, random socialization is more ambiguous and less controlled by the social system. The fourth dimension identified by Van Maanen and Schein is that of fixed versus variable socialization. Fixed socialization occurs when the organization “provides a recruit with the precise knowledge of the time it will take to complete a given passage” (p. 55). Doctoral students are more likely to experience variable socialization, where the progress to degree completion differs according to the individual and the context. In the neuroscience program at Glenhaven, some doctoral
32 students defended their dissertation by their fourth or fifth year; others reached year eight without a clear concept of how they should proceed with their dissertation research. The fifth dimension, serial socialization, involves the organized interaction between recruits and more experienced members. For doctoral students, serial socialization occurs when faculty advisors provide regular and reliable guidance (Tierney & Rhoads, 1994). Professors serve as role models for students, and embody what can often be perceived as the abstract definition of the “organization.” Disjunctive socialization occurs when no role models exist for newcomers. Anna, a married first-year student in Glenhaven’s neuroscience program, describes her experiences as disjunctive socialization. “Even with my advisor right now, she is not married and doesn’t have a boyfriend, so she is always here, even on the weekends,” Anna relates. “I know quite a few people who are having doubts, including myself, and I think all of them are women.” Anna feels that she and her female peers are “out of place” in the neuroscience program. The demands of the program are incongruent with her personal identity. Van Maanen and Schein’s final strategy concerns “the degree to which the socialization process is constructed to either confirm or disconfirm the entering identity of the recruit” (1979, p. 64). Investiture affirms personal characteristics of the newcomers. Anna’s experience is one of divestiture—her interest in having children and spending time with her family is incompatible with the image of a
33 neuroscientist as she observes it within the program. In this instance, students feel compelled to make choices. Diane is the mother of two children who recently graduated from Glenhaven. When we spoke in June, she was deciding between two post-doctoral positions. As she explained: Well, I actually told them, the two [professors] that I am seriously considering [working for], that I won’t start anything until January, because I—you know what, if I am not going to worry about getting a Nobel Prize anytime soon, what is the rush? You only have your kids for a certain amount of time. My son is 13, and I only have him for about five more years. So if I can keep my foot in the door until then…I don’t do this to support my family anymore, that’s what I originally started out as—a job that I enjoyed that would also support my family, but now it is just… don’t get me wrong, I do think I deserve money for it, and I won’t work for free. It’s not a hobby. But now I do it because it is something I like to do, basically. Diane believes that the culture of neuroscience forced her to make a choice between being a neuroscientist and a mother. According to Diane, few role models exist for women who desire to combine the two identities: The women that have been successful up until now, they have made a choice not to have children or alternatively not to have much of a relationship with their children, so there are few and far between the role models, mentors, that have a happy marriage, happy children. It is not really very forgiving, this career, and because of that, that main reason right there, is why women have to choose between having children or having a really successful career as a neuroscientist… Van Maanen and Schein’s dimensions of socialization are commonly cited in studies of doctoral student and faculty socialization (i.e., Tierney & Rhoads, 1994; Weidman, Twale, & Stein, 2001; Weidman & Stein, 2003). The dimensions are useful for understanding how “the experiences of an individual in transition from one role to another are structured for him by others in the organization” (Van Maanen &
34 Schein, 1979, p. 34). Van Maanen and Schein’s dimensions of socialization provide a useful perspective to understand how the development of doctoral students has been conceptualized. First, a clear distinction exists between the agents of socialization (the faculty) and the individuals being socialized (the student). The end result of socialization is that this distinction becomes less clear, and the student is integrated into the community. But more significantly, the dimensions of socialization are reflective of the values, behavior, and history of the organization. The socialization of new members represents core organizational processes. Collectively, the dimensions illustrate the holistic nature of organizational context. For example, the origins of the contemporary medical school curriculum can be traced to the 1910 Flexner Report. As a result, young doctors must demonstrate a high level of intellectual and professional expertise as well as a commitment to patient health as they progress through their program. Socialization is not solely related to the essential nature of being a member of community, but also to the processes prioritized in becoming a member. Table 1 summarizes the six dimensions of socialization presented by Van Maanen and Schein (1979). Structuralist perspectives regarding socialization My goal in the previous section was to outline the processes by which socialization occurs. I now examine the relationship between the organization, culture, and socialization. The most commonly accepted theory of socialization
35 Table 1: Dimensions of socialization Collective vs. individual
Newcomers enter either as a group or alone
Formal vs. formal
Newcomers are either isolated from or integrated with other members
Random vs. sequential
Newcomers have ambiguous or ordered requirements towards membership
Fixed vs. variable
Newcomers are offered a set timetable, or no timetable, for advancement
Serial vs. disjunctive
Newcomers interact with role models, or are given no guidance by a mentor
Investiture vs. divestiture
The organization welcomes or disregards the personal characteristics of newcomers
Adapted from Van Maanen and Schein (1979), Tierney and Rhoads (1994)
applied to doctoral students is drawn from the traditions of functionalism and structuralism. Such theories take a macro-sociological approach and focus on institutions and organizations as complex social systems (as opposed to a more focused study on the individual). As with any biological or mechanical system, multiple parts contribute to a systematic whole. The efficient operation of these parts enables the operation of the system. Organizations and institutions, as social systems, possess an underlying and often unobservable foundation. The goal of any system is
36 to maintain equilibrium; therefore, it is vital that systems govern individual behavior by social norms and rules. Disciplines are a specialized form of organization within higher education. They constitute the multiple parts that result in the systematic whole of the university. Becher and Trowler (2001) concluded that disciplines can be measured by “the number and types of departments in universities” (p. 25). Knowledge organization and development, according to Becher and Trowler, occur within a unique organizational form (p. 26). The individual’s role within the discipline is to interpret the validity of knowledge and, by extension, maintain the boundaries of the system. Acceptable knowledge is published in disciplinary journals, presented at conferences, and taught as a part of the curriculum to new students. Socialization is the means by which individuals come to understand these social norms. Rosaldo provided a useful summary of this perspective: …culture and society determine individual personalities and consciousness…with the objective status of systems. Not unlike a grammar, they stand on their own, independent from the individuals who followed their rules. Like the languages [humans] speak, culture and social structure exist before, during, and after any particular individual’s lifetime. (1989, pp. 3233) Parsons (1951) offered a two-fold description of socialization from the structural perspective. First, socialization is the process by which an individual internalizes the culture of a social system. The individual is socialized to normative behaviors that further the system’s well being. In addition, socialization occurs when an individual is prepared to assume an autonomous, independent role that serves
37 social interests. In the case of doctoral education, students progress through a series of activities with the end goal of becoming specialists in a particular discipline. Doctoral education, in Parsons’ terminology, can be best understood as a bridge between undergraduate studies and a professional identity; graduate education is a means to ensure that professionals within the same discipline or field receive similar training. Christopher is socialized to become a neuroscientist. He enters the doctoral program at Glenhaven, and, after five to six years of structured study, graduates with the Ph.D. degree in neuroscience. Figure 1 illustrates this perspective. According to Merton (1957), socialization is “a process by which people selectively acquire the values and attitudes, interests, skills, knowledge—in short, the culture—current in the groups in which they are or seek to become a member” (p. 287).
Figure 1: Linear model of doctoral student socialization Student is admitted to program
Student is socialized
Student graduates from program
The Mertonian perspective regarding socialization assumes that individuals are changed by their exposure to normative role dimensions. At the end of the socialization process, the individual has not only internalized a respective professional identity, but also the values and beliefs inherent with group
38 membership. Merton further argued that socialization was a process that occurred in stages. The first, anticipatory socialization, occurs when the individual clearly differentiates between the reference group and other social systems, and “becomes aware of the behavioral, attitudinal, and cognitive expectations held for a role incumbent” (Bragg, 1976; Merton, 1957; Weidman, Twale, & Stein, 2001, p. 12). The individual is outside of the system looking in, and is motivated to assume the perceived values and behaviors exemplified by the reference group. For doctoral students, this process frequently begins during undergraduate studies through exposure to faculty and advanced students in the respective system (the discipline). For example, many of the doctoral students at Glenhaven became interested in neuroscience through their undergraduate work in the biological or computational sciences. In the subsequent stages of socialization, individuals directly and indirectly are exposed to normative role expectations—or “the set of often diverse behaviors that are more or less expected of persons who occupy a certain defined position within a particular social system” (Merton, 1957; Parsons, 1951; Van Maanen & Schein, 1979, p. 28). In order to maintain what Parsons defined as the homeostasis inherent to the function of a social system, individuals are inducted and gain knowledge relevant to role performance. Bragg’s framework of socialization (1976) identified several interrelated behavioral and psychological steps inherent in this process, including observation, imitation, feedback, modification, and
39 internalization. Each step is a part of the continuous social development of the individual from an organizational outsider to a member of the social system. Individuals gradually abandon idealistic and sometimes stereotypical notions of the organization developed during anticipatory socialization. Becker and Geer (1958) detailed the socialization experiences of aspiring physicians; they described an “increasing cynicism” on the part of students in medical school. In the first year, for example, “students become cynical about the value of their activities...they feel that the real thing—learning which will help them to help mankind—has been postponed” (p. 52). Later, the student residency “further diverts the student from idealistic concerns...he finds himself low man in a hierarchy based on clinical experience” (p. 53). For medical doctors, gaining professional expertise is a long and sometimes unclear process, heavily controlled by the system. Individuals who enter an organization, such as students in doctoral or professional programs, are inducted in a continuous social process that entails observation, learning, and role modeling. Socialization is a “comprehensive and consistent induction” focused on the “acquisition of role-specific knowledge” (Berger & Luckmann, 1966, p. 130, 138). The inherent goal is modify the beliefs and actions of newcomers to fit the social norm, thus ensuring the survival and stability of the organization. Tierney (1997), in summary of Merton and the modern/structuralist definition of socialization, concluded that “culture is the sum of the activities in the organization, and socialization is the process through which
40 individuals acquire and incorporate an understanding of those activities” (p. 4). From the foundations of structuralism, socialization has been metaphorically described as a progressively “upward-moving spiral” or a “train leaving the station for a particular destination” (Weidman, Twale, & Stein, 2001, p. 5). In the case of doctoral students, individuals are expected to assume their proverbial seat on the train if they are to complete their degree program and become a member of a disciplinary community. Cultural perspectives regarding socialization Although the structural perspective has dominated the literature on socialization, emerging viewpoints place less emphasis on the social structures and more on the individual. From this perspective, socialization is a bi-directional, cultural interaction. This multidimensional interaction consists of the exchange of thoughts, actions, and beliefs that collectively shape the organization and the individual. For cultural theorists, the organization exists as a social construction. The unique aspects of social context shape its culture. The socio-cultural context, as Geertz (1973) has argued, consists of “webs of significance” within which individuals simultaneously exist and help create. The cultural perspective examines this process as one where both the individual and the organization are influenced through socialization. This perspective is a response to the structuralist approach that “splits the subject from the object” (Rosaldo, 1989, p. 41) and consequently examines the organization independent of those individuals within it.
41 Valimaa (1998, p. 119) defined academic worlds as “cultural entities that are based on social constructions of reality.” Within this framework, socialization is the process by which individuals come to recognize and interact with such construction. This perspective also recognizes the heterogeneity of culture. Organizational culture is the result of social contact among individuals who share membership in a specific community (Geertz, 1973; Tierney & Bensimon, 1996). Members of a disciplinary community do not share the same commitment to epistemologies, ideas, or concepts. These individuals are not part of a structured social system, but instead share a common, fluid space where “ideas exist in relation to one another” (Lattuca, 2001, p. 25). These ideas are reinforced through formal and informal interaction. As Van Maanen has suggested, Culture refers to the knowledge members (“natives”) of a given group are thought to more or less have; knowledge of the sort that is said to inform, embed, shape, and account for the routine and not-so-routine activities of the members of the culture…a culture is expressed (or constituted) only by the actions and words of its members. (1988, p. 3) In their study of faculty experiences, Tierney and Rhoads defined socialization “as a cultural process that faculty become enmeshed within—and change, as well” (1994, p. 1). As opposed to the structuralist theories of Merton, Parsons, and Becker, cultural theorists do not necessarily see the organization as a contained social system. The organization consists of two related components: first, the explicit, exterior rituals and processes such as structures, artifacts, symbols, and practices through which individuals participate; and two, the values or assumptions
42 exemplified by such elements (Denison, 1996). For example, doctoral neuroscience students at Glenhaven University undergo an orientation session when they begin the program. The messages conveyed by the orientation materials and topics influence how students come to see the program and their role as a community member. In addition, all students are required to complete a two-semester core class, which also emphasizes knowledge significant to community membership. Cultural theorists acknowledge that the organization consists of formal structures, such as committees, policies, and rules. Just as significantly, as Tierney and Rhoads noted, “[Organizations] revolve around informal codes and expectations shared by organizational participants” (1994, p. 1). Figure 2 represents this cultural perspective of the organization. In this model, the university is represented as an organization with multiple external influences. Therefore, doctoral student socialization is not a linear process, but rather a multidimensional, dynamic one, influenced by multiple internal and external elements. Doctoral student socialization is a process of sense-making and identity development within this context. The distinction between the structural and cultural perspectives is particularly relevant in terms of understanding socialization. The structuralist perspective associates culture with the taxonomic components of the organization. If the organization consists of stable, interrelated parts, then specific knowledge is associated with each component. For example, doctoral students would be expected to master specific, well-defined bodies of knowledge as they progress through the program. From this perspective,
43 Figure 2: Cultural perspective of doctoral student socialization
From Weidman, J.C., Twale, D.J., and Stein, E.L. (2001). Socialization of graduate and professional students in higher education: A perilous passage? ASHE-ERIC Higher Education Report No. 28(3). Washington, DC: The George Washington University, School of Education and Human Development. socialization is a one-way, linear process designed to incorporate newcomers into organizational patterns. Part of socialization, then, is the exposure to (and subsequent mastery of) associated knowledge. The transmission of associated knowledge ensures stability within the social system (Merton, 1957; Parsons, 1951). In contrast, cultural theorists maintain that members continually change (and are changed by) the
44 organization. Culture is not a self-contained unit, nor is knowledge a universally defined entity. The exchange and interpretation of knowledge influences the organizational structure and cultural context (Behar & Gordon, 1995; Geertz, 1973; Rosaldo, 1989). This exchange is at the center of the cultural perspective of socialization. Understanding the disciplines The question of culture and the nature of the organization are basic components of any discussion regarding socialization. I have outlined two forms of analysis, structural and cultural, that serve to explain how individuals interact with their environment, and what influences the individual brings to the organization. These two frameworks are also useful in understanding the disciplines and interdisciplinarity, a discussion to which I now turn. A structural analysis defines the disciplines as social worlds existing as part of the higher education framework. The cultural perspective views the disciplines as socially constructed and continually negotiated. Disciplines are “groups with shared commitments to certain activities, sharing resources of many kinds to achieve their goals, and building shared ideologies about [how to operate]” (Clarke, 1991, p. 131). Lattuca (2001) highlighted a useful portrait of interdisciplinarity from these two positions. “[A] structural analysis of the disciplines [helps] understand how interdisciplinarity transgresses…scholarly conventions,” she noted. The cultural focus illustrates that “disciplinary structures that are important to understanding
45 interdisciplinarity are not spontaneously constructed or magically maintained” (p. 25). Both positions are valuable perspectives for understanding interdisciplinarity. Previous research tends to focus on interdisciplinarity (or “boundary work” between and among the disciplines) in structural terms: as an anomaly, a historical event, or a developmental stage (Klein, 1990; Newell, 1998; Palmer, 1999). This perspective is aligned with a deceptively simplified account of the disciplines and their related institutional communities (departments). Interdisciplinarity exists because of the disciplines. To better understand this inherent relationship, I summarize the characteristics of the disciplines as related to knowledge production and cultural norms. Disciplines3 provide a community of practice, a controlled network of individuals sharing interest and expertise in a specific knowledge domain. Disciplines are the “prescribed structure for legitimate intellectual activity” (Mourad, 1997, p. 129). This perspective views the discipline as part of the organizational framework of higher education. Clark argued that the “university or college [is] a collection of local chapters of national and international disciplines” (1983, p. 31). The shared point of view is supported by social norms regarding behavior and scholarship; continuing the metaphor of the discipline as a social system, these social norms are designed to create homogeneity and stability. As a consequence, the discipline has economic and institutional influences; it confers a privileged status on 3
I acknowledge that individuals within the same discipline may hold different methodological, epistemological, and ontological positions. Lattuca (2001, p. 71) summarized this contradiction when she noted, “We reify the disciplines even as we acknowledge the depths of the divisions within them.”
46 selected individuals and creates further opportunities for employment and knowledge production. Disciplinary contexts are always related to the nature of knowledge (Braxton & Hargens, 1996; Neumann, 2001; Neumann & Becher, 2002). Becher and Trowler concluded, “The ways in which particular groups of academics organize their professional lives are related in important ways to the intellectual tasks on which they are engaged” (2001, p. 23). Kuhn compared disciplinary knowledge to a common language, a shared property of a community (1996/1962). The value given to particular areas of inquiry and the methods by which scholarship is pursued and acknowledged is directly related to an individual’s perception of the attitudes and expectations within the community. The community exists within the higher education framework. In this fragmented environment of knowledge, boundaries are often shared between disciplines: economics, political science, and mathematics, for example, or sociology and anthropology. The characteristics of the disciplines are frequently defined in binary, oppositional terms—the hard nature of knowledge in the natural sciences as opposed to the soft knowledge of the humanities and social sciences (Biglan, 1973); the tendency towards collaboration in the laboratory sciences compared to the isolated, lone scholar in the humanities (Knorr Cetina, 1999); the practical, applied character of the professional disciplines, such as education and law, as opposed to the more theoretical orientation of certain scientific fields of inquiry, such as physics (Whitley,
47 1977); the organized, bounded nature of the sciences as opposed to the looselyrelated, unrestricted humanities and social sciences (Pantin, 1968); or disciplines with mature, clearly established paradigms compared to those still in stages of paradigmic development (Kuhn, 1996/1962). These dichotomies are frequently utilized when discussing the nature of a discipline, and differences among the disciplines. For example, Kuhn’s concept of paradigms is commonly employed to discuss knowledge production, the disciplines, and research activities. As defined by Kuhn, paradigms are “universally recognized scientific achievements that for a time provide model problems and solutions to a community of practitioners” (1996, p. x). Paradigms serve as a framework for the operation and advancement of knowledge. This definition of paradigms assumes that knowledge is “firmly embedded in the educational initiation that prepares and licenses the student for professional practice” (p. 5). Due to the stringent nature of the curriculum, paradigmatic knowledge gradually assumes a “deep hold in the scientific mind” (Kuhn, p. 5). According to Kuhn, disciplines can ultimately be assessed, categorized, and deciphered based on the strength of these guiding paradigms. Biglan (1973) ranked the disciplines in terms of how disciplinary actors define and interpret their community. His analysis categorized disciplines as hard/soft and applied/pure. The hard/soft dichotomy relates to the degree of paradigm development, while the applied/pure distinction
48 denotes the degree to which disciplinary knowledge is utilized for practical, applied problems. Table 2 outlines Biglan’s typology of disciplines. Table 2: Classification of the disciplines by knowledge and culture Group
Knowledge
Culture
Physical sciences (e.g., physics)
Cumulative; atomistic
Competitive; gregarious;
Hard/Pure
(crystalline/tree-like);
politically well-organized; high
concerned with universals,
publication rate; task oriented
quantities, simplification; resulting in discovery Humanities (e.g., history) and
Reiterative; holistic
Individualistic; pluralistic;
Social sciences (e.g.,
(organic/river-like); concerned
loosely structured; low
anthropology)
with particulars, qualities,
publication rate; person
Soft/Pure
complications; resulting in
oriented
understanding/interpretation Applied sciences (e.g.,
Purposive; pragmatic (know-
Entrepreneurial; cosmopolitan;
mechanical engineering)
how via hard knowledge);
dominated by professional
Hard/Applied
concerned with mastery of the
values; patents submitted for
physical environment
publication; role oriented
Applied Social sciences (e.g.,
Functional; utilitarian (know-
Outward looking; uncertain in
education)
how via soft knowledge);
status; dominated by
Soft/Applied
concerned with the
intellectual fashions;
enhancement of (semi)
publication rates reduced by
professional practice; resulting
consultancies; power oriented
in protocols and procedures Adapted from Becher (1987), Biglan (1973), and Fry (2004)
49 This modern concept of the discipline is one characterized by categorical boundaries. We understand that the disciplinary knowledge of sociology, for example, is soft, qualitative, and reiterative by comparing it to hard, quantitative, and cumulative disciplinary knowledge of physics. Disciplines are bound by a foundational logic that influences core values, paradigms, and elements of knowledge production. In addition, this perspective of disciplines as binary opposites results in the conclusion that disciplines are stable, predictable, and autonomous. The uniformity of the disciplines, in terms of organizational structure, contributes to the intellectual foundation of the university. Each discipline is built upon a knowledge tradition. The network of disciplines and their structural community (the department) influences academic research, student learning, human resources, and fiscal decisions. “Disciplines are so powerful,” Burton Clark noted, that “they constitute a ‘first principle’ of the university” and knowledge production (1983, p. 29). The educational structure of the department is framed by “a theory of knowledge, in that they help define what currently counts as knowledge” (p. 26). Each discipline has a knowledge tradition, codes of conduct, common vocabulary, and a shared system of beliefs for its members. Each of these elements is part of a disciplinary culture, which I discussed previously. Becher and Trowler’s perspective on culture in higher education is significant here: By ‘cultures’, we refer to sets of taken-for-granted values, attitudes and ways of behaving which are articulated through and reinforced by recurrent practices among a group of people in a given context….[The] ways in which academics engage in their subject matter, and the narratives they develop
50 about this, are important structural factors in the formulation of disciplinary cultures. Together they represent features that lend coherence and relative permanence to academics’ social practices, values, and attitudes across time and place. (2001, p. 23) Accordingly, disciplinary epistemology (ways of knowing) and disciplinary cultures (ways of behaving, interacting, and believing) are interrelated and constitute what is understood to be an academic discipline. In Table 3, I summarize the five dominant characteristics of the discipline. Table 3: Characteristics of academic disciplines Community of practice
Individuals who share an interest in a particular knowledge domain
Economic and professional status
Individuals assume employment based on their training
Community of expertise
Individuals who share common training in a particular knowledge domain
Shared epistemology
Shared knowledge is validated and particular methodologies privileged
Shared location
Individuals are institutionally identified as members of a specific group
Disciplinary socialization Disciplines are constructed from the intersection of structural features and cultural elements; the result is a unique and often exclusive community. Before I turn to a discussion of interdisciplinarity, I focus on how individuals are socialized within the disciplines. Becher and Trowler (2001, p. 47, citing Geertz, 1973) argued, “In its
51 very nature, being a member of a disciplinary community involves a sense of identity and personal commitment, a ‘way of being in the world,’ a matter of taking on a ‘cultural frame that defines a great part of one’s life.’” The developmental process typically has its origins in undergraduate studies, and culminates in the completion of a doctorate or other terminal degree in the respective field. The organization of disciplines around topics and methods of inquiry requires that newcomers be inducted into disciplinary practice in an efficient manner. Becher and Trowler maintained, “Disciplinary socialization involves a number of different elements that are structural in nature, conditioning [the] accommodative process” of individual identity (2001, p. 48). The influence of the disciplinary ideology is particularly relevant. Ultimately, doctoral students must understand what degree of knowledge is required to suffice as acceptable inquiry within the discipline. The acquisition is not always formal; much of this process occurs through the development of tacit knowledge. As defined by Nahapiet and Ghosal (1998), tacit knowledge is embedded in personal experiences and bolstered by personal interactions, such as between the doctoral student and the faculty advisor, or between students working in the same laboratory. For example, Amy, a first-year doctoral neuroscience student at Glenhaven, explained how such interactions had increased her skills in science. Before starting the program at Glenhaven, Amy worked at a physiology laboratory, although she had no background in the field. She explained: I was very new, and had no idea what gels were, everything was new. But the [professor] wanted someone like that. She said her last tech was kind of stuck
52 in bad habits, [and] she wanted someone fresh and trainable.... [the senior technician] kind of trained me, although it was rough for the first few months. Amy worked in the lab for several months before enrolling at Glenhaven, and credits the position with providing “hands-on experience” with knowledge production. Yet during her first year at Glenhaven, Amy made the decision to work in a computational laboratory, despite her extensive experience in biological (“wet”) labs. Amy noted: It is different. I am not really used to this type of research. I had a meeting with [the professor] yesterday, and told her that I really liked the lab, but I am used to looking at proteins. It is hard to attack the question [in this lab]—you need a lot of statistics, and it is just different. So [the professor] is working with me—right now, I am in the middle of just researching a lot, reading up on different aspects of the project, and then trying to come up with where I am going to get my data set. Tacit knowledge, as seen through Amy’s background, is grounded in the knowledge, skills, and values needed for membership in the community. “Tacit knowledge,” concluded Delamont and Atkinson (2001, p. 101), “is a crucial component of all scientific work.... the tacit competence of practical skills in the laboratory is transmitted through oral culture, by means of trial-and-error, and through practical example.” Regardless of how such knowledge is transmitted, tacit knowledge is a vital component of the socialization process as the doctoral student moves from being a newcomer to a member of the disciplinary community. Understanding interdisciplinarity The training of doctoral students is structured by the disciplines. Students are socialized as members of a disciplinary community, and as such, internalize an
53 understanding of knowledge, boundaries, and values. I have summarized the characteristics of the disciplines, with particular emphasis on disciplinary socialization, and now examine the origins of interdisciplinarity. If the disciplines are an ingrained component of academic work, how are we to conceptualize interdisciplinarity? Efforts to understand interdisciplinarity must first, acknowledge the nature of the disciplines and second, understand the contested and various definitions of interdisciplinarity. Interdisciplinary knowledge is usually conceptualized in one of two ways. First, interdisciplinarity can be understood as a model drawn from the earliest scholars, such as Aristotle, who advocated for a unified science and generalized knowledge across the human experience (Klein, 1990; Newell, 1998). Christopher’s undergraduate experience with a “Great Books” curriculum is an example; through such a curriculum, students engage in sustained study of works of literature, science, and thought that have influenced the development of Western society. Second, interdisciplinarity is a phenomenon of more recent decades, the result of scholarly activity across the disciplinary boundaries of the university (Lattuca, 2001; MesserDavidow, Shumway, & Sylvan, 1993). The responses needed for social, technological, and other challenges require the expertise of scholars from multiple disciplines. For the purposes of this dissertation, I acknowledge the inherent relevance of the first definition, but concentrate on how interdisciplinary knowledge has evolved
54 in relation to the academic disciplines. My focus is on doctoral student experiences in an interdisciplinary neuroscience program that blurs the disciplinary boundaries of the university; I do not engage in what might be defined as a critique of the nature of neuroscientific knowledge, but rather an analysis of the culture in which such interdisciplinary knowledge is recognized and created from the perspective of doctoral students. The idea of the disciplines, according to Klein, is a 19th century connotation linked with several forces, including “the evolution of the modern natural sciences, the general ‘scientification’ of knowledge, the industrial revolution, technological advancements, and agrarian agitation” (1990, p. 21). The contemporary American university evolved with the disciplines as a part of its foundation. Students were recruited for training in a specific discipline. Businesses and industry increasingly demanded graduates with specialized training. This growth resulted in what Klein has labeled the “professionalization” of knowledge in the 20th century (1990). For the past century, the professionalization of knowledge has been organized by the institutional, political, and cultural confines of the disciplines (Vosskamp, 1986). Contemporary interdisciplinarity, then, developed as a reaction to the growth of the disciplines and the compartmentalization of knowledge. Examples of contemporary interdisciplinarity “Interdisciplinarity is usually advanced as a way of enhancing the disciplinary pursuit of knowledge of reality or the comprehensive application of
55 disciplinary knowledge to practical problems,” noted Mourad (1997, p. 135). I contextualize this definition by offering three examples of interdisciplinarity. I also seek to place the neuroscience program at Glenhaven within a contemporary interdisciplinary framework. These examples illustrate the range of private, federal, and international organizations involved in supporting interdisciplinary work at colleges and universities over the last century. First, the Social Science Research Council was founded in 1923 to encourage integrative and interdisciplinary methods of knowledge production. Disciplinary knowledge was seen as overly focused on theory and of little use in practice; pure knowledge (as opposed to applied knowledge) was ill suited to the demands of the evolving industrial society of the United States during this era. The SSRC focused on problem oriented, realistic, and applied scholarship in the social sciences (Fisher, 1993). Yet terms such as interdisciplinarity and integration were difficult to realize in reality. Klein concluded, “The terms…has no fixed or stable meaning. In the end, the dream of an universal social science never materialized, and many research teams wound up functioning in more ‘multidisciplinary’ than ‘interdisciplinary’ fashion” (Klein, 1990, p. 99). As the work of the SSRC illustrates, it is not enough to simply bring multiple disciplines together. Rather, the process of interdisciplinarity requires an integration of the disciplines to create new bodies of knowledge. In addition, in 1972, the Organization for Economic Development (OECD) produced what is still one of the most highly consulted references regarding
56 interdisciplinarity—Interdisciplinarity: Problems of Teaching and Research in Universities. The result of seminars and research into the topic that began in the late 1960s, Interdisciplinarity was influenced by the structuralist concepts of such theorists as Jean Piaget and Leo Apostel, and focused on how to bring individuals trained and located in different disciplines together to advance underlying theoretical systems for broad areas—a so-called “grand theory” for human life. In the report, Apostel defined interdisciplinarity as “the interaction between two or more different disciplines…from simple communication of ideas to the mutual integration of organizing concepts and methodologies” (1972, p. 25). The report further noted that interdisciplinarity was a challenge to universities, due in part to the existing segregated structure and independent functions of the discipline. A second OECD publication, Interdisciplinarity and Higher Education (Kockelmans, 1979), furthered the definition of interdisciplinarity as one that focuses on interactions between the disciplines. Interdisciplinarity exists on a continuum; this framework resulted in the development of numerous interdisciplinary typologies, which I discuss later in this chapter. The continuum is based on the degree of integration of disciplines. According to Lattuca (2001, p. 10), “Proponents of integration argued that interdisciplinary projects achieved a higher level of disciplinary integration than multidisciplinary projects that merely concentrated on disciplines or their components.” The challenge to interdisciplinary work, as argued by the OECD, was not only to bring the disciplines together, but to enable scholars to
57 abandon their disciplinary perspectives and focus on the development of “seamless” interdisciplinary knowledge (Lattuca, 2001; Rossini & Porter, 1985). Again, as seen in the work of the SSRC, interdisciplinarity requires utilizing the knowledge of multiple disciplines in an integrated approach. Also, since the post-World War II era, federal agencies such as the National Science Foundation (NSF) and the National Institutes of Health (NIH) have funded interdisciplinary and various types of applied research. Klein attributed this growth to technological, political, and intellectual needs. “The postwar status of the United States heightened the demand for interdisciplinary discourse across state political lines, corporate decision-making and planning, and a variety of state and political movements,” she wrote (1990, p. 35). Such demand heightened the belief that realworld problems are not necessarily equivalent to (or successfully solved by) disciplinary categories of knowledge. The NSF, for example, prioritizes funding for research programs that cross disciplinary boundaries; encourage collaboration of faculty and students across disciplines; expand skills and methodologies beyond a single discipline; and apply theoretical knowledge to pressing, practical issues. One recent NSF call for proposals regarding biocomplexity, a study of biological, physical, and social systems, encourages researchers to think in the broadest possible terms. The proposal describes some questions as example of this breadth: “Do the physical arrangement of genes in our DNA and neurons in our brains share patterns with the underground network of bacteria, fungi, and plant roots that nourish the
58 planet, and can computers be used to explore such large-scale networks? How do current property laws and age-old cultural norms affect the rate of deforestation in tropical regions? And what is the mechanism by which human activities affect species diversity?” (Mervis, 2005, p. 2068). A typology and characteristics of contemporary interdisciplinarity These examples of contemporary interdisciplinarity exhibit similar characteristics. First, researchers have commonly differentiated between endogenous and exogenous motivations for pursuing interdisciplinary research. Endogenous interdisciplinarity seeks “to produce new knowledge with the aim of realizing unity of science” (Aram, 2004; Klein, 1996, p. 12). Similar to the Aristotelian concept of knowledge—defined by logical thinking and the cumulative organization of all knowledge—endogenous interdisciplinarity is motivated by internal, institutional factors. The ideal of research that “follows where the data might lead” is an example of endogenous scholarship. This viewpoint can be problematic. As I previously outlined in this chapter, knowledge is neither anthropomorphic nor pre-determined. The definition of a problem and its solutions are determined by human action. For example, in terms of the brain imaging conducted in Christopher’s lab, formal mathematical analyses and computer models were developed to study the brain; the complexity of these models requires collaboration from numerous individuals in order to work effectively. Brain imaging alone is not inherently interdisciplinary. The complexity and breadth needed to conduct the work within the university is.
59 In contrast, exogenous interdisciplinarity results from pressures outside (or external to) the university. Exogenous pressures are common in the examples above. University researchers respond to the NSF call for proposals with research that will contribute to our understanding of interdisciplinary environmental, biological, or health conditions. The OECD reports were in part a response to the tumultuous and dynamic post-World War II era. Exogenous interdisciplinarity is assumed to be particularly valuable, and an effort to resolve social dilemmas to which the traditional academic disciplines have been unable to respond. Ultimately, both types of interdisciplinarity seek to fill the knowledge gaps left by the disciplines. Several interdisciplinary typologies have been constructed in recent decades (i.e., Klein, 1990; Lattuca, 1996). I utilize Lattuca’s (2001) typology of interdisciplinarity for this dissertation; her typology is particularly useful because of its focus on aspects of teaching, research, and practice that collectively result in knowledge and activities across disciplinary boundaries. She offered four categories. I summarize each category to offer the range of interdisciplinary work. First, informed disciplinarity is “essentially disciplinary in nature… motivated by a disciplinary question” (Lattuca, 2001, p. 82). Knowledge and theories from other disciplines are brought to bear on a specific area of inquiry, but only with the objective of further understanding in the original discipline. Scholars bring new knowledge into the disciplinary organization. The second example, synthetic interdisciplinarity, focuses on issues intersecting multiple areas of study, and serves
60 as a bridge between disciplines. The third category, transdisciplinarity, is the exploration of knowledge across disciplines, while the fourth category, conceptual interdisciplinarity, transcends the disciplines. Such inquiry is “without a compelling disciplinary basis” (p. 73) in mapping new areas of knowledge. Table 4 outlines Lattuca’s typology of interdisciplinary knowledge as related to teaching and research, and offers examples of research from each category. Table 4: Typology of interdisciplinary knowledge Type
Teaching
Research
Example of research
Informed disciplinary
Disciplinary
Disciplinary
Using physics to explain
courses informed
questions
biological theories and anatomy
by other
requiring outreach
disciplines
to other disciplines
Synthetic
Courses that link
Questions that
Urban studies, linking the
interdisciplinarity
disciplines
link disciplines
disciplines of sociology, economics, and political science
Transdisciplinarity
Courses that cross
Questions that
Sociobiology, a study of animal
disciplines
cross disciplines
social organization using genetics and evolutionary research
Conceptual
Courses without a
Questions without
Using feminist theory to broadly
interdisciplinarity
compelling
a compelling
study issues of gender
disciplinary basis
disciplinary basis
Adapted from Lattuca, 2001; Lattuca, 2003
61 Her typology explored two interrelated concerns: the nature of the questions asked in the production of knowledge and the degree of integration between established bodies of knowledge. Each of these concerns is related to issues of socialization previously outlined in this chapter. To understand the degree of interdisciplinarity, it is important to acknowledge those motivations for its creation. Klein (1990) identified five demands: the development of the sciences (including increasing specialization and elements common to multiple disciplines), student demand, issues of institutional administration, vocational needs, and the “original social demand” (new needs that are not satisfied by a single discipline) (p. 41). Interdisciplinarity is a means of responding to knowledge demands through various degrees of interaction and integration. In addition, Lattuca’s typology is relevant to this dissertation not only for the conceptual framework it offers to understand the degrees of interdisciplinarity, but also for its implications. Informed disciplinarity, for example, does not require faculty or doctoral students from a particular discipline to work outside their respective department. Students become socialized to the norms of a specific discipline. As an individual becomes progressively removed from a traditional disciplinary “home,” two changes occur: 1) fluency in the language, knowledge, and methodologies of multiple disciplines is required; and 2) the spatial location of individuals (both faculty and doctoral students), particularly in relation to their peers, becomes increasingly relevant. Christopher, for example, is only one of two
62 neuroscience doctoral students in his research laboratory. His laboratory peers are from other disciplines. As part of their laboratory interaction, a new language is formed that is built upon the shared foundation of their research interest, not any single discipline. The challenge of interaction becomes more difficult as the degree of integration increases in interdisciplinary work. Two common models of interdisciplinarity exist. The first (and most common) model assumes that individuals receive training in a specific discipline. Over the course of their professional careers, they are exposed to (or engage with) problems that cannot be solved by a single disciplinary approach. This dilemma dictates an interdisciplinary, collaborative approach, where multiple perspectives provide greater insight. Lattuca (2001, p. 61) equated this model with that of conceptual change, where “individuals modify their conceptions when they confront information that calls previously held beliefs into question.” This linear model also reinforces the definition of interdisciplinarity as grounded in the disciplines. It is helpful to think about interdisciplinary knowledge as being highly disciplined in its structure and development. Mansilla argued that interdisciplinary understanding is “deeply informed by disciplinary expertise” (2005, p. 17); that is, the foundation of interdisciplinarity is the knowledge and epistemology central to the disciplines. By conceptualizing interdisciplinarity as constituted by the disciplines, interdisciplinary knowledge can be defined as an extension of disciplinary knowledge.
63 This concept of interdisciplinarity has been characterized as “disciplined interdisciplinarity” (Delkeskamp, 1977; Klein, 1990; Messmer, 1978). Using this perspective, Christopher’s laboratory can be classified as one created by the addition of various disciplines. Figure 3 illustrates this concept of interdisciplinary, using the work of Christopher’s laboratory as an example. Figure 3: An additive model of interdisciplinarity
Cognitive science
Computer science Christopher’s Physics laboratory
Psychology
Physics
The extension of knowledge in the various disciplines has coincided to result in the construction of a research laboratory studying in multiple disciplines. The goal of the laboratory is to construct computational models of the brain related to cognition and perception; the students and faculty in the lab use psychophysical experimentation, physiological investigation, clinical testing, and computational modeling as research tools. Christopher’s advisor, Dr. Lin, has a Ph.D. in physics. Dr. Lin has collaborated and published with several other professors on campus, including faculty from psychology and biomedical engineering. Christopher’s peer colleagues are studying in psychology, cognitive science, and neuroscience. Each brings their professional
64 disciplinary background to the study of brain cognition and perception. The combined expertise in these various disciplines contributes to the work of the laboratory. A second concept of interdisciplinarity assumes that individuals are trained as interdisciplinary researchers, and approach knowledge production as a process outside of rigid disciplinary boundaries. In this sense, interdisciplinarity is not solely the addition and integration of knowledge from multiple disciplines. Such an approach is difficult to conceptualize, for previous reasons outlined in this chapter. Can there be knowledge without the disciplines? Can there be socialization without the disciplines? Lattuca (2001) notes that some scholars feel they have always perceived of knowledge in an interdisciplinary (or adisciplinary) manner, which she attributes to early educational experiences and personal identity. For example, one of Lattuca’s respondents, a self-described “philosopher/art historian,” claimed, “I became interested in the various perspectives by which I can understand art. And that very naturally led to some courses in sociology...and also to Continental philosophy...and critical theory” (2001, p. 66). In this instance, an individual’s identity defines knowledge production. In other cases, the field of inquiry stands apart from the disciplines; for example, the broad and complex nature of the human brain cannot be contained by a single discipline. One Glenhaven professor explained to me, “I don’t think you could find another example of interdisciplinarity like neuroscience. It really is so broad, and the fact that individuals from so many
65 different disciplines have been able to study it under one umbrella is a testament to that breadth.” The question of whether interdisciplinarity is the result of an additive relationship among the disciplines or the adisciplinary nature of knowledge is beyond the scope of this dissertation. The implications for knowledge production and doctoral student socialization, however, are significant, and I consider those questions here. An additive concept of interdisciplinarity assumes that doctoral students are trained and socialized into a single discipline, one that integrates with other areas to form an interdisciplinary body of inquiry. Doctoral students are trained as disciplinarians, master the core knowledge of the discipline and over the course of their career, collaborate with scholars from other disciplines or adopt new techniques to solve problems. This dissertation focuses on the second concept of interdisciplinarity. How are doctoral students trained as interdisciplinary researchers? What socialization experiences affect students who operate outside of the traditional disciplinary boundaries? In this chapter, I outlined the dynamics and processes of socialization with particular emphasis on the significance of the discipline for doctoral student socialization. The doctoral neuroscience students at Glenhaven University, however, do not operate within a single disciplinary paradigm. Instead, they are trained as interdisciplinary researchers. I explore the implications of such training in subsequent chapters.
66 CHAPTER THREE METHODOLOGY “My lab is looking at androgens,” Esther tells me. Her voice is lost in the loud hum of the refrigerator. I have asked her about the work of her research laboratory, located in a small building near the medical school. It is early on a Friday morning, and the space is practically empty—our only companions are some two dozen hamsters, housed in small, clear cages lining the wall. “What exactly that does, and what exactly testosterone does to neurons in terms of communication and strength of synapses, what exactly it is doing in the brain is largely unknown,” she continues. I automatically nod, although I am not sure I completely understand. Esther is one of the first students to which I have spoken, and concepts such as androgens and testosterone are largely unfamiliar. “And a lot of the effects of testosterone in the brain have been attributed to estrogen, because it gets aromatized. It doesn’t always get aromatized, but it can be.” I am too distracted by watching Esther work to immediately follow up with a question. As we talk, she has donned a white lab coat and plastic gloves, and delicately picks up a detached hamster brain (no bigger than an acorn) from a Petri dish on the counter. She punctuates her sentences with quick, efficient cuts with a sharp blade, creating tissue-thin slices of hamster brain which splash back into the clear fluid in the Petri dish. Esther is preparing frozen samples to place into a refrigerated chamber, or cryostat. “So my
67 project will take a stab at the obvious big question—what are androgens doing to neuroanatomy?” she concludes. An hour later, I leave Esther’s lab, pondering her story. Unlike many of the doctoral students in the neuroscience program, Esther completed a master’s degree before applying to Glenhaven; she lives with her husband in a suburban area far from campus, and cultivates the appearance of a serious, earnest scientist. She has a fluency and enthusiasm for science that some students seem to lack. A professor tells me that Esther is one of the best doctoral students in the program— she received the highest grades in the first-year core course. As I sit in my car, reviewing my notes and jotting down ideas, the elusive detail of Esther’s work frustrates me. How are the concepts of interdisciplinarity and neuroscience embodied through her daily actions? Has her previous experience in a master’s program influenced her success in doctoral studies? What knowledge did she utilize to accomplish her laboratory research? I am reminded how closely intertwined Esther’s story is with my own, and am frustrated by the question that lingers as I make my way out of the parking lot: How much of Esther’s work must I decipher to understand her experiences? “Scientists have an aversion to what nonscientists say about science,” Jonas Salk noted (in Latour & Woolgar, 1979, p. 11). He continued, “While such [nonscientific] examinations are of some value, they leave much to be desired because…they are not concerned with the substance of scientific thought and scientific work.” I argue in this dissertation that, in order to interpret the culture of
68 the interdisciplinary neuroscience program at Glenhaven, understanding how doctoral students frame scientific knowledge, apply such knowledge in their research, and undertake their professional careers is of necessity. As I outlined in chapter one, knowledge is an integral component of socialization—acquiring knowledge allows students to fulfill and perform a perceived professional role. Therefore, interpreting the “activity among tribes of scientists” (Latour & Woolgar, 1979, p. 17) offers a framework for understanding how doctoral students navigate the cultural terrain to assume the role of interdisciplinary neuroscientist. “The contextual grounding of the meanings of human actions and language is valid to our…understanding of our own and others’ behavior,” noted Mishler (1979, p. 1). Mishler’s “meaning in context” is particularly relevant to the question of scientific behavior, culture, and knowledge, as such concepts are inherently derived from situated human behavior. Doctoral students in Glenhaven’s interdisciplinary neuroscience program exist within multiple, overlapping social worlds. An intensive case study of the program participants was utilized to document these worlds and human behavior within them—all components of the program’s culture. In this chapter, I outline the methodology used to understand Esther’s work, and that of the other neuroscience students in Glenhaven’s doctoral program, as part of an interdisciplinary culture. First, I summarize the research design, and then detail the three-fold methodological approach utilized in this study: interviews, participant observations, and document analysis. I then discuss issues of validity and reliability
69 as related to my research design. Next, I outline the selection of doctoral students and faculty in the research, and finally, I detail the procedures used for data analysis. Research design “I am not a neuroscientist,” I initially tell Professor Bachman as I settle into an uncomfortable chair across from his expansive oak desk, awkwardly crossing my legs. “My background is predominantly in the social sciences, and my Ph.D. will be in education.” For some reason, my words assume the hushed tone of a confessional. Dr. Bachman is an outspoken, well-known professor at Glenhaven, and my first faculty interview. I am unsure of my rationale for providing this personal information. My uncertainty is compounded by his response. As he leans back in his chair, lacing his fingers tightly together, he replies, “I don’t know if I would tell people you aren’t a scientist, and I certainly wouldn’t tell them you are from education.” For the rest of the hour, I feel somewhat unbalanced as Dr. Bachman and I collectively navigate our conversation—he, the neuroscientist; me, the graduate student and educational researcher—concerning topics where he commands a practiced expertise. At the end of our conversation, he offers a somewhat uncomfortable compliment: “You are much too smart for education. You are smarter than your discipline.” I utilized an ethnographic, phenomenological case study to understand the stories of doctoral students enrolled in Glenhaven’s neuroscience program. This perspective encourages a focus on how individuals decipher their experiences within
70 a context of socially constructed, negotiated, and shared meanings (Merriam, 1998). Case studies are generally defined by three characteristics. First, “the single most defining characteristic of case study research lies in delimiting the object of study, the case” (Merriam, p. 27). I approached this study with the methodological goal of exploring the stories of individuals who were participants in a bounded system—that of the neuroscience program. Second, the unit of analysis in case studies is the experience as opposed to the individual (Polkinghorne, 2005; Yin, 2003). The unit of analysis is ultimately related to the definition of the guiding research questions. “Findings from qualitative studies,” wrote Polkinghorne, “provide an enriched understanding of an experience itself rather than how different individuals or groups vary in their [experience]” (2005, p. 141). In addition, case study methodology uses multiple research techniques to gather data. Research techniques are dependent on the nature of the case and the ultimate goal of the research. In formulating the research design for this study, I outlined the end goal of the project: to document student interpretation of the culture of an interdisciplinary neuroscience program and the subsequent effects on knowledge production and socialization for doctoral students. I chose a qualitative methodology for the following: 1) an interest in the process of cultural negotiation by individuals within the neuroscience program, rather than the outcome; 2) a desire to understand how “meaning” is constructed and interpreted by individuals; and 3) the motivation to allow students to verbally express their realities through their stories—all hallmarks
71 of qualitative research (Cresswell, 1994; Merriam, 1998). “Qualitative research,” explained Berg, “refers to the meaning, concepts, definitions, characteristics, metaphors, symbols, and descriptions of things” (1995, p.3). This definition spanned my research goal of understanding how students make sense of their environment and what effect the environment has on their commitment, motivation, and development. Qualitative research consists of two broadly defined and intricately connected experiences—the first occurring during fieldwork and data collection, the second during the process of analysis and writing. Each component is ultimately shaped by the researcher’s interpretation of events, narratives, and experiences. Before I explore how this dual nature of qualitative research influenced this study, I outline the research design and methodology. I was guided by three research questions, which I previously identified in chapter one: 1) How do doctoral students in an interdisciplinary program define their professional identity? 2) How do these doctoral students navigate disciplinary cultures to engage in interdisciplinary scholarship? 3) What skills, beliefs, and attitudes does interdisciplinary work in a doctoral program foster?
72 Gaining access This dissertation is based on a case study of an interdisciplinary doctoral program in neuroscience at Glenhaven University, a large, research-oriented institution, which occurred between March 2005 and October 2005. My initial interest was not in neuroscience or the “hard” sciences broadly; rather, I searched for an interdisciplinary program that offered the Ph.D. The search was more complicated than I initially envisioned. As I discussed in chapter two, the contested, complex concept of interdisciplinarity is difficult to define. Particularly at the graduate level, issues of curriculum and research are seemingly fluid, albeit it at different levels. For example, doctoral programs frequently require students to complete a “cognate,” a series of courses outside their main discipline. Most doctoral committees are comprised of an outside member, a professor not within the student’s primary discipline who represents the interests of the institution in the student’s research. Faculty are free to selectively choose and assign relevant texts for classroom study, and often cross disciplinary boundaries in doing so. But while “the institutional framework of the disciplines remains very strong,” noted Wallerstein (2003), “important crevices in the overall structure of knowledge” do exist (p. 454). The neuroscience program at Glenhaven University is an example of a curriculum created to explore these crevices. By traditional, institutional standards, the program is truly interdisciplinary—while the program is officially housed in Glenhaven’s College of Arts and Sciences, faculty are drawn from the departments
73 of biology, computer science, linguistics, philosophy, and psychology as well as the schools of gerontology, engineering, medicine, and pharmacy. Neuroscience is not an independent department. Doctoral students can engage in coursework and/or research from any of these areas. The fragmented, expansive nature of the program does have some negative consequences. The neuroscience program director, Dr. Quinlan (who is an appointed professor of biology, and during the course of this study, left the program to assume another administrative position at Glenhaven), refers to the neuroscience program as an “administrative nightmare.” Dr. Quinlan notes that the College of Arts and Sciences is the “main player” in terms of funding, although program monies are also available from the provost office at Glenhaven. Yet other affiliated departments, such as the medical school, “try to claim praise for the program, even though they really contribute nothing in terms of funding.” Ultimately, since the program is spread across two distinct campuses, the director maintains that “neuroscience interests have developed independently of each other.” This distance would later prove quite relevant during student and faculty interviews. My contact with the doctoral students in the neuroscience program began with a single email. When I met with Dr. Quinlan, he was enthusiastic about the project, and interested in knowing what could be learned to improve the educational experience of the neuroscience students. He provided the contact information for David Crigler, the student president of the neuroscience graduate forum, an association of all neuroscience students. Dr. Quinlan also agreed to keep me
74 informed of upcoming faculty and administrative meetings. Over the next few months, I attended five such meetings based on his invitation. My primary form of data came from student interviews. As such, I carefully composed my email to the student, anxious to ensure his involvement and the participation of students: David: I had a nice meeting with [Dr. Quinlan] today, and he suggested I contact you. Briefly, I am a Ph.D. candidate in the school of education doing a study on the experiences of doctoral students in interdisciplinary degree programs in the sciences. The [neuroscience program] here at [Glenhaven University] is my focus, and, after conversations with [Dr. Quinlan] and other faculty, I'm excited that the administration and faculty are supportive and interested in the study. Much of my study rests on student interviews. [Dr. Quinlan] suggested you would be the person to help in terms of contacting and recruiting students. It would be a one-time interview, 1-2 hours (with no compensation, unfortunately). How would you suggest getting started in this regard? I know there is an active graduate student group in [the program]. Is there an upcoming meeting, or an email listserve? I would also be interested in interviewing you regarding your experiences. My questions include: How did you decide to enroll in a neuroscience doctoral degree program? What is your perception of neuroscience as a discipline? What research area are you most interested in? Do you work with a faculty mentor in that area? How did that relationship evolve? I'm attaching a copy of the consent form for your information. What do you think? Fortunately, David’s response was both immediate and enthusiastic. The response did foreshadow a looming issue that I was forced to navigate over the next year in terms of coordinating interviews, focus groups, observations, and my attendance at faculty/administrative meetings.
75 Karri: I'd be more than happy to help you out. I'll try to email you sometime early next week to set up a day/time to meet up and talk (I'm a little swamped today to even think about next week)… However, I'm rarely on the main campus. Are you doing all of your interviews on the main campus...or do you think you might be able to come over to the [medical school] campus some days? There are about 10 [neuroscience program] students on the [medical school campus]...so you might be able to schedule a day or two over here that would be much more convenient for us. If not, I'll look into my schedule and try to figure out a block of time I can meet you on main campus. (I did my undergrad at Glenhaven on the main campus...so I know my way around). While the distance between Glenhaven’s main campus and its medical school is not large in terms of physical space, and the university has instituted a shuttle-tram program to facilitate travel between the two locations, the distance was at best inconvenient and at worst, frustrating for me as a researcher. In my efforts to interview as many doctoral students as possible, I traveled to the medical school campus frequently, juggling my own schedule and navigating traffic and parking. Beyond my personal experiences, however, the physical distance was looming for most of the doctoral students. Few, if any, doctoral students on the medical school campus came to the main campus with any regularity, missing such events as seminars or informal interaction with faculty and other students. A handful of doctoral students on Glenhaven’s main campus even admitted that they choose their research laboratory and faculty advisor based on the campus location, not necessarily the research topic. These students found it more convenient to be on the main campus rather than extending their commute to the medical school. I further explore the connotations of this dichotomous space in subsequent chapters.
76 Methodologies I utilized two primary forms of data gathering during this dissertation: individual, semi-structured interviews, primarily with doctoral students, but also with program faculty; and participant observation, observing various social, academic, and administrative program activities. I also conducted one group interview with four first-year doctoral students. Interview transcripts and fieldnotes were supplemented by program documents, including the course catalogue, admission and recruitment materials, and publications from neuroscience symposia held by the program. Interviews Interviews are considered a basic method of qualitative research where the goal is to gain a personal, in-depth perspective on a specific experience. Yet interviews are also a complex, contested process. “Interviews are not neutral tools of data gathering, but rather active interactions between two (or more) people leading to negotiated, contextually based results,” noted Fontana and Frey (2005, p. 698). Two issues are particularly important when considering the social construction of the interview. First, “interviewees are not so much repositories of knowledge as they are constructors of knowledge in collaboration with interviewers” (Jarvinen, 2000, p. 371). Rather than being seen as an interaction where the interviewer solicits facts and opinions regarding one’s personal experience, the interview is instead a very specific, contextual engagement of two or more individuals. In addition, interviews
77 are conducted within “a horizon of meaning” (Holstein & Gubrium, 1995); that is, the interviewer and the respondent are actively engaged in the construction of knowledge that emerges through an interview. Multiple meanings are possible. The “success” of the interview is dependent on the interviewer’s ability to actively engage in “interpretative practice” (Holstein & Gubrium, p. 18). Spradley (1979) defined three distinct forms of interview questions. The first, descriptive questioning, invokes what Spradley labeled the “grand tour” response. The goal is to elicit a “verbal description of significant features of a cultural scene” (p. 87). Such questions allow for the respondents to offer as few or as many details as they feel appropriate. Descriptive questions proved particularly useful for me early on in the data collection. For example, I asked Lisa, a fourth-year doctoral student and one of my first student interviews, to tell me about herself. As part of her description, she offered, “I work on the [medical school] campus in a lab that is interested in what happens to the brain with issues of injury and aging and neurogenerative disease, how the brain can compensate for the damage that happens with those factors.” Without a background in neuroscience or laboratory research, I had great difficulty picturing how such work was embodied, and what such efforts involved on a daily basis. Simply knowing what someone did for their research provided little for me in terms of understanding the context. As I neared the end of my interviews, my protocol was continually modified to gather more detail and description from the doctoral students. For example,
78 Kaitlyn, a first-year student, works in “wet lab,” which usually involves animal experimentation. I asked her: “If I followed you for a day in the lab, what would I see you do?” Her answer painted a portrait of her daily routine; I offer her full response here to illustrate the richness of the information. Hmm—well, coming in, checking my email [laughter], and then like right now, I have to analyze data, so looking at tons of images, we process all the brain tissue—I did in situ hybridization, which is interesting, where you incubate it with all these chemicals to get it somewhere where you can see signals from a specific peptide, so that is all done—that takes a long time. And you have all these slides with brain tissue on them, and it’s a radioactive signal, and you put the slide into this cassette with film—it is like Kodak film, that has an emulsion coating, and what you do is get an imprint on the film of this specific signal, and then you have to quantitate it and see—you have all these slides from different manipulations of your animals, and you want to compare if it has an injection of this drug or not, or whether it’s missing its adrenals or not, does that affect somewhere in the brain? Right now, I am looking at all the films, and you have to take pictures with the microscope of the nucleus, and how much gene expression you are getting, and then compare that—so basically that is what I am doing, I sit at a computer and look at all of these images that look like butterflies, and run statistics in Microsoft Excel. So that is what I do now… Structural questions are asked concurrently with descriptive questions to enhance the response. Such questions are designed to “discover information about the domains, the basic units in an informant’s cultural knowledge” (Spradley, 1979, p. 60). How do individuals classify their knowledge and experiences? A common structural question I employed throughout the interviews was “How would you personally define neuroscience?” This question was particularly effective when asked in context. For example, Amanda, a first-year student, offered a long definition of neuroscience before concluding, “I mean, a short answer would be that it is the
79 biology of psychology.” I responded, “I like that one, I haven’t heard it from any other student.” Amanda laughed, and added, “That doesn’t surprise me. Everyone else is probably like ‘oh, it’s the biochemical nature of brain cells.’” Amanda’s orientation to neuroscience is rooted in her psychology/linguistics background and research interests, as opposed to the biological orientation of many of her peers. The third type of interview question, contrast questioning, is to determine “what an informant means by the various terms used in his native language” (Spradley, 1979, p. 60). The goal is to restate and incorporate terminology utilized by the respondent to gain a clearer understanding of the experience. After Amanda defined neuroscience, and outlined her research interests, I was quite interested in her concepts of neuroscience and linguistics. Only a handful of doctoral students in Glenhaven’s neuroscience program have this focus; linguistics is a relatively small component of the broader field of neuroscience. How did Amanda understand them fitting together? “Neuroscience and linguistics—there seems to be quite a dissonance there…” I offered. Amanda responded: Right, linguistics is very different than neuroscience, it is much more theoretical. But there is a nice little stepping stone to psycholinguistics, and it brings in grammar and how people react to different grammar and sentence structure and meanings, so that is a nice steppingstone to the neuroscience, like the brain imaging. You get some idea of what is going on, like when you get meaning from a word, and when you resolve the ambiguous meanings of certain words. By explaining the definitions and differences between the two concepts, I was able to better understand Amanda’s perspective regarding the connection between the fields.
80 I interviewed 40 doctoral students in Glenhaven’s neuroscience program from March 2005 to October 2005. This dissertation is primarily based on their stories. I also conducted a group interview with four doctoral students who had just completed their first year in the program and worked in various labs on the main campus. I contacted most of the 40 students directly to arrange for an interview, although a few students emailed me to express their willingness to participate. I also interviewed five Glenhaven faculty who are affiliated with the neuroscience program. In some cases, I was able to interview both the professor and the students who worked in his/her lab—but not always. With the student’s permission, I introduced myself to faculty by noting that I had spoken to one of their students. Participant observation Atkinson and Coffey noted, “Social life is [both] performed and narrated” (2002, p. 802). In addition to 46 doctoral student, faculty, and group interviews, I also participated in several program activities. Observation as a research technique is generally considered “the fundamental base of all research methods in the social and behavioral sciences” (Angrosino, 2005, p. 729). During the eight-month study of Glenhaven’s neuroscience program, I observed nearly 30 hours of program events. The postmodern concept of culture implies that culture itself cannot be seen by observers, but is instead represented through its members. This perspective acknowledges existing historical and social forces that influence the organizational culture; such forces are individually interpreted and negotiated by the participant.
81 Documenting the elusive phenomenon of culture requires “the full-time involvement of a researcher over a lengthy period of time (typically unspecified) and consists mostly of ongoing interaction with the human targets of study on their home ground” (Van Maanen, 1988, p. 2). While I take issue with Van Maanen’s “human targets” terminology, the implication is significant—understanding culture requires observing both the performance and the narrative. The weekly seminars, where attendance is required of first-year and secondyear doctoral students, proved an excellent opportunity to meet students and gather information on individual research. Faculty and administrative meetings were also particularly informative. During one marathon three-hour meeting, a nine-member faculty committee discussed the progress of each doctoral student enrolled in the program. In another, faculty argued regarding the relationship of the neuroscience program to other departments on campus, specifically Glenhaven’s large biology program. Meetings of the neuroscience graduate association provided an excellent opportunity to both meet students and watch their interaction in a communal context. I also observed several dissertation defenses, two of which featured students I subsequently interviewed for this study. Engaging in observation contextualizes student experiences, and acknowledges that individual biographies are shaped by a unique cultural context. Utilizing both interviews and observation as data-gathering techniques enabled a more complete understanding of student experiences. Becker (1970; also Becker,
82 Geer, Hughes, and Strauss, 1961) maintained that observation enhances the understanding of events, actions, and behaviors that can be solely gained through interviews. A brief example is in order to illustrate how the dual nature of interviews and observations (and the relationship between them) enhanced the data collection in this study. All doctoral students in the neuroscience program who have completed coursework must give an annual hour-long presentation regarding their research. First-year and second-year doctoral students are required to attend, and receive course credit for doing so. The student’s advisor and committee members are typically present. I attended Diane’s presentation in late April as she outlined her research in brain function and anatomy. In my observation notes, I wrote, “Much of her work is produced by very time-intensive techniques, it seems. What is her lab environment like? How did she acquire these skills?” Diane also frequently mentioned the work of Dr. Smith, who is a neuroscience professor at Glenhaven—but not on Diane’s committee. “Is there an interaction between them?” I asked in my fieldnotes. Two weeks later, Diane agreed to meet with me in her lab for an individual interview. Before our meeting, I reviewed my observation notes from her presentation and used that additional information to modify my interview protocol. The transcript from our interview reveals this influence—for example, I asked, “At your presentation, you mentioned Professor Smith and his work. His lab is on the floor above you, right? Do you have any interaction with him or his students?” Not all doctoral students gave a
83 presentation during the time of my study, nor was I able to attend every student presentation over the course of data collection. Yet for those presentations I observed, as well as faculty and student meetings, program symposium, and recruitment events, my interview protocol was enhanced, and my interpretation of the program culture was sharpened. Atkinson and Coffey (2002), however, offered a significant caveat to the dualistic, complementary nature of interviews and participant observation. The strategies should not be seen as strictly additive. They noted, “We cannot assume a unitary and stable social world that can simply be viewed from different standpoints or different perspectives” (p. 807). The methods adapted by researchers influence, to some degree, the “reality” described. The concept of reflexivity is significant here, the goal of which is “to produce research that questions its own interpretations and is reflexive about its own knowledge production towards the goal of producing better, less distorted research accounts” (Pillow, 2003, p. 178). Reflexivity is a concept with multiple interpretations. Guba and Lincoln noted that reflexivity is “the process of reflecting critically on the self as researcher” (2005, p. 210) with an emphasis on understanding how the process of data collection shapes the research. I managed questions about my role as a researcher through a personal journal. My goal was to identify and manage my personal involvement with the students in the program as the research progressed. In particular, I focused on the dilemma inherent in the application of interpretative methodological techniques to
84 study a quantitative, laboratory science. Being from the professional discipline of education, with training in the social sciences, my background also seemed to be starkly separated from many students within neuroscience. This distinction was at times problematic, as doctoral students discussed their work in detail and shared the nature of their research interests. Other forms of data collection Although interviews (with individual students and faculty, as well as one student group) and participant observation served as the primary methods of data collection, I also collected and reviewed program documents as part of this study. I reviewed the course catalogue; materials from the Society for Neuroscience that were available in Glenhaven’s neuroscience building (such as Brain Basics: The Life and Death of a Neuron and Know Your Brain); a syllabus for all modules in the firstyear core course; abstracts of research conducted by neuroscience affiliated faculty, available through the National Institute of Health; university news releases and articles regarding the neuroscience program; and schedules from various neuroscience symposia held at Glenhaven during the time of my study. Through document analysis, my goal was to better understand the institutional and social context in which the neuroscience program existed. A ten-year comparison of Glenhaven’s course catalogue, for example, revealed changes in course requirements, affiliated faculty, and the name of the program. NIH research abstracts were reviewed before interviewing respective doctoral students and faculty to gain a
85 preliminary understanding of their laboratory work. While not a primary source of data, document analysis supplemented interview transcripts and fieldnotes, and allowed for a unique source to compare and contrast emerging themes. In Table 5, I summarize the methodologies utilized for this study, the frequency in which they were used, and the timeline for data collection. Table 5: Research methodologies utilized in dissertation Method
Targeted group
Frequency
Timeline
Interviews
40 Doctoral students
Single interviews, 1-2
March—October 2005
enrolled in
hours
neuroscience program Interviews
5 neuroscience faculty
Single interviews, 1-2
March—October 2005
hours Group interviews
Four first-year students
A group interview, 1 ½
August 2005
hours Observation
Specifically focused on
At least one program
doctoral students
activity, seminar, or
March—October 2005
class on a weekly basis Document analysis
Website, application materials, syllabi
As available
March 2005—October 2005
Throughout this dissertation, doctoral students and professors are identified by pseudonyms. Any identifying information (i.e., work with a unique animal species) is also modified to protect individual privacy. Records, such as interview transcripts
86 and contact information, were maintained in order to preserve anonymity. A more detailed discussion regarding the protection of human subjects and IRB protocol as well as the interview protocol used with students and faculty is included in the appendix. Validity The challenge of defining validity in terms of interpretative research is related to the positivist, rational origins of the term. Lincoln (2001) noted that “validity is a property or characteristic of both the products and processes of interpretive work” and is ultimately itself a social construction (p. 38). In this study, I was guided by four standards of qualitative validity as proposed by Eisenhart and Howe (1992). First, “research questions should drive data collection techniques and analysis, rather than vice versa,” the authors noted (p. 658). Doing so ensures that the researcher is motivated by questions that guide the work, rather than techniques that produce it. This study originated from a single research question: How do doctoral students in an interdisciplinary program experience socialization over the course of their studies? My research design is grounded, therefore, in the perspectives of individuals within an interdisciplinary program—primarily doctoral students, and to a lesser degree, faculty and administrators. In order to gather student interpretations, I utilized interviews as my primary source of data collection. Participant observation, faculty and group interviews, and document analysis were used to supplement the interview transcripts. As I previously noted, such
87 techniques are not necessarily additive, yet they do provide a broader picture of cultural life. These multiple methodologies allowed me to record the voices of students, observe their actions (and interactions), and review documents related to their lives as doctoral students. In addition, techniques of data collection and analysis should be utilized effectively. “It is incumbent on educational researchers,” stated Eisenhart and Howe, “to locate their work in the historical, disciplinary, or traditional contexts in which the methods used have been developed” (p. 659). For this study, the successful and efficient use of research methodology resulted from clear definitions of key conceptual terms used throughout my research—such concepts as culture, socialization, identity, and knowledge. These concepts are not generally considered ideas that can be precisely represented through statistical inferences or numerical data. Defining these concepts allowed me to shape my research design in order to accurately interpret student experiences. Knowledge, for example, is closely associated with the concepts of culture and socialization. In short, “the production of knowledge [is] socially and historically constructed and [is] the consequence of power” (Tierney, 1991, p. 7). I assume that culture is “a rich and complex text, with a subtle patterning influence on social life” (Alexander, 2003, p. 22). The “interdisciplinary culture” of the neuroscience social world at Glenhaven is revealed through the words, actions, and perspectives of its members. In this sense, the boundaries of knowledge are not rigid, fixed disciplinary
88 structures. Doctoral students in Glenhaven’s interdisciplinary neuroscience program actively engage in the creation and interpretation of knowledge, in turn setting individual (and sometimes contested) knowledge boundaries. The goal of this study, therefore, was to determine how students negotiated these boundaries. Eisenhart and Howe further maintained that “the assumptions and goals embedded in the development and conduct of the study must be exposed and considered” (p. 659). In particular, the prior knowledge of the researcher “must be made explicit if [it is] to advance, rather than obscure, the validity of the research argument” (p. 659). To further the understanding that my own perceptions played a role in both data collection and analysis, I have chosen to adopt a writing style throughout this dissertation that reflects my individual involvement in the production of this study. This choice is more than stylistic; rather, the choice reflects three factors—one, that value exists in the presentation of multiple truths and perspectives, including my own; two, that writing involves a series of active, engaged choices; and three, that the process of writing is not a task reserved for the end of a study, but is an “integral part of fieldwork” (Emerson, Fretz, & Shaw, 1995; Marshall & Rossman, 1997; Tierney & Lincoln, 1999; Wolcott, 1990, p. 127). Questions of validity also include questions of value constraints. Two factors are important here: one, external value constraints, where the research informs and improves upon practice and two, internal value constraints, or the ethics of the research. Education as a discipline occupies an integral link in the connection
89 between research and practice; my research is closely related to my interests in understanding and improving the learning experience. Research studies should be not only valid in terms of methodological rigor, but also in terms of implications for educational practice. Eisenhart and Howe defined external validity as the “so what?” question, also commonly expressed as the “should-do-ability” of a research study (Marshall & Rossman, 1999, p. 9). In the case of this dissertation, I constructed the research question based on several motivations: the low rate of degree completion by doctoral students (Lovitts, 2001); concerns regarding socialization of doctoral students in terms of their future social role as educators and leaders (e.g., Austin, 2002a); and the rapid growth of knowledge in the new century (Nowotny, Scott, & Gibbons, 2001). The internal validity of research relates to “the way research is conducted visà-vis research subjects, not with the (external) value of the results” (Eisenhart & Howe, p. 661). In this study, I found that establishing trust with students and being open about the purposes and goals of the research not only bolstered internal validity, but also strengthened data collection and analysis. The question of internal validity is “closely tied to issues of how and where knowledge is created, as are enduring questions of privacy [and] confidentiality” (Olesen, 2005, p. 254). During my interviews, I spent several minutes at the onset describing informed consent forms and methods of ensuring confidentiality. Each individual was subsequently identified only by a pseudonym and identifying details of their research (i.e., their
90 experiments on a unique animal species with which no other researchers at Glenhaven worked) were altered if needed. The students “The focus of qualitative inquires is on describing, understanding, and clarifying a human experience,” Polkinghorne wrote. “It requires collecting a series of intense, full, and saturated descriptions of the experience under investigation” (2005, p. 140). In terms of collecting the descriptions, Polkinghorne further noted that qualitative researchers engage in selection as opposed to the process of sampling, common in quantitative methods. “Participants and documents for a qualitative study are not selected because they fulfill the representative requirements of statistical inference, but because they can provide substantial contributions to filling out the structure and character of the experience under investigation,” he concluded (p. 141). During the time of this study, 80 doctoral students were enrolled in Glenhaven’s neuroscience program. Approximately half of the students were women. Dr. Quinlan, the program director, noted that some 40 percent of the students were international with a large number of these from China or India. I used these percentages as guidelines in terms of interviewing students. In addition, the neuroscience program is organized with five research areas: cellular and molecular neurobiology, behavioral and systems neurobiology, cognitive neuroscience, computational neuroscience and neural engineering, and the neuroscience of aging. I
91 was interested in the relationship between these various areas of study; as such, I sought doctoral students conducting research in the various concentrations. Forty doctoral students were interviewed for this study. Over half (53%) of these students were women, and 13 (approximately 33%) students were international. After I contacted David, the president of the neuroscience graduate student association, he sent out an email message to the group’s listserve with information about my research project and my contact information. My first three interviews were students who contacted me directly after receiving this email. These students provided the names of peers either in their cohort or lab who might be willing to participate. Dr. Quinlan, the program director, also provided the names of students. I contacted the remaining students directly, introducing myself and asking them to speak with me. From the students I contacted, I had only two directly decline—the first cited issues of privacy, the second claimed his schedule was just too busy. I also conducted one group interview, which consisted of students I had previously interviewed. The faculty In addition to student interviews, I also conducted five faculty interviews. Faculty interviews were a supplement to the stories and experiences of the doctoral students in the program. In many cases, my interviews with faculty provided an indepth understanding of the contextual factors that influenced a student’s experience. After my interview with the student, I asked if the student felt the faculty advisor
92 would be an appropriate person to contact for an interview. In some cases, a student’s response provided additional information regarding the environment of the lab. For example, one student had been enrolled in the neuroscience program for almost a decade. When we initially spoke regarding his advisor, a well-known expert in his field, I said, “I’ve heard a lot about him.” The student shrugged, and mumbled, “I don’t think you will have a chance to meet with him.” I had heard similar comments from other students about the same professor. “Is he not around much?” I asked, anticipating the answer. With an edge in his voice, the student responded, “He’s not around for me or any of his other students, so I don’t think he would be around for you.” Later, I would realize the accuracy of the student’s comments—my attempts to meet with his faculty advisor were frustrating and unsuccessful. The five professors with whom I spoke had been affiliated with the program for various times. Some had been with the neuroscience program since its inception. Others had only recently become affiliated, usually as a result of advising a neuroscience student or agreeing to have a neuroscience student work in their laboratory. While I use information gained from all interviews, observations, and document analyses during this dissertation, I organize the following chapter as a series of three ethnographic vignettes and discussion. Anthropologist Jean-Paul Dumont, in his ethnographic study of life in the Philippines, noted that ethnographic vignettes characterize “a plurality of images” (Dumont, p. 1) that are representative of the experiences of participants and the researcher. The three stories in chapter
93 four are drawn from my interviews and observations of doctoral students in the neuroscience program. I interviewed two of the three students for a second time near the end of this study, asking them to comment on my emerging themes as well as respond to follow-up questions from the initial interview. I summarize characteristics of each of the students here to serve as a guide for the following chapter. (A full description of all the doctoral students interviewed for this study is included in the appendix.) •
Victor is a first-year doctoral student. Originally from Peru, he came to the
United States five years ago to study for a master’s degree in computer science. During his master’s degree, he became interested in artificial intelligence, and sought a doctoral program that allowed him to research the human brain and its relationship to robotic engineering. Although Victor feels his “computer science friends” are proud of accomplishments, he also thinks that no one really understands the choices he has made or the work he is doing. •
Megan graduated from the GU neuroscience program in 2003, and is now a
postdoctoral researcher at the GU school of pharmacy. Before her doctoral studies, she was interested in issues of psychology and biology. She found neuroscience to be an ideal bridge between the two. Now that she is working in a different field (pharmacy), she is uncertain as to her neuroscience background, and even more uncertain as to describe herself. When I ask her to do so, she replies, “I guess—
94 I guess just a neuroscientist. No. I guess I would say I am a scientist and I do aging research. That is what I say right now. Some day I will say aging and neuroscience, hopefully.” •
Jonathan is a fourth-year doctoral student who researches the impact of
Alzheimer’s disease on speech and language. He completed his undergraduate studies in Spanish. He originally enrolled in the doctoral linguistics program at GU. Although he was interested in neuroscience, he worried that the work required would conflict with his strongly-held ethical beliefs against animal research. Only after doing further research into neuroscience and speaking to GU neuroscience faculty did he determine he could engage in neuroscience without working with animals. Jonathan is married; his wife is also a full-time student, completing her undergraduate degree. Data analysis Culture is an elusive concept, negotiated through the actions and interactions of individuals, and by the interpretation of their words, behaviors, and meanings. Cultural analysis, then, “is sorting out the structures of signification… and determining their social ground or import. Doing an ethnography is like trying to read (in the sense of ‘construct a reading of’) a manuscript” (Geertz, 1973, p. 20). Since culture is not a pre-determined entity, waiting for the researcher’s analysis, the process of cultural analysis is particularly relevant to understanding the research
95 design and methodology. “The activity of making sense of, interpreting, and theorizing the data,” concluded Schwandt (1997, p. 5), “is both art and science.” Each of my student, faculty, and group interviews lasted for approximately one hour, although some were as short as 35 minutes and others as long as an hour and a half. With individual consent, I audiotaped each interview. Each interview was transcribed verbatim—some with the assistance of Dragon Naturally Speaking, a voice-recognition software. Both the positive and negative effects of utilizing software to record and transcribe qualitative interviews have been documented (e.g., Coffey, Holbrook, & Atkinson, 1996; Fielding & Lee, 2002; Weitzman & Miles, 1995). I found the software somewhat cumbersome and difficult to master. Ultimately, the benefits of transcribing each interview “by hand” were significant. The time spent transcribing the interview was, in effect, time spent conducting the interview for a second time. Several of the themes and organizing concepts presented in this dissertation originated during transcription. After transcription, I offered each participant the chance to review his or her transcript for further comments and/or edits. Most had not further comments, although a few did use the opportunity to expand on portions of the conversation. As Merriam (1998) explained, “The process of data collection and analysis is recursive and dynamic” (p. 155). The interconnected nature of the process means that “data analysis” is not a grand act reserved for the end of data collection, but rather an ongoing, continually evolving process that the researcher originates from
96 the onset of her study. “Our wealth of perceptions expands as our awareness of categories expands,” argued Peshkin (2001, p. 239). After interview transcription, for example, I subsequently modified my interview protocol to include questions that were particularly relevant, delete those that were ineffective, or alter questions that were ill-worded. In order to sort through “the cultural structures of signification” (Geertz, 1973), I adapted a modified protocol for each interview, aligned with emerging themes and concepts. I ultimately allowed the words, experiences, and thoughts of the students to shape the data analysis. As Rubin and Rubin (1995) noted, this approach mandates “systematic efforts to really hear and understand what people tell you” (p. 17). Conclusion In this chapter, I outlined the development of this dissertation—the selection of methodologies and participants; the significance of validity; and my methods for data analysis. Ultimately, the research purpose serves as guiding criterion for the selection of methodologies, participants, and design. My goal is to document the perspectives of doctoral students enrolled in an interdisciplinary neuroscience program regarding socialization. While the socialization literature has increasingly focused on the experiences of doctoral students, narratives from students enrolled in interdisciplinary programs and from scientific disciplines has been lacking. The central role that students would take in the research was a pre-determined guideline. While the words and stories in this dissertation belong to the individuals in GU’s
97 neuroscience program, the interpretation presented in these pages is my own. The researcher’s obligation is to ensure an accurate, honest, and fair portrayal of these stories—an obligation I sought to satisfy by such measures as involving the participants in research development, seeking multiple sources of information, and documenting my personal responses to data collection and analysis. In chapter four, I utilize a series of ethnographic vignettes (drawn from my interviews and observations) to convey the multitude of student experiences involved within an interdisciplinary program. I use these stories and their implications as a framework for a summative discussion in chapter five.
98 CHAPTER FOUR CONSTRUCTING INTERDISCIPLINARITY The American model of doctoral education in the sciences, defined by an intensive research experience and a curricular focus on disciplinary foundations, has provided a strong framework for the education and training of future scientists for the past half-century. The acquisition of research skills is central to doctoral training in the sciences (COSEPUP, 1995). Such skills are supplemented by “a comprehensive understanding of the current state of knowledge and techniques in a field” (COSEPUP, p. 50). The rapid development of knowledge in the new century, however, challenges the focus of the traditional model of doctoral education on the production of a narrow disciplinary specialist. Scientific demands increasingly require individuals to engage in research and knowledge across disciplinary boundaries. This chapter examines how doctoral students enrolled in an interdisciplinary neuroscience program experience processes of socialization. The Glenhaven course catalogue notes: The Graduate Program in Neuroscience offers a highly interdisciplinary approach to understanding neural function. Our environment promotes interactions between scholars working at different levels of analysis, including scientists engaged in research on cell-molecular neurobiology, systems-level analysis of neural circuits, and cognitive neuroscience. Students in our program come from various backgrounds, and are able to pursue study in a wide range of neuroscience areas.
99 I consider how the interdisciplinary breadth of neuroscience affects doctoral student socialization in three interrelated areas: 1) knowledge acquisition, 2) identity development, and 3) disciplinary/community integration. These concepts are drawn from Weidman, Twale, and Stein (2001). As I outlined in chapter two, Weidman et al. discussed several stages of socialization, including a formal stage, where doctoral students complete a required curriculum and participate in research; an informal stage, where role expectations are internalized through interaction with the reference community; and a personal stage, where the individual develops a professional identity respective to the respective discipline. Knowledge acquisition is a significant component of doctoral student socialization and development. Individuals engage in the epistemic culture of the academic community. As doctoral students acquire knowledge and develop skills as researchers, they assume a congruent identity related to the discipline, the institution, and the profession. Identity development serves as a means of community integration. For doctoral students in a highly interdisciplinary neuroscience program, however, significant reference communities can be multiple; such communities are experienced and defined as part of the socialization process. Doctoral education offers the highest level of training available in the disciplines. Doctoral students gain an understanding of the field of inquiry—its foundations, privileged epistemologies and methodologies, and boundaries—through socialization. Students advance through various academic, social, and institutional
100 stages, which are organized to produce scholars who are engaged, committed members of the community. From this perspective, if the disciplines are the core component of structures of knowledge, then interdisciplinarity is understood to be an extension of disciplinary knowledge. Researchers are required to transgress, eliminate, or re-define disciplinary boundaries in their pursuit of interdisciplinary knowledge. This study seeks to expand on the concepts of socialization and disciplinary knowledge by examining how doctoral students experience socialization in an environment created by the integration of multiple disciplines. From this perspective, interdisciplinarity is not simply an extension of disciplinary knowledges, but rather is actively created as part of the student experience. How doctoral students acquire knowledge, develop their identities, define their communities, and understand the disciplinary structure of the university are highly relevant. Figure 4 illustrates the relationship of these factors to interdisciplinarity and doctoral student socialization. These themes are the focus of this chapter. Each theme in this chapter is introduced by an ethnographic vignette drawn from interviews and observations of three doctoral students, who were presented to the reader in the previous chapter. Acquiring knowledge: Victor This was a lot different than working with a computer, Victor first thought, as he gingerly maneuvered the scalpel inside the dog’s brain. The comparison was natural. After all, he had spent the last eight years living in front of a computer screen. Victor
101 Figure 4: Interdisciplinarity and doctoral student socialization
Disciplinary and community integration: Disciplinary cultures, knowledge context, and social reference groups
Knowledge acquisition: Curriculum, faculty interaction, laboratory research, and professional memberships
Interdisciplinarity and doctoral student socialization
Identity development: Laboratory work, disciplinary (academic) cultures, and knowledge acquisition had always enjoyed computers and engineering. As a boy growing up in Peru, his deftness with tools and mathematics quickly landed him in the prestigious science track of the public school system. He came to the United States after earning an undergraduate degree in computer engineering, and spent another three years
102 studying for a master’s degree in computer science. The result, he later decided, was that he had been trained to think like an engineer. The world appeared to him as models and equations; he was quick to systematically analyze a hypothesis and identify its strengths and weaknesses. This was a lot different, Victor realized, staring down at the anesthetized body of the dog stretched out on the table in front of him. The nature of biology and the complexity of a living body challenged his analytic, rational approach to knowledge. In fact, during his first few months in the neuroscience program at Glenhaven, he would walk out of the core course in neural structures and cell biology with a pounding headache. The last time he took biology was a decade ago, as a schoolboy in Peru. He tried to memorize the neural structure of the human brain—its cellular connectivity, the placement of synaptic connections, the significance of action potentials. Victor had always been an outstanding student, a fact he attributed to his ability to memorize and recall information. But in the neuroscience program, he found the amount of information overwhelming. His colleague in the lab was also in the neuroscience program, but had a strong biology background. He advised Victor to concentrate on the circuits as opposed to the whole picture—understanding how the brain is wired together, for example, rather than memorizing each individual component. Victor tried to remember that advice as he watched Dr. Hedley, his advisor, insert the first electrode into the brain. When Dr. Hedley asked him to assist her on
103 this experiment, he was both flattered and terrified. Although he had tried not to show it, he had worried about this day for the last few months. The past semester in her lab had been particularly challenging. When he first arrived at Glenhaven in August, he had little more than a vaguely compelling research interest. He wanted to know more about the biological basis of vision. During his master’s degree, he did research with a professor on artificial intelligence. The research initially placed him well within his comfort zone: building hardware and software computational systems. Victor grew increasingly interested in how to make robots “see” in a manner resembling that of humans. How could human vision be used to enhance artificial intelligence? Victor’s problem, as he would soon come to realize, was that he had little understanding of the biological underpinnings of human vision, much less how to apply that knowledge to computational systems. He made the decision to enroll in the Ph.D. program at Glenhaven, which was well known for its emphasis in computational neuroscience and vision research. He was confident that he had made the best decision. Here he was, seven short months later, Victor thought with amazement, observing as his advisor expertly maneuvered electrodes in the brain of the dog. He was surprised at his reaction. When he first started working in the lab, surrounded by caged research animals, he was worried that he wouldn’t be able to handle experimentation. During the first few months of the program, he learned what his classmates did in other labs across campus. Some worked with computers, never handling any animal. Others did
104 research with human subjects. A very few worked with birds or monkeys. The vast majority spent their days with rodents. A small smile crossed his face. Victor never had the opportunity to work with rats to ease the transition to Dr. Hedley’s lab. He had jumped straight from computers to canines. The longer he worked in Dr. Hedley’s lab, though, the more he developed a fervent obsession with developing the skills to become a competent neuroscientist. He wanted to do good research, and working with animals was an integral part of the process. Victor felt he simply couldn’t afford to be disgusted by the experiments. Watching his advisor manipulate a series of dye-filled electrodes into the dog’s brain, he was secretly thrilled to realize that he was both nervous and excited—but not revolted. Here was finally an opportunity to see how data was produced. Dr. Hedley had taken advantage of his computer skills, and put him to work for the last few months analyzing endless stacks of data. Victor didn’t mind, really. The work appealed to his analytic nature, and he knew it was an essential part of Dr. Hedley’s research. To be honest, he appreciated the opportunity to do familiar work. Nothing else seemed familiar. In his previous lab, the sound of computers humming had provided a comforting backdrop to which he became quickly accustomed. Working in such close proximity to animals had been a difficult adjustment. Victor was still particularly startled by the sounds of dogs barking. A loud, unexpected bark always caused him to jump in his seat.
105 He could anticipate the next steps of the experiment. Although this was the first time Dr. Hedley had included him in the process, he had observed earlier work in the lab. Victor had also worked enough with the data to be familiar with the end result. Using the dye-filled electrodes, they would make whole cell recordings of neural activity in the dog’s brain. The goal was to determine the activity of neural cells in the thalamus and cortex, and how such activity related to vision. They would also preserve slices of the dog’s brain to examine the synaptic physiology of the neural circuits. There was so much to learn—and from just one animal. This fact somehow made Victor feel better about the dog’s imminent demise. No one in the lab really talked much about using animals, or how he should feel about their death. He got the feeling that he really shouldn’t ask. Just last week, the local newspaper ran a series of articles about how a researcher had been targeted by animal rights activists. The researcher, a professor at a nearby university, used cats in his study of brain modeling. Animal rights activists had protested in front of his house for several days, and even vandalized his car. Victor belatedly realized that Dr. Hedley was quite sensitive about her work with dogs. While he had never been advised to do so directly, he had become increasingly cautious about discussing the nature of his research with outsiders. Victor almost wished Dr. Hedley had told him about the sensitivity of the issue immediately. He was surprised—having spent most of his academic career analyzing computational systems, he had never given the ethics of animal research much thought.
106 Victor didn’t have the time to dwell on questions of ethics. He was too worried about remembering all the steps involved in the experiments. Before the experiment began, he had assembled a series of micropipettes, which would be used to penetrate the cellular membrane and record the membrane currents. In vivo clamping, he had learned, was a complicated and time-consuming technique. The process could take up to 48 hours, which was one of the reasons why experiments were conducted so infrequently. The amount of data accumulated from a single experiment could be overwhelming. The lab would work with the data for months. Dr. Hedley had already planned out the next few weeks of the schedule. Victor, along with Wang, his lab colleague who was also in the neuroscience program, had been assigned the task of sorting and organizing the data. Victor liked Wang, who was also an international student. There were a lot of international students in the neuroscience program at Glenhaven. Victor was initially dismayed to realize almost half of his entering class was from China. Over time, the students seemed to drift into two groups: the American students, and everyone else. Victor wasn’t sure where he fit, but he couldn’t worry too much about that. He was too busy in his lab. Wang had been an invaluable resource for him. Wang shared Victor’s interest in computational neuroscience and artificial intelligence, although his background was in biology. Victor appreciated sharing a common bond with anyone in the program. He had been drawn to Glenhaven by its strong interdisciplinary focus. He had applied to
107 six or seven schools—some in neuroscience, others in cognitive science, one in computer engineering. Only Glenhaven offered him the opportunity to study vision, computational neuroscience, biomedical engineering, and psychology, all in the same degree program. He didn’t exactly know what job he wanted to pursue when he completed the program. Victor knew his research interests overlapped in multiple areas; he just wasn’t so sure how to go about studying those areas. He had not been surprised to find out the other students in the program felt the same way. Several of the students in his cohort had such grand research interests that they had difficulty even articulating them, much less explaining how they would put together their program. The real problem, though, was that Victor felt he had nothing in common with a great many of his classmates. Sure, they were all interested in the brain, and he generally found his peers to be a collegial and friendly group. But there were very few people with whom he could really exchange ideas. Maybe because he was from computer science and 80 percent of his classmates were from biology. Maybe because the professors in the neuroscience program did a poor job of teaching the importance of computational neuroscience and its relationship to the biological sciences. Victor wasn’t sure. In the last core class on computational systems, he got angry. He overheard several students outside of class questioning why they should be required to take the course. Victor was frustrated by their dismissive attitude and their belief that computational
108 neuroscience was only about drawing little boxes around regions of the brain and making models of them. The way he saw it, neuroscience required both computational and biological advances. In fact, just the other day, a friend from Peru had asked him to describe the work he was doing. Victor proudly told him that he was a computational neuroscientist interested in the biology of the brain. Although he still wasn’t exactly sure how the two areas worked together, he liked the description. For now, it seemed to fit. Interdisciplinarity and knowledge acquisition Neuroscience is an interdisciplinary, hybrid area of inquiry, drawing from the knowledge of multiple disciplines. The hybrid nature of neuroscience appeals to doctoral students such as Victor, who enrolled in the Glenhaven program because of its multiple foci. The challenge for such an environment is to ensure that doctoral students are given broad scientific training that allows them to understand the breadth of the field and be able to connect their research to the work of others, yet also encourages students to become fluent in one of the constituent disciplines. “The nature of neuroscience is that everything is all over the place,” Gloria, a first-year student interested in neurobiology, summarized. The breadth of neuroscience makes it difficult for students to become “experts” in the field. At Glenhaven, little consensus exists among students as to what knowledge doctoral students in neuroscience should share. As Victor found, doctoral students disagreed on the value
109 of studying the many constituent disciplines of neuroscience. Students entered the program with a diverse range of academic backgrounds. For some students, the core course in neural development was a basic review of information from previous coursework. Other students like Victor, with little if any background in the natural sciences, were challenged by the breadth of knowledge. As I outlined at the conclusion of chapter two, there are two approaches to working in an interdisciplinary area. The first approach is reflected in many of Glenhaven’s neuroscience faculty, who concurrently hold appointments in traditional disciplines. As Lenoir noted, “Disciplinary identity shapes a scholar’s vocational identity, setting problems and defining tools for addressing them” (1997, p. 47). Many of these professors obtained disciplinary doctorates, and received training as a graduate student through a traditional department. For some Glenhaven faculty, their neuroscience research is the result of emerging scientific trends, such as fMRI/brain imaging, rapid advances in molecular biology, or stem cell research. Such trends have altered the direction of scientific knowledge production. “As new [knowledge] goals develop and interests change, the core of [knowledge production] practices also shifts,” concluded Klein (1996, p. 43). Other faculty agreed to advise neuroscience students and include them in their laboratory; as a result, the professors became involved in the neuroscience program. In contrast, the neuroscience doctoral students experience interdisciplinary training as part of their doctoral program. Victor, for example, has enhanced his undergraduate and master’s training in
110 computer science and engineering with graduate coursework in biological sciences. As opposed to a gradual progression in methods of knowledge production that shape disciplinary and vocational identities over one’s career, doctoral neuroscience students at Glenhaven are encouraged to develop initial professional identities as interdisciplinary scientists. The contrast between the faculty’s disciplinary training and the students’ interdisciplinary motivations emerged as a continual conflict of expectations, roles, and student learning, particularly as related to knowledge expectations and the neuroscience curriculum. “If you walked into a room full of neuroscientists, what would you expect to be common conversation?” I asked students during our interview. “Basic things like the anatomy of the brain, and what goes on in different lobes,” one student said. Another replied, “The structure of neurons, and hot topics in the field.” Diane, a recent graduate of the program, offered this response: “General things. A little bit of anatomy, where the main pathways and parts of the brain are, how a neuron fires, and you should know the basics of system—cognition, language, hypothalamic—that the hypothalamus is responsible for homeostatic behavior, stuff like that.” But other individuals agreed with the conclusions of a second-year student, who noted, “I don’t really expect anyone to know anything, just because our research is so different. Some people are more psychology based, for example. Why do they need to know the molecular structure of the neuron?”
111 Interdisciplinarity, the curriculum, and knowledge acquisition The process of curriculum development in an interdisciplinary area such as neuroscience is “fluid, locally developed, and responsive to comparative and competitive pressures” (Hall, 2004, p. 2). The neuroscience curriculum at Glenhaven is designed to provide doctoral students a shared knowledge base. The syllabus for the class states, “Overall, the course … is intended to introduce graduate students with diverse backgrounds and interests to molecular, cellular, systems, cognitive, and computational approaches to neuroscience.” 4 The curriculum is influenced by two components: first, the structure of the program and second, the judgments of faculty within the institution. Since the neuroscience program was formally instituted at Glenhaven in the early 1990s, the curriculum has undergone numerous changes. In the last decade, the course has been redesigned with shorter modules, a greater focus on applicability, and more emphasis on the connection between knowledges contained in the curriculum. According to Glenhaven’s current course catalogue, the purpose of the course is threefold: 1) to provide a sense of current knowledge in all areas of neuroscience; 2) to understand relevant “classical papers and experiments”; and 3) to understand the future directions and needs for neuroscientific research. Exposing doctoral students to current research in all areas of neuroscience remains the primary goal, but students
4
The syllabus also provides a noteworthy disclaimer: “Bear in mind that no course can cover all aspects of neuroscience, and that independent reading and self-taught knowledge will form an increasingly important part of your repertoire as your graduate career progresses.”
112 are also encouraged to disciplinary experts in one of the constituent disciplines (such as biology, chemistry, psychology, engineering, or computer science). Most students recognize the inherent value in the course. One first-year student said, “I think you never know what will happen in your research, and you might end up needing that information, and almost everything they covered in the [core] course, I should know as a neuroscientist.” A second student added, “[The course] is a foundation, it’s just basic.” Another student noted, “I think it is necessary, at least for a brief introduction to the field and some readings of classic papers.” One first-year student concluded, “If we want to study neuroscience and all the areas of science related to the brain, then we have to take coursework related to those things.” Victor expressed little confusion over the value of the curriculum. “The course explains everything—what a cell is and what is in a cell, its electrical properties—all those things I need to know. Time and again, I wish I had more biology in my background, because it is a challenge, but I need to know.” The faculty decided upon a relatively small number of required courses (the two-semester core course and a weekly seminar) to compromise between the need for interdisciplinary breadth and disciplinary depth. Students are free to select their remaining courses from their disciplinary area of expertise. Not all neuroscience faculty agree with the limited number of course requirements for students. Dr. Quinlan, the program’s director, called the curriculum “woefully inadequate.” Dr. Barnes, a professor of engineering and computer science, added, “I teach the same
113 topic in a semester course for engineering students as I teach in the core neuroscience module. How do you adequately cover something in six weeks compared to four months?” Throughout the data collection for this dissertation, the faculty debate over curriculum was the most prominent example of the structural difficulty in designing an interdisciplinary program. Interdisciplinary researchers are continually challenged with the “burden of comprehension” (Klein, 1990), and are required to gain fluency in the multiple disciplines that make up the interdisciplinary field. As part of this burden, interdisciplinary researchers “must acquire at least a basic understanding of how something is used in its original context” (Klein, p. 88). Palmer (2001) further concluded, “The integration across disciplines requires more than borrowing specifics from another field…researchers need to understand the context, history, and status” (p. 85). For Victor, the difficulty in terms of knowledge acquisition resulted from a perceived conflict between two bodies of knowledge: the biological sciences and engineering. Victor was challenged to abandon his previous approach to knowledge acquisition when presented with unfamiliar material he was expected to master. Understanding the neural structure of the brain in its “original context” was frustrating for Victor, who had no understanding of the original context on which he could rely. The interdisciplinary burden is a particularly difficult one for doctoral students, who have traditionally been trained to high levels of competence in the foundations of a single discipline. Such students also typically enter doctoral
114 programs with previous experience in a single discipline, such as Victor’s background in engineering. This experience creates distinctive learning patterns. As Victor explained, With the example of the endocrine system class that we had, there wasn’t anything in there that was computational [related to my background]. I studied that module, and then there was a different way [that biology students] studied that module. I would try to memorize, but you can’t memorize the whole body. That is not possible. So I think there is a huge difference in the way engineers and biologists think. The structure of doctoral education has historically not allowed for intensive student learning in multiple disciplines. At Glenhaven, the core course in neuroscience is designed to give doctoral students the breadth of cross-disciplinary understanding. Through eight intensive six-week modules, the students are taught what the neuroscience faculty deem to be the most significant components of neuroscience: the development of the nervous system; electrical properties of neurons; cognition and awareness; neuronal signaling; sensorimotor systems (including the brain stem and spinal cord); modeling and computation; and the physiological basis of human behavior. One student summed up his impression regarding the core class: “I heard someone describe it before as these other things are in the water. It is not a strong exposure, but you get it…the flavor, they are there.” For many students, the core course offers the first (and perhaps only) exposure to one of the constituent disciplines of neuroscience. With his lack of biological knowledge, Victor found the work in neural structures and cellular biology particularly challenging. His previous approach to knowledge acquisition—
115 understanding and memorizing whole circuits—was inadequate to understanding the complex nature of the brain. Other students expressed similar frustrations with their personal shortcomings as compared to the course requirements. Consider the responses of three other first-year students when asked to assess the core course. In an interview with Larry, a first-year doctoral student who received his undergraduate degree in biology, I asked, “Was there any content [in the core course you were unfamiliar with]?” He responded: Most of it. In some ways, they could have had more prerequisites. We don’t have—like specifically, any kind of anatomy prerequisite, which when you are studying the body, is hard, especially in the brain, where things are kind of not as defined or concrete. That would have been nice to have sort of ‘This is what we are talking about,’ and just in my mind, I could have gone ‘That is here, versus here.’ I asked Esther, a first-year student with a master’s degree in neuroscience and an extensive biological background, what module she perceived to be the most difficult. “The computational—because it is very far removed from what I did, and what I do. And it is just not as interesting for me, and I had never had anything remotely similar and I will probably never have it again, thank God [laughter].” Gloria, a first-year student with a dual undergraduate degree in biology and psychology, admitted, “I really struggled with the module on cognitive neuroscience. The professor, Dr. Bachman, was great. He’s hilarious. But we didn’t learn cognitive neuroscience. We learned the recognition theory, which is Bachman’s specialty, and that was it.”
116 Interdisciplinarity, the role of faculty, and knowledge acquisition Faculty are charged with imparting the foundational knowledge of the discipline to doctoral students, who are subsequently expected to master such knowledge. Through their interaction with faculty, doctoral students gain “knowledge of and the ability to engage in multiple kinds of scholarly work [including] the traditional scholarship of discovery, integrating bodies of knowledge, and applying knowledge to problems” (Austin, 2002b, p. 100). Although the neuroscience faculty at Glenhaven designed the core course to cover the basic principles of a constituent discipline, students often felt that the modules gave them information that they did not need or would not use in their research. While the core course is designed to provide knowledge of the breadth of neuroscience, doctoral students in the program were generally disappointed with the outcome. Much of the students’ frustration related to how professors taught the course. In terms of the module on cognitive neuroscience, Gloria expressed a desire to learn the foundational theories of cognition as related to neuroscience. Instead, she concluded, “I became an expert in recognition theory, which Dr. Bachman has developed in his own research, and that was it.” During an interview with Dr. Bachman several weeks later, I asked him to tell me about the neuroscience courses he taught. He explained: The first module that I teach is cognitive neuroscience, but I teach it with a great emphasis on cognitive vision neuroscience, with some analogies to language, which I do actually feel there are parallels with that. And cognitive neuroscience is such a broad area, you wind up doing it really superficially and not learning much, or you can really get a feel for the paradigm, and vision is the most developed of that, the most sophisticated model. Right at
117 the outset, I said we were just going to concentrate on vision, and I explained why, it’s the most advanced, and what I know best. There are plenty of things we don’t cover. But if we do it right, the students should have some exposure, and be able to intelligently understand something. A comparison of the perspective of the student, Gloria, and the professor, Dr. Bachman, provides an explanation for the significance of knowledge acquisition, interdisciplinary knowledge, and the role of faculty in doctoral student socialization. Gloria, a self-described neurobiologist, felt the course should have provided students with a basic understanding of cognitive neuroscience, designed as a review of significant theories and concepts related to cognition and the brain. Dr. Bachman, whose research focuses on the brain’s role in vision, believed that cognitive neuroscience was much too broad an area to be taught to students in a six-week overview course. He opted to focus on the theoretical component of the field— vision—that he perceived to be the most advanced (and with which he had the greatest familiarity). Lacking Dr. Bachman’s understanding of the breadth of cognitive neuroscience, Gloria was unable to judge his assessment. Instead, she felt frustrated that she became an “expert” solely in Dr. Bachman’s recognition theory, which Gloria perceived to be a narrow component of the cognitive neuroscience field. She felt such learning had little value. Interdisciplinary researchers should “know what information to ask for and how to acquire a working knowledge of the language, concepts, information, and analytical skills pertinent to a given problem, process or phenomenon” (Klein, 1990, p. 183). Such competencies allow them to access and act upon knowledge that may
118 initially be unfamiliar. Individuals are better able to cross multiple disciplinary boundaries when they are equipped to translate knowledge and understand practices that define a particular community. Palmer concluded, “[Interdisciplinary researchers] need to learn enough about the other discipline’s cognitive map to be able to interpret a problem in that field’s terms” (2001, p. 86). One method of interpreting knowledge from other disciplines is through tacit knowledge, an embedded competency that is enhanced by informal, personal experiences and interactions. Acquiring tacit knowledge is accomplished by “learning along the way” and “picking up on new things.” Doctoral students gain tacit knowledge through observation and practice. Nonaka and Takeuchi (1995) outlined the principles of knowledge conversion, from tacit knowledge to explicit knowledge. The process of converting knowledge is dependent upon acquiring knowledge by practice and imitation of more skilled individuals, not solely through reading texts or classroom instruction. Doctoral neuroscience students such as Gloria lack the experience and expertise to know what information is valuable for their professional and academic development. From the perspective of many neuroscience students, the structure of the curriculum and the brief six-week instructional modules does not allow students to engage in this type of knowledge acquisition. Some doctoral students felt that the curriculum was a necessary obstacle, but one that provided little added value to their development as neuroscientists. Such students were often encouraged by their faculty advisors to limit their engagement in
119 course activities and instead concentrate on research. “I don’t really see the coursework as a supplement to my lab,” said a first-year student who works in a “wet lab” studying spinal cord development in birds. “It’s more just expanding our horizons, being able to understand what someone else is talking about. But it doesn’t really help with our own research, except the cell biology part.” Students generally recognized the importance of understanding the interdisciplinary foundations of their field. I asked Kacey, a second-year student, to assess the value of the core course. She responded: You don’t use all the information. But in my project [which examines how nicotine works in the brain], the reason that the question is interesting is what nicotine does to the brain, and because people become addicted to nicotine, and it causes problems in society and with health, this question is interesting because of the bigger question, and there are questions on all different levels. Because some students did not have the background knowledge or contextual understanding to process information in the core course, such individuals often resorted to rote memorization or “cramming” to meet faculty expectations and prepare for final exams. A first-year student explained, “Towards the end [of the semester], there was a complete lack of motivation. In the beginning, we would study in the library together and work hard. By the end, we went to class, but no one was studying ahead of time. We would literally do just a cram session the day before, and that is not learning. I didn’t learn anything.” Interdisciplinary science ultimately supports a problem-based approach to knowledge production that encourages flexibility and integration. Such an approach does not demand that doctoral students
120 master the multiple components of the interdisciplinary field of neuroscience. Using the framework of situated cognition, mastery of multiple fields of study is not feasible for doctoral students. Learning and knowledge cannot be separated from the social context in which it develops. From this cultural perspective, learning is not strictly the passive transfer of knowledge from one learned individual (the professor) to a novice (the doctoral student). Instead, the creation, interpretation, and transfer of knowledge occur within a social exchange. Koschmann, Kelson, Feltovich, and Barrows (1996) explored situated cognition theory, arguing that “learning is viewed as a process of entry into a community of practice” (p. 12). They further noted, “To learn to use tools as practitioners use them, a student—like an apprentice—must enter that community and its culture. Thus in a significant way, we believe, learning is a process of enculturation” (p. 13). Doctoral students engage in a unique social context that supports learning and investment in a particular aspect of neuroscience. The goal of interdisciplinary socialization is not to master the constituent disciplines, but to understand their significance. Doing so enables students to situate their research in the larger interdisciplinary context, reflected in Kacey’s recognition of “questions on all different levels.” Interaction with other students and faculty in the program reinforces the belief that the practice of neuroscience involves at minimum an awareness of the relationship between constituent disciplines. The challenge for the faculty in terms of curriculum design is the construction (and implementation) of
121 a core course that is relevant to students and focuses on the link between foundational disciplinary knowledges. Interdisciplinarity, the role of laboratory research, and knowledge acquisition The curriculum represents only one avenue through which doctoral students in the neuroscience program acquire knowledge. Students successfully progress through a doctoral program by mastering tacit, informal knowledge as well as producing valid, replicable results from research. Another avenue for doctoral student socialization is through laboratory work, structured at Glenhaven through an initial series of three rotations. For example, Victor rotated through two other laboratories before deciding on his current lab. A significant criterion for Victor in terms of lab selection was being able to work both with computational data and animal models. “Electrophysiology is my place,” he explained, “and I am getting to do both, computational and biology there.” Dr. Hedley, Victor’s advisor, includes Victor in the design and implementation of laboratory research, which encourages knowledge acquisition and practical expertise. For scientists, laboratory training fosters socialization into the “accomplishment of particular kinds of work, including the laboratory-bench experience…and producing positive results from their investigation” (Delamont & Atkinson, 2001, p. 87). Scientific research is an essential component of doctoral education for students in a wide array of science disciplines. The doctoral neuroscience students at Glenhaven commit to a laboratory at the end of their first year, and remain in the lab until their graduation. In assessing
122 the purpose of laboratory rotations for doctoral student training in the sciences, Hall observed, “The purpose of rotations is twofold: to give students experimental evidence in diverse laboratory and scientific settings; and to allow students (and advisors) to try out potential laboratories for thesis work” (2004, p. 4). Laboratory rotations are particularly valuable for an interdisciplinary field such as neuroscience. Doctoral students are given the opportunity to “try out” different research techniques, topics, and epistemologies before committing to a laboratory for the duration of their doctoral career. Jacob, a first-year student, completed all three rotations, and decided to stay in his last lab, working with Dr. Blauson, a professor from biomedical engineering. He explained: Jacob: When I first got to Glenhaven, I rotated through a vision group where we were developing models to describe a particular theory, and then I rotated through Dr. Blauson’s lab, and before I committed to joining the lab, I did another rotation, in Dr. Turner’s lab, who happened to be Dr. Blauson’s mentor when he was finishing his PhD at Cal Tech. There wasn’t a question about staying in Blauson’s lab, really. But I wanted to satisfy my curiosity and make sure I was making the right choice. And the program encourages us to maximize the usage of the rotations, so I thought I would take advantage of the fact for a couple of months, to learn more techniques, if anything. If nothing else— Karri: Did you learn more techniques? Jacob: Yeah—well, I don’t know if I mastered more techniques, but I was at least exposed to them. So now if I need to use those in the future, I know who to go to. I know basically what to do, but I could easily go to one of them and ask them to show me again. Several benefits of the lab rotations exist in terms of knowledge acquisition and doctoral student socialization. First, students are encouraged to closely work
123 with faculty in a research-intensive environment. Second, in addition to expanding technical skills and tacit knowledge, students are also exposed to the different constituent disciplines of neuroscience. Understanding how faculty in the constituent disciplines define and undertake scientific research allows students to understand how disciplinary questions are asked, how problems are framed, and how knowledge is assessed (Hall, 2004, p. 4). Third, students bring their personal experiences from one lab to another. Jacob’s undergraduate degree, for example, was in electrical engineering and computer science, and he spent the year prior to his enrollment at Glenhaven working in a cognitive motor behavior lab. As he settled into his permanent research position with Dr. Blauson, Jacob was able to draw upon the knowledge and experience he gained during his previous professional experience and laboratory rotations. One of Jacob’s primary work responsibilities involved removing and slicing the hippocampus from rodent models; during his rotations, he was able to practice this technique under the supervision of different professors and research technicians. Doctoral neuroscience students at Glenhaven have increasingly recognized the benefits of laboratory rotations. David, a neuroscience student writing his dissertation, started the program in 2001, before the development of required rotations. He did not experience working in different laboratories, which he now regrets: One of the best things about doing rotations is picking up techniques that you wouldn’t have otherwise. I’ve been in the same lab doing pretty much the same thing for the past few years. We’ve had some new people join our lab who were able to show me some new techniques, but doing rotations
124 provides you with a time period where you can focus on that sort of thing. And while it’s not essential for future success, the more techniques you pick up along the way, the more likely you’ll be able to step into any lab and be able to be productive quickly. Most doctoral students do not chose laboratory rotations outside of their area of research interest or existing expertise. For example, although Jacob has newly perfected the technique of brain slicing related to his doctoral research, much of his work involves computational modeling, an area he first worked in as an undergraduate. “It would be weird for someone to come in with a background in molecular biology or something, and end up in computational neuroscience. That just doesn’t happen, at least not often,” admitted Kacey, a second-year student. Students enter the program with a history of academic experiences and motivations for entering neuroscience. While the curriculum is designed to expose them to the multiple disciplinary principles of neuroscience, the research laboratory often builds upon existing interests. The laboratory allows students to master “at least one constituent discipline or approach from among those that contribute to neuroscience: systems neuroscience, physiology, behavioral neuroscience, computational neuroscience, genetics, or the like” (Hyman, 2004, p. 7). Interdisciplinarity, the role of professional associations, and knowledge acquisition Weidman, Twale, and Stein (2001) concluded that socialization occurs as a result of the convergence of multiple influences, including individual experiences, the university culture, personal communities, and professional communities. While coursework and laboratory experiences are essential to knowledge acquisition for
125 doctoral students in neuroscience, so is participation in meetings held by various professional associations. Many doctoral students referenced the annual conference of the Society for Neuroscience, which regularly boasts over 30,000 attendees. Several of the first-year students in the program repeated what I later learned was the philosophy of the program’s director, Dr. Quinlan. As one first-year student explained, “We are supposed to be learning different facets of neuroscience this semester, to be able to go to the Society for Neuroscience conference and go to a poster, for example, and be able to say ‘I recognize this,’ and have a vague idea of what is going on there.” Lisa, who is nearing the end of the program, regularly attends the annual meeting. She explains: Scientists go to the conference, and they sit in along a seminar or something they wouldn’t go to otherwise, and they realize that someone has already answered this question that they are looking at from a different perspective. [The conference] is just a reminder of what neuroscience is and how many things are going on. You can go to so many different things—there are the poster sessions, and the seminars, and the symposia, and you can get so many perspectives on the specific things that you are interested, and there’s always a couple of people who have written lay books about things, and they are usually pretty good speakers—even if it is something you don’t have a specific interest in, you can get a good perspective on. You can really be reminded that neuroscience is an interdisciplinary field, and there are many things going on that I wouldn’t take my time to devote to otherwise, but since I am there… Another first-year student shared Lisa’s perspective that the conference serves as a reminder of the interdisciplinary breadth of neuroscientific knowledge: And when you go to a conference like the SfN and see there are tens of thousands of posters, and you can walk up to a sizeable chunk of them and not have any idea what these people are talking about... I actually think it is kind of fascinating, because of course some things are just not interesting to
126 me or you or whoever. But if you are genuinely interested in something, for the most part when you walk up to somebody, they want to tell you about their poster, they are excited, they’ve created this science. So mostly what I do in a situation like that is have them walk me through it, tell them I don’t know anything about it, that I am very unfamiliar with this subject or this particular field of research, or whatever, and they just kind of take you through it. So it is really fascinating to get out there and see how different people, everybody is in neuroscience and everybody is doing such different things. The sheer size of the annual conference in neuroscience is daunting to many doctoral students, particularly those who perceive their area of knowledge to be removed from the primary research emphases of neuroscience. Even those doctoral students who attend the conference and present research findings can be overwhelmed. I asked Madeline, who graduated from the program in 2004, about the conference. She replied, “It is too huge for me, I can’t get anything out of it. What are you going to do, watch a slide presentation about something or another and then what? I presented there about twice. I liked it, I guess—but it is just too huge.” The size of the neuroscience conference was one deterrent. Another was the breadth of knowledge represented by the conference program. “I went to the conference once,” explained a third-year student who works in a neuroimmunology lab. “But there was so much I didn’t understand. I think it would be better for me to go to more of an immunology conference, stuff that [my advisor] usually goes to.” A first-year student added, “[My advisor’s rule] is if you are not presenting or anything like that, then there is no reason for you to go. He is probably right—I don’t know what I would learn.” A second-year student concluded, “I think there are more
127 developmental type conferences that [my advisor] goes to [that are more related to my research], and I would be willing to go to those.” In terms of knowledge acquisition and development, doctoral neuroscience students frequently identify with conferences that represent the primary constituent discipline of their research. When queried in regards to what conferences would be beneficial to attend, students acknowledged the annual meeting of the Society for Neuroscience, but almost always in addition to conferences directly related to the primary discipline or area of research. A summary of knowledge acquisition and interdisciplinary socialization Doctoral training in the disciplines ensures that scholars are able to generate new knowledge, understand the foundations of the field, and communicate ideas both within and outside disciplinary boundaries (Carnegie, 2005). But what are the “foundations of the field” in an interdisciplinary program such as neuroscience? The first-year required core course is designed to expose students to the breadth of the field, but students are not necessarily expected to master it. Mastering such a broad foundation is likely impossible, and also arguably unnecessary. At Glenhaven, doctoral students do not amass the knowledge necessary to become an expert in neuroscience. Rather, they hone their skills in a specific area of neuroscience: computation, cognition, vision, learning and memory, or behavior. Through such formal activities as the core course and laboratory rotations, and informal interaction with peers, other faculty, and members of professional associations, students gain an
128 understanding of how their area of research is situated within the multiple perspectives that can be utilized to decipher brain function. The goal of interdisciplinary science is to coordinate knowledge from highly specialized scientists working in disparate fields. Such an objective does not presume that one individual masters knowledge from multiple disciplines or integrates multiple disciplinary approaches within a single area of research. Instead of honing specialized techniques or tools, such research concentrates on a problem-based approach to science that allows flexibility in terms of knowledge production. Ultimately, interdisciplinary scientists need to be “both disciplinary and multidisciplinary, to have the breadth to see problems and the depth to solve them” (Reis, 2000). Identity development: Megan Megan couldn’t decide what was worse—the discomfort of pregnancy or working with fruit flies. Working with flies was always a challenge. Thankfully, running the fruit fly experiment was a small part of her job, although the fact offered little consolation this particular morning. Megan closed her eyes and listened to the steady February rain splatter against the window nearby, trying to gather her enthusiasm for the experiment. Finally, she took a deep breath, and maneuvered as close to the microscope and the anesthetized fruit flies as her burgeoning belly would allow.
129 Megan appreciated the benefits of using the Drosophila model. Although she was initially uncertain that such a simple organism could be used as a framework for complex human diseases, she had quickly learned that the development and function of the nervous system in fruit flies provided a strong foundation for studying neurodegenerative disorders. Such appreciation did not endear her to working with the animals. Megan much preferred the biochemical aspect of her research: immunochemical analyses as well as radio and enzyme immunoassays. She valued the quick turnaround of information. Working with animals was more frustrating. Between data collection, brain slicing, histology, and cell counting, the length of time from the start of the study and getting the answer could be considerable, and so much could go wrong in between. With biochemistry, she would complete an experiment one day, input her data the next day, and have her initial results immediately. Megan reluctantly acknowledged that the older she got, the less patient she became with the somewhat tedious histological research techniques. In some ways, the fact that Megan found biochemistry so appealing was ironic. When she completed her degree two years ago, she defined herself as a neuroscientist with an expertise in histology and anatomy. During her enrollment in the neuroscience Ph.D. program, she worked in a small lab that focused on the histology and anatomy of the brain related to aging. She would remove part of the cortex that provided connections to the hippocampus, and examine what neural molecular responses occurred as part of the recovery. Dr. Miller, her doctoral
130 advisor, enjoyed the small size of the lab, but Megan found the lack of equipment and resources frustrating. The lab was tucked away in a rarely-used corridor of an aging building on the medical school campus. Megan would spend hours there, with Dr. Miller and another graduate student her only human companions. At times she felt immensely isolated, both physically and intellectually. With limited resources, she could only dabble in questions that arose related to biochemistry. She lacked the background to pursue the questions further, and Dr. Miller, who was trained as a neural anatomist, could provide little feedback. Megan wanted to branch out into other areas of science, in large part because she felt that working in different areas was increasingly necessary. Her post-doc position had been invaluable in allowing her to develop her interest in biochemistry. The lab was full of people with a biochemistry background, yet no one else in the lab shared her advanced knowledge of the brain. Dr. Sijinder hired Megan because she was a neuroscientist, and he was initially interested in expanding the neural aspects of his research. Now two years into the position, the irony was that Megan did little if any research explicitly related to neuroscience. In fact, she increasingly thought of herself as a biochemist. The brain was at best only marginally related to her current work. She hadn’t encountered any overt bias to studying the brain in Dr. Sijinder’s lab. Certainly, biochemistry was an integral aspect of neuroscience, as evident through such specialties as molecular pharmacology and developmental neurobiology. It was just that other organs in the body, such as the liver and kidney,
131 provided stronger and more reliable responses to the research questions on which this lab focused. With Dr. Sijinder’s training, background, and focus in biochemistry, however, Megan felt more and more removed from neuroscience. She shifted slightly on the uncomfortable stool, trying to relieve the growing pressure in her lower back and the aches in her feet. Megan appreciated the early hour, as she was the only one working in the lab. There were simply never enough hours in the day. Her work with the fruit flies was only a small part of her daily tasks. There was the data collection, management, and analysis from the rodent population, which took most of her time. She was co-authoring two papers with Dr. Sijinder and Anthony, another post-doc, based on their most recent data. In addition, Megan was still hopeful that she could manage at least one publication from her dissertation. Although it had only been two years since she completed her doctorate degree in neuroscience, Megan felt less like a neuroscientist and more like a biochemist. Perhaps that was why she kept putting off the revisions to her manuscript. She wanted to have a publication, which would serve in some way to validate the significance of the time she had invested in her doctoral program. Perhaps the publication of her dissertation findings would make her feel like a neuroscientist again. Whenever she would return to her data or edit the manuscript, however, Megan felt like she was reviewing someone else’s writing. The elapsed time was a significant factor, although the fact that her post-doc experience was
132 leading her further away from neuroscience was another. Her collaborative paper with Dr. Sijinder and Anthony was a persistent reminder of the distance. She was targeting her dissertation research towards classic neuroscience journals, such as Comparative Neurology or J Neuroscience. Megan was still learning the names of all the journals in biochemistry and their rankings. She hoped the research from Dr. Sijinder’s lab would be accepted by Journal of Biological Chemistry or Free Radical. Megan constantly struggled to adopt the appropriately distinct focus for each journal. The struggle reminded her of the two parts of her identity which were sometimes difficult to reconcile. Megan laughed softly as she recalled a conversation with Anthony several weeks earlier. They had been discussing data from a transgenic fruit fly with a decreased enzyme and how best to present the data in their paper. The paper’s emphasis was on the role of glutamate in enzymatic regulation. “Is there more glutamate in the brain than the rest of the body?” Anthony had off-handedly asked as he sorted through the stack of papers on his desk. Megan looked at him for a long moment before answering. She was initially unsure, and then could only laugh aloud. Of course glutamate existed throughout the human body. It was a standard amino acid used by every organism in its cellular function. Such a fact would be regularly taught to all new biology and chemistry students. With her neuroscience training, however, Megan’s first reaction to glutamate was that it was the most common
133 neurotransmitter in the brain. Why would it need to exist elsewhere in the body? While she initially laughed at her response, Megan was also troubled. There were constant reminders in the laboratory regarding her relatively unique background. Not only was Megan the only individual with a Ph.D. in neuroscience, she also completed her undergraduate studies in psychology. Compared to the extensive biochemical and biological training of her colleagues, Megan realized that she approached scientific methods somewhat differently. The difference was elusive and sometimes hard for her to define. Dr. Sijinder had a distinct approach to thinking about statistics, for example. Others in the lab were so focused on a particular molecule that they cared little about how it interacted with the rest of the body. Occasionally, Megan had trouble following conversations regarding chemical reactions and molecules. Even though Dr. Sijinder hired Megan because of her expertise in neuroscience, he frequently chastised her to think of concepts in terms of biochemistry. As Megan neared the end of her post-doc contract with Dr. Sijinder, she thought about these issues a good deal. She wondered what direction she should take next—she didn’t feel ready to apply for a faculty position, and was reluctant to commit to another post-doc. The baby’s arrival would only further complicate her decision. Maybe she should stay home with the baby for awhile. Sometimes she questioned whether she would study for a Ph.D. in neuroscience, if she had the process to do over again. In the end, for numerous reasons, Megan always decided
134 that she would. She loved science. The techniques she perfected working for Dr. Miller as a doctoral student were invaluable, and she enjoyed working with him. But when Megan did in situ hybridization work in Dr. Miller’s lab, she had to go to an outside professor for advice. Dr. Miller had never worked with histological techniques before nor was he familiar with the biochemical technique of a Western blot. Such areas were simply outside his strength in neural anatomy. Megan had encountered a similar situation with Dr. Sijinder. He was an outstanding biochemist, but much better suited for theory as opposed to practice and application. Her lab colleagues were a valuable resource. She also anticipated leaving her post-doc position with several publications, which made the experience worthwhile. Megan ultimately felt she had enhanced her general knowledge regarding disease and aging. Those topics remained her primary areas of interest, and her work with Dr. Sijinder provided an alternative means of studying them. Even while she frequently struggled with terminology, Megan took comfort in the belief that by combining training in neuroscience and biochemistry, she was building a strong future foundation for running her own research laboratory. She was determined to be an expert in multiple areas. The more she learned about the larger cultural and social context of science, the more Megan felt that such an approach was necessary. Grants didn’t go to a single researcher whose expertise was only in a limited field. Being an expert in one area simply wasn’t good enough.
135 Interdisciplinarity and identity development The development of a professional identity requires “the formation of an attitude of personal responsibility regarding one’s role in the profession, a commitment to behave ethically and morally, and the development of feelings of pride for the profession” (Bruss & Kopala, 1993, p. 686). Identity development is a significant component of doctoral education as students make a transition from a novice member of the community to emerging professional. In doctoral programs, student identity is influenced by intellectual competence. One means of demonstrating community membership is through the acquisition and application of knowledge. Baxter Magolda (1992) argued that knowledge is intimately related to the development of personal epistemologies and identity construction. As outlined in Victor’s story, the process of community membership involves participation in laboratory research, classroom learning, formal and informal interactions with faculty and peers, and professional associations. The acquisition of formal knowledge (as represented by the curriculum, for example) and tacit knowledge (gained through practice and observation) is influenced by individual processes of interpretation. Doctoral students come to understand the knowledge required of community members through interaction with faculty and peers. As an element of socialization, knowledge acquisition shapes the evolving professional identity of the doctoral student.
136 The discipline plays a significant role in shaping the doctoral student’s professional identity. Becher and Trowler (2001, p. 47, 48) concluded: “Being a member of a disciplinary community involves a sense of identity…novices are initiated into folkloric discourses and codes of practice and conventions that condition the way they see the world and interact with it.” Three components are particularly relevant to this dissertation: first, the community (i.e., the interdisciplinary neuroscience program and for some doctoral students, other constituent disciplines) as the source of one’s professional identity; second, the doctoral program as a timespan of intense socialization into one’s disciplinary community; and third, the perception of disciplinary boundaries. Massey (1999) illustrated the significance of boundaries in terms of identity formation. She noted, “Defining a discipline defines what lies beyond it.” Disciplinary identity can be understood “through counterposition, through the process of differentiating itself from what it is not” (p. 6). Doctoral students graduate from a program in biology, for example, differentiating themselves from students in the social sciences or humanities and even from colleagues in other natural science disciplines more related to biology. For the doctoral students in this study, the broad nature of the interdisciplinary neuroscience program fostered multiple professional identities. To some degree, such a disparity can be expected even within the traditional disciplines—opinions regarding what it means to be a biologist, chemist, or physicist vary according to individual experiences. I return to Lattuca’s argument:
137 “We reify the disciplines even as we acknowledge the depths of divisions within them” (2001, p. 71). In neuroscience, however, doctoral students often developed multiple professional reference groups. Students identified with their interdisciplinary neuroscience affiliation, frequently in addition to primary discipline where their work was concentrated. Jonathan, for example, began his doctoral program in linguistics, but found the curriculum did not support his interest in neuroscience. Even after he transferred into the neuroscience program, he retained his interest in linguistics, and was continually challenged to integrate the two. James, a first-year student, completed a bachelor’s degree in computer science; he enrolled in the neuroscience program at Glenhaven with an interest in artificial intelligence. “I spend most of my day reading papers and working on the computer, designing models,” he said. “What I am really learning in this program is how to think about questions related to the brain, and synthesizing large amounts of experimental data through computer modeling.” Although James identifies strongly with computer science, based both on his past professional experience and research interests, neuroscience is better structured to encourage his current focus on artificial intelligence. A second-year international student said, “I am a neuroscientist, among all the science fields. But within neuroscience, I am an electro-physiologist, so I think a lot like some physiologists.” Students utilize the multiple associations to explain their work to outsiders. One student, who is completing his dissertation, noted, “I tell people I am in neuroscience, and I must say it oddly because people
138 give me strange looks. I explain that my work is similar to psychology, understanding human behavior and biological reasons for it.” Often students make unconscious associations. Diane, a recent graduate of the program, said, “I don’t really think about those things. I just say I’m a scientist who does research.” Interdisciplinarity, laboratory work, and identity development While the interdisciplinary nature of the neuroscience program allows for the construction of multiple identities, the requirement that doctoral students rotate through various laboratories before selecting their advisor has a particularly strong influence for some students. The course catalogue states, “Three laboratories provide students with an opportunity for rotation. Therefore, they can learn different styles of research before choosing the subject of their dissertation work.” Along with the core courses, elective disciplinary classes, and seminar requirements, the rotations are an integral part of the curriculum for doctoral students. Not all students were enthusiastic about the requirement. Some made the decision to enroll at Glenhaven based on the work of a single professor; such students generally had a well-defined research interest and applicable skill set. They were reluctant to spend months working with other professors. Faculty could be influential in a student’s decisionmaking regarding rotations. “I don’t like rotations,” confided one professor. “My strategy is to make my students famous as fast as possible. And you do that by getting out good research and going to scientific meetings and publishing... so, if you are going from lab to lab, and spending three months or so in different places, you’re
139 not accomplishing anything.” When she first enrolled in the neuroscience program, Megan completed one rotation with Dr. Miller, and then chose to stay in his lab. She explained, “Dr. Miller actually contacted me—right after I interviewed, or maybe it was during the summer when I was accepted, and he pursued me as a potential graduate student and told me he would like to have me start off the rotation in his lab. So that sounded fine.” Most doctoral students approached the rotations as the opportunity to meet faculty from multiple disciplines, engage in different types of research, and be exposed to new research methods. Doctoral students did not commonly choose a research laboratory that was far removed from their previous academic experiences. That is, a student interested in molecular biology would not seek a rotation with a cognitive physiologist, nor would a computational scientist work with students focused on psychobiology. Although the interdisciplinary program is designed to expose students to the breadth of neuroscience, doctoral students concentrated their research interests and practice in a specific area. It is important to note that doctoral students generally enrolled in the neuroscience program with an interest in a single area and level of analysis in neuroscience. Glenhaven’s application materials for the neuroscience program note that “applicants should normally have defined an interest in one or two specializations.” Doctoral students did not choose their rotations in laboratories at opposite ends of the neuroscience continuum—the reductionist approach of biophysics and neurochemistry that focuses on the structure, function,
140 and interaction of ion channels and synapses, for example, as compared to cognitive neuroscience, which examines more holistically the biological underpinning of mental processes. The selection of rotation opportunities and the determination of one’s dissertation advisor were significant milestones for students in terms of professional identity development for three reasons. First, the focus of a student’s research laboratory determined the student’s skill development, theoretical perspectives, and dissertation topic (COSEPUP, 1995; Delamont & Atkinson, 2001; Zhao, Golde, & McCormick, 2005). While existing literature addresses the significance of focused interaction, timely and purposeful feedback, and engagement in creating a positive relationship between doctoral students and advisor (e.g., Austin, 2002a), less attention has been given to how the doctoral advisor shapes a student’s intellectual perspectives and future research agenda. For example, Lauren entered the program in 2001 with a background in psychology and rodent models, but her interest was more directed towards the biological basis of human behavior and disease. After starting the program, she attended a seminar presented by a professor who studied Alzheimer’s disease. An important connection was made: Dr. Peters agreed to supervise Lauren’s doctoral work, and she graduated from the program in 2005 with an award-winning dissertation that focused on the influence of steroid hormones on aging, and accepted a postdoctoral position working in stem cell research. “[Dr.
141 Peters] has been very supportive of me,” Lauren said. “All in all, it was a good experience. I learned a lot.” In addition, working closely with a faculty advisor offered doctoral students a role model in the field of neuroscience. How the advisor approached collaboration and integrative research across the field was particularly relevant. Megan, the recent graduate, recounted, “My advisor worked a lot with computational neuroscientists. I always knew they were around.” Other students spoke of the relationships between their laboratories and other adjacent research facilities. “We always share things, so in some ways, we really are the same lab,” said a first-year student. The selection of a research laboratory also determined a student’s primary community for the duration of their doctoral program. After completing the required coursework, doctoral neuroscience students at Glenhaven spent most of their workdays in the research laboratory. Consider the responses students gave when asked about their daily schedules. “I’m in my lab from nine to five, some days longer, and sometimes on the weekend,” a second-year student said. A first-year student added, “I’m usually here from ten or so each morning to nine at night.” Another first-year student in the same lab, which worked with the very controlled development of embryos, said, “We [my lab colleagues] are often here on Sundays.” While the nature of the interaction between students in laboratories ultimately depended on the research topic and techniques, students reported spending the bulk
142 of their time in the laboratory. Space and location as mediating influences for student socialization are highly relevant. In some labs, all of the students were enrolled in the neuroscience program. The program context was quite different for other students, who were often the only neuroscientist in a laboratory. One first-year student chose a position with a biology professor; the other two students in the lab were from the biology program and the dental school. A second-year student worked with three students from the doctoral program in psychology. Her colleagues often invited her to seminars and events in the psychology department in which she had little interest. Another student had difficulty explaining the relatively small number of required courses in neuroscience to the other students in her lab, all of whom were in the biology program. “Who do you interact with most on a daily basis?” I asked Amanda, who works in a psychology laboratory. She responded, “My professor, and the other person that is in the lab everyday, a psych student, we are really good friends. And I don’t really see the other neuroscience students on a regular basis.” More significantly, perhaps, was the differences neuroscience students perceived when asked to define their identity compared to their disciplinary peers. As one first-year student responded, “We pretty much do the same work, completely overlapping. If you walked into the lab, you couldn’t tell that one individual was in pharmacology and another was in neuroscience.” This similarity was confirmed by several faculty. One professor explained, “We have three [doctoral students] right now. One is from
143 neuroscience…and two are from psychology. But they are indistinguishable.” I asked, “That doesn’t change how you interact with them?” Shaking his head, he replied, “No, it’s the same problem, the same range, and they have the same training. It’s really indistinguishable.” Dr. Miller, a psychology professor, agreed. “[My neuroscience students] are more on the cognitive, psychological side of neuroscience, and my psychology students are more on the cognitive, neuroscience side of psychology.” Valimaa (1998) outlined practical questions to consider when conceptualizing academic identity. “Who and where are the significant others? What are the culturally determined groups of reference that demand academics to ask who am I? And, where do I belong?” (p. 131) Within the university, the disciplines have a significant influence in answering these questions. As I outlined in chapter two, context—space, location, and time—are particularly relevant. For Glenhaven doctoral students in the interdisciplinary neuroscience program, the responses to these questions were complicated by multiple and sometimes conflicting reference groups. The laboratory environment of doctoral students, their advisor, and their peer colleagues (other neuroscience students enrolled in the program, but more often their laboratory peers) were strongly salient for identity development. In particular, a student’s significant others affected how the individual defined such concepts as interdisciplinarity and neuroscience and perhaps more importantly how they approached emergent professional identity.
144 Interdisciplinarity, the disciplines, and identity development Identity development for faculty is most commonly related to the discipline (Carnegie, 1989; Clark, 1983; Weiland, 1995). Such identities are often taken for granted, and are assumed to result from a seemingly permanent relationship to disciplinary knowledge traditions, epistemologies, and methodologies. In the sciences, for example, “students inherit and take on trust of a good deal of knowledge and research problems that derive from previous generations” (Delamont, Parry, & Atkinson, 1999, p. 55). Disciplinary identity originates from academic work within a particular community, whose members serve as a disciplinary reference group. The origins of disciplinary identification can be traced to doctoral education, where “the primary reference groups from doctoral students are the more local student and faculty communities that reside in the schools, programs, and departments that house the specific fields of study in which the doctoral degree is pursued” (Tinto, 1993, pp. 231-232). In the interdisciplinary neuroscience program at Glenhaven, the primary reference groups are multiple and overlapping disciplines, depending on the student’s research interests and area of specialization. The broad interdisciplinary nature of the program complicates the definition, relevance, and permanence of reference groups. During her doctoral studies, Megan worked with Dr. Miller, who was trained as a neuroanatomist. The work she completed in his laboratory “placed” Megan within this area of research. She then accepted a postdoctoral position, which is common among graduates of neuroscience
145 programs5. Due to the breadth of neuroscience as an interdisciplinary field of study, it is not uncommon for graduates such as Megan to pursue a postdoctoral position in an area of study outside that of their dissertation. Megan specifically sought a position in a biochemistry laboratory. “That was kind of my goal, too, after I finished my Ph.D.,” she said. “I wanted to do two post-docs: one that was more biochemistry, and one that was more molecular biology, so I would have the anatomy, histology, the molecular biology, and biochemistry, and be able to work it all together.” She continued, “I think it will give me a general knowledge, a good, strong background knowledge in all of those—for me, my interest in disease and aging, that would be a really good foundation for me for my own lab, so I have those knowledge bases to build on.” For Megan, her interest in aging and disease is not solely defined by neuroscience. She utilized her postdoctoral position to strengthen areas of training not available to her as a doctoral student, areas that she perceived relevant to her future professional career. Victor, the international student, also struggled to define his identity as a neuroscientist. Much of Victor’s frustration was related to interaction with his peers within the core curriculum. Some doctoral students completed the three required courses in the neuroscience curriculum, and then had little if any interaction with neuroscience peers during the remainder of their program. They worked in research
5
Seventy-one percent of graduates from doctoral neuroscience programs pursued additional research training through a postdoctoral position in 2003 (ADNP, 2003). Other graduates enrolled in medical school (16%), assumed a faculty position (3%), or worked outside of academe in an industry position (10%).
146 laboratories in other departments or campuses. “It is really isolating to be away from the neuroscientists,” confided one first-year student located on the medical school campus. She was one of only two neuroscience students in a lab staffed by doctoral students from the departments of cellular and molecular biology. Other students worked in the neuroscience building on the main campus, and maintained strong connections with peers from the program. One second-year student who worked on the main campus admitted, “I have lunch with people from my cohort nearly every day.” For these students, assuming the identity of a neuroscientist was less complicated by matters of space, location, and context. The interdisciplinary breadth of neuroscience ensures that the field shares boundaries with numerous disciplines. Megan received some exposure to biochemistry during her doctoral experience, although she felt that Dr. Miller lacked the expertise to sufficiently develop her interests. Neuroscience students at Glenhaven commonly worked on the boundaries of psychology, biology, engineering, and gerontology, among other areas. They were frequently the only neuroscience student in a lab of doctoral student colleagues from other disciplines. For example, Amanda, a first-year student, received two bachelor’s degrees in linguistics and psychology. She enrolled in the neuroscience program with a strong interest in cognitive science—how the brain processes information, and what effect that has on human behavior. Her faculty advisor has a dual appointment in psychology and neuroscience; the lab studies the visual and sound deficits in the
147 brain related to reading disorders, such as dyslexia. The other two students in the lab are doctoral candidates in psychology. Amanda explained the similarities and differences between their work: The other students do the same things I do in terms of research. The only difference is they have to take more requirements, things like statistics. So the only difference is the classes, and the seminars that neuroscience students are required to go to. I do learn a bit in each seminar, and am constantly adding those bits to my general idea of neuroscience and the brain. But I mean psychology students could come to those seminars if they wanted to. The only difference between a neuroscience and a psych degree is oh, I have had a class on that certain property of neurons. It really is just a prestige thing, kind of. The research experience gained in laboratories serves as a supplement to the required curriculum. Amanda’s coursework increasingly placed her in the psychology department. Even her research interests—cognitive science and developmental psychology—are situated in the overlap between psychology and neuroscience. For example, Amanda’s research centers on utilizing fMRI imaging to document brain behavior as related to reading. FMRI technology (or functional magnetic resonance imaging) provides high resolution, non-invasive reports of neural activity. Glenhaven recently added an elaborate fMRI imaging complex, which allows researchers to gain a “real time” view inside an active brain. Amanda, along with her advisor and her lab peers (from psychology), has received extensive training related to fMRI data collection. Although fMRI focuses on brain activity, the technology has been embraced by multiple disciplines and is not unique to neuroscience. The technology is increasingly applied in almost all of the constituent
148 disciplines of neuroscience (Beauchamp, 2002). Amanda, a doctoral neuroscience student, has received the same training as faculty and students from psychology, biology, physiology, and biophysics; that is, her training is not unique to her enrollment in a neuroscience program. Dr. Matthews, Amanda’s advisor and a self-defined developmental psychologist, has gradually embraced the neuroscience aspects of his research over the past decade, although he shares Amanda’s sense of a blurred identity. He attributes his work in neuroscience largely to the growth of fMRI technology, which has rapidly altered the direction of cognitive research regarding dyslexia. “I certainly have a connection to neuroscience, but I don’t know that I’ll ever feel like a neuroscientist,” he concluded. “I don’t have a biological background or any biological interest in studying the brain. If a neuroscience student came to me and wanted to study the molecular basis of reading disorders, I wouldn’t be able to do it.” Dr. Matthews works with three doctoral students, including Amanda. “Really, in terms of the research they do, you couldn’t draw the line between neuroscience and psychology. Even in terms of publishing in journals, which are not neuroscience and not psychology, but somewhere in between—and really belonging to neither.” He offered the following assessment in terms of her development as a neuroscientist: Amanda is more on the cognitive side of neuroscience, related to issues of developmental psychology. The other students I work with [from psychology] work more on neuroscience issues related to psychology, in terms of cognition. They really have the same focus, so I’m not sure that the specific program they are enrolled in really matters.
149 Identity development for doctoral students—in terms of the discipline, the academic profession, and the professional community—is an integral element of socialization. As Reinharz (1979, p. 374) concluded, one component of socialization is “the active creation of a new identity.” Because neuroscience is such a broad field of study, and because individuals experience unique training, doctoral students developed often disparate identities. During my interviews with students, I asked them to describe themselves professionally. “The work I do is immunology, so I would put myself there,” was the response of one student. “I’m a neuroendocrinologist, especially in the research I did for my dissertation,” a recent graduate concluded. A third student said, “I’m a computational neuroscientist, sure, but one focused on biology.” A second-year student confided, “I’m a jack of all trades. I would never just pick one area. I dabble in everything.” Most students, particularly those nearing the end of the program, identified with the interdisciplinary field of neuroscience as well as their respective constituent discipline. How doctoral students defined such disciplinary identities was the result of unique personal experiences. Some doctoral students at Glenhaven struggled to define their interdisciplinary identities in an institutional culture shaped by the disciplines. Neuroscience, as an exciting, novel, and relatively new field of inquiry, seemed to possess a certain degree of prestige for some students. “Neuroscience is a very popular field right now, and everyone is excited about it,” a first-year student said.
150 “It really stems from being able to cure Alzheimer’s disease and have retinal implants and so on, all of those things in sci-fi movies.” Another first-year student commented, “I feel that neuroscience is really all science. All the science of the brain, and the programs are really cutting edge, so you have new and interesting things going on there.” When Amanda compared her neuroscience curriculum to that of psychology, she concluded that neuroscience had a “prestige” that traditional disciplines lacked. Other doctoral students were confused and frustrated by studying in an interdisciplinary program such as neuroscience. As one international student noted, “I think that you are in many disciplines, and you understand about nothing, you are not good at engineering or biology or whatever, so what are you good at? I always struggle with that.” A recent graduate explained, “It’s hard to find a place to fit in.” For such students, the interdisciplinary breadth of the program was a disadvantage. Graduates of the neuroscience program commonly apply for faculty positions in such disciplinary fields as biology, chemistry, engineering, or computer science. Why should they be hired, they asked, instead of an individual with a Ph.D. in one of those disciplines? Megan, the recent graduate who is completing a postdoctoral position in biochemistry, was hired for her expertise in neuroscience, but found that the research was more strongly related to biochemistry than neural functioning. She felt increasingly pressured to abandon her orientation to neuroscience.
151 Jason, a fifth-year neuroscience student, was particularly bothered by the (perceived) lack of marketability of an interdisciplinary degree. “I’m a computer scientist, I know nothing about biology,” he said. “But I am in this neuroscience program…” Unlike Amanda, who perceived neuroscience as possessing a prestige that other sciences lacked, Jason felt his future career would be strengthened by a disciplinary doctorate. Even though Jason had completed the single required core course in neurobiology, his research experience consisted of computational modeling of the brain. Because he lacked a biological expertise in terms of the brain, he was unsure of his identity as a neuroscientist. Dr. Matthews, the developmental psychology professor, also hesitated to define himself as a neuroscientist because of his lack of interest in biology. Neuroscience draws upon the knowledge and expertise from a range of disciplines, including an increasing number of areas outside the life sciences. The implication for identity development is that, although neuroscience is an interdisciplinary field of study drawing upon different types of science, a biological basis for understanding the brain was perceived by some students to be relevant. “A guy who works in a [neural computational lab], you ask them if they know neuroscience—they don’t know neuroscience,” Jason concluded, shaking his head in frustration. Interdisciplinarity, the curriculum, and identity development “The curriculum…sets the tone for how students are socialized into the profession,” concluded Weidman, Twale, and Stein (2001, p. 72). In addition to the
152 role curriculum plays in formal knowledge acquisition, which I discussed in the previous section, required coursework in graduate education also provides a framework for understanding disciplinary identities. How students identify with the discipline is shaped in part by the curricular framework. The limited curriculum did not provide doctoral neuroscience students with a cohesive, shared emergent professional identity. By minimizing the number of required courses for doctoral students, the interdisciplinary neuroscience faculty allowed students to make individual choices in terms of their coursework. The goal is for students to take the bulk of their coursework in their respective constituent discipline of neuroscience. As the course catalogue noted, “Students in our program…are able to pursue study in a wide range of neuroscience areas. Their specific program of study is tailored to their individual interests.” For example, the bulk of Megan’s coursework concentrated on neurobiology. Victor anticipates taking most of his outside coursework in computational physics and biomedical engineering. Such coursework will supplement his laboratory training and Victor’s interest in computational neuroscience and human vision. The neuroscience program encourages doctoral students to develop “a deep understanding” of a selected topic, yet such topics are frequently shared by doctoral students in other departments. “I want to see myself in neuroscience,” another firstyear student admitted. “But the reality is that I am in the computer science department doing neuroscience.” In terms of identity development, the minimum
153 number of neuroscience courses accomplishes little in terms of fostering the student’s sense of self as a neuroscientist. As Amanda noted, there are very distinctions in terms of curriculum between doctoral students in neuroscience and those in the respective constituent discipline. She concluded, “I have very little interaction with people from neuroscience. I could easily be in psychology and be doing the same work.” It is useful to examine interdisciplinary identity development in terms of a continuum of identities. There are those identities that exist on opposite ends of the continuum: a molecular neuroscientist examining the structure of intercellular receptors (a more reductionist approach to understanding the brain) as opposed to a neuropsychologist, who studies memory of human adults in a controlled setting (a much more holistic perspective). No single identity as a “neuroscientist” exists. But the continuum exists under the shared interest in the brain. Rather than being driven by a shared methodology or common epistemology, interdisciplinarity is structured by a shared topic of interest—in the case of neuroscience, neural structure and brain function. Such topics of interest can be manifested in multiple and diverse ways. For Amanda, her interest in the cognitive basis of linguistic knowledge and application overlaps with an emergent area of psychology. Amanda is enrolled in an interdisciplinary Ph.D. program, but her professional identity could easily place her within the discipline of psychology. The identity conflict she expresses is reflected in the attitude of her advisor, who also feels suspended in the overlapping areas of
154 psychology and neuroscience. When students were asked to define themselves as part of this study, a common response placed individuals both in neuroscience and a respective constituent discipline. This multidisciplinary identity is not always defined equally, as Megan discovered during her postdoctoral experience. Victor continually struggled with the balance between neuroscience and his previous training in computer science. He stated, “[Enrolling in the neuroscience Ph.D. program], I’ve had to start at the bottom again and try to build everything back up.” A summary of identity development and interdisciplinary socialization The development of multidisciplinary identities—as neuroscientists and members of a constituent discipline—can be beneficial in terms of socialization. Doctoral students are equipped to understand and identify research across disciplinary boundaries. In terms of emergent disciplinary identities and doctoral students, Austin (2002a) concluded: Developing an identity as a member of a discipline or field requires doctoral students to become familiar with the roots of the discipline, its history, the paradigms and central questions that have framed the discipline and its boundaries, and the methods and discourses used in the discipline. The doctoral experience historically has been associated with the development of expertise in one’s discipline. Yet scholars must also be able to connect with others outside the discipline and sometimes outside the traditional scholarly discourse community. Learning how to be both specialized and connected with others is an important ability that doctoral students develop as disciplinary members. (p. 10) Neuroscience students neither identified solely with a single discipline nor were completely removed from the disciplines. Close proximity to students and faculty from constituent disciplines encouraged neuroscience students to approach
155 the study of the brain from disciplinary perspectives. However, a socio-cultural conflict emerged as students simultaneously defined their identity from both a disciplinary and interdisciplinary foundation. As Megan found during her postdoctoral experience with biochemistry, “Nothing I do is really neuroscience, at least not anymore. I hope to get back to that part someday, hopefully soon.” In chapter five, I will offer an alternative interpretation of the often multiple reference groups identified by doctoral students in this study. Defining one’s professional identity by two or more groups focuses on the concept of boundaries, and how one might negotiate those boundaries as a part of identity development. Such boundaries might be blurred (or even non-existent) to the degree that the doctoral student does not feel as if she is negotiating multiple, different social worlds. From this perspective, defining one’s professional identity is more significant than defining and negotiating boundaries. Disciplinary/community integration: Jonathan Jonathan leaned back in his chair with a frustrated sigh, nudging his glasses up on his nose to rub his eyes. He opened them slightly to peek at the clock on the bottom of the computer screen. Even though he had a vague sense of the late hour, he was somewhat startled to see the numbers shift to 8:20. The day had been long, and he had promised his wife, Susannah, that he would try not to be late again this week. It was too easy to become engrossed in the data and forget his promises, particularly down in the basement. Jonathan’s door was always partly closed, and he
156 never heard the other students leaving for the day. He also never noticed the slow setting of the late afternoon sun. Jonathan was surprised at how quickly he had become accustomed to working in the windowless basement of the neuroscience building. The first time he visited the campus, he was unimpressed by the harsh fluorescent lights that lined the basement hallways. Now, when he stepped off the elevator and walked down the long corridor to his small office, he hardly noticed the lights. He needed to get home. Jonathan thought briefly of calling his wife to tell her he was packing up, but decided against it. He would save that conversation for when he finally arrived. She would understand, as always, but he couldn’t help feeling guilty. His wife was still working toward her undergraduate degree, and he had at least another two years in his doctoral program—their lives were far too enveloped by academics. Jonathan glanced past the mess of books, food wrappers, and campus newspapers scattered across his desk to the hallway. He was surprised to see the crack of light beneath his advisor’s door. Dr. Abelson worked in a unique niche of neuroscience, one that drew from the disciplines of linguistics, psychology, and biology. While she was a highly motivated and engaged scientist, she would almost always leave the building at five o’clock. During his first few months of working in her lab, Dr. Abelson’s insistence on a regular, ordered schedule nearly drove him crazy. He had gradually become accustomed to her organized personality. She would briefly stop by his office, chide him for working late, and then hurry toward the
157 elevator with a steady staccato of her heels. In the mornings, she would walk the path in reverse, breezing off the elevator in a waft of perfume and papers. Jonathan found that he unconsciously organized his own day around Dr. Abelson’s hours. Her other student, Claudia, did the same. Jonathan rarely saw Claudia, whose office was on the other side of the hallway. Part of the reason why Jonathan rarely saw his officemate was that he had spent the past few months endlessly driving to the homes of individuals stricken with Alzheimer’s disease, testing the responses of the usually feeble and elderly patients to a variety of speech perception exercises. The laboratory examined the linguistic and cognitive impairments related to aging. Jonathan found the semantic deficits of such patients to be particularly interesting—how the disease affected different parts of the brain. Trying to describe his research to his wife was complicated. To the outside observer, he imagined that the work was boring: the research subjects sat in front of a computer, naming various photographs which were flashed on the screen. The participants also arranged words on a sorting board. Sometimes, Jonathan felt like he was a game show host. But here in his small office, he felt like a scientist, sorting and analyzing the wealth of data accumulated from the research. Sure, the hours could be long, and there was always some exhausting issue with which he had to contend. Most days, he felt fortunate to be working with in this lab. He had been enrolled in the doctoral program at linguistics just across campus two years ago, growing increasingly bored and frustrated. The program was intensely
158 focused on theoretical linguistics, which left Jonathan little time to explore his interests in psycholinguistics. There were no opportunities to conduct research and he shared little in common with his peers. As he often recounted to Susannah during those days, he was miserable. Things were better now, although he still didn’t really consider himself a neuroscientist. When he transferred over to the doctoral program in neuroscience, he had to take all the required core courses: neural structure and cell biology, electrophysiology, biophysics, and neurochemistry. Jonathan appreciated the introduction to the breadth of the field, and he was constantly amazed at just how much knowledge he had retained. Last week, for example, the program brought in a neuroscience researcher with an expertise in cell physiology. He went to the seminar because he was required to do so, but he left amazed that he could actually understand a portion of the professor’s work. He thought about what one of the professors in the neuroscience program kept saying—that working with brain cells and understanding action potentials was the “real science in neuroscience.” Jonathan felt sure that, if he ever asked the professor about the connection between linguistics and neuroscience, the answer would not be kind. Although he couldn’t say with real certainty, he only imagined that most of his neuroscience peers felt the same way. The location of his office in the basement of the neuroscience building was quite appropriate, he thought glumly. He was surrounded by other psycholinguists and computational neuroscientists, areas that were in many ways peripheral to the
159 field of neuroscience, just as he was. The more-central physiologists and molecular biologists worked high on the upper floors. Sometimes Jonathan would meet up with his classmate, Walter, who worked on the fourth floor. He felt like an outsider, and thought the distant sounds of dogs barking and birds chirping, locked away in the research laboratories, were somewhat eerie. Although he never spoke of the issue with his friends or colleagues, the reason Jonathan initially enrolled in the linguistics program was because of the animals. The day he nervously stood before his parents, a skinny twelve-year boy, and told them he was becoming a vegetarian was still vivid in his memory. Although Jonathan had long been interested in the sciences, he wasn’t sure how he could ever pursue science as a career. Animal research seemed an inherent component of the scientific process. He still felt a disconnect between his personal and professional identities. Proclaiming that he was ethically opposed to animal experimentation would not endear him to his neuroscience professors, and certainly not to his peers. He really didn’t want to make anyone feel bad about their personal choices, but he also had no desire to sit around and listen to people talk about their research. Invariably the conversation would revolve around some research technique involving animals, and his stomach would turn. In an effort to avoid the conversations, Jonathan avoided the other students altogether. When Jonathan first considered the neuroscience program at Glenhaven, he felt that he would be forced to conduct animal research. He opted for the program in linguistics with the hope that he could still fulfill his interests in human language
160 from a social science as opposed to a natural science perspective. Only after meeting Dr. Abelson and realizing he could focus on his interests without working with animals did he transfer to neuroscience. The transfer cost him an additional year of coursework, but he considered it worthwhile. Jonathan often thought the frustration related to his transfer from linguistics to neuroscience was only the first indication of what he would face throughout his career. Living from one graduate student stipend check to another made Jonathan incredibly concerned about securing a faculty position at the end of his program. He didn’t have the research interests or skills to be competitive for an industry position, even though the pay would be higher. Not only was it difficult to explain to others his self-definition as a psychoneuro-linguist, but he was also increasingly worried about finding the right job. He could never see himself working in a linguistics department, and recognized that he was too far removed from the foundational core of linguistics to even be seriously considered for a position. He also suspected that he would never be hired in an educational psychology department, even if he promoted himself as a linguist—no doubt he would be affected by the common impression of linguists as bad scientists. Jonathan’s only other option was neuroscience. He was certainly not a neuroscientist in the sense that Walter was. Walter had a bachelor’s degree in biology and completed a M.D. before enrolling in the Ph.D. program at Glenhaven. Many of his other peers in the program also had a rich background in the sciences, with undergraduate degrees in chemistry or physics and seemingly vast experience
161 working in wet labs. Although Jonathan had always liked science, his undergraduate degree was in Italian. His undergraduate transcript reflected his original interest in becoming a teacher, showing only the science courses that the university forced him to take. He wasn’t sure exactly where he belonged. Attending the Society for Neuroscience conference highlighted his outsider status. He had only returned from the conference a few days ago, which was perhaps why the feeling that he didn’t fit was so strong. Walking through the rows and rows of posters concerning the molecular structure of neurons or the biophysics of action potentials, Jonathan felt so far at the other end of neuroscience spectrum that he might as well have spoken another language. While his research considered neurons, Jonathan was more interested in the relationship between the neural structure of the brain and language. He examined that relationship with computer modeling, which also placed him awkwardly in the camp of the computational neuroscientists. His introverted, somewhat anti-social nature probably worked out for the best, he realized with frustration. He had an interest in so many different places that he really belonged nowhere. Jonathan could hide behind his computer screen, or spend hours with Alzheimer’s patients, and few people would really notice. There was a small consolation in the fact that in two months, he and Dr. Abelson would be presenting their work at a conference on aphasia, followed by a cognitive psychology conference. He felt more comfortable there. There were no answers to be found, at least not so late in the evening. He was too tired. Jonathan turned off the light, and
162 hesitated for a moment before shutting the door, trying to decide if he should say good night to Dr. Abelson. The decision was quite easy. A quick good night would turn into a long conversation about his data analysis, which would further delay his commute home. Besides, he would be back in the office in just a few hours. His decision made, he softly shut his door and turned towards the elevator. Interdisciplinarity and disciplinary/community integration Within the university, interdisciplinarity is achieved through both cultural and structural changes. Harris, Giard, and Pijawka (2003) noted that one of the most significant elements of successful interdisciplinary graduate education is organizational strategies—program structure, specialized administrative policies, and other organizational initiatives. The neuroscience program at Glenhaven is the result of a new academic structure that was built upon disciplinary strengths. The interdisciplinary structure of the program has a strong influence on learning, research, and socialization. Doctoral students are located in laboratories that frequently provide exposure to related bodies of knowledge. Victor, for example, worked with computational modeling and experimental psychology. Megan received limited exposure to biochemistry during her doctoral experience. Jonathan’s experiments utilized research from computer science and linguistics. Because of the interdisciplinary breadth of neuroscience, doctoral students such as Victor and Jonathan construct, influence, and are influenced by a unique community. For example, a first-year female student worked in a neural biology lab that was next
163 door to another lab run by a professor who specialized in neural anatomy. The benefit, she said, “is just having the other lab there to talk to, and bounce ideas off of. We have our journal club together, and we meet every week. So basically, we are almost the same lab. We all work together, and if you have a question or want to borrow something, it is basically like borrowing it from your own lab.” Nicole, a fourth-year doctoral student, noted, “I am in neuroscience, but working in kinesiology, and on the floor of my building, we have a neuroanatomist on one side and a computational neuroscientist on the other. It feels very interdisciplinary.” This broad exposure through research is part of the program’s efforts to give students an extensive understanding of the biological, cognitive, and computational approaches to understanding brain function. This exposure is also reflective of the nature of neuroscientific knowledge. Neuroscience exists because of the integration of biology, chemistry, and physics with studies of behavior, physiology, and structure. But as Nicole concluded, “You know, the grass is always greener, so it would actually be nice not to be so intellectually isolated. Like if our whole floor was people who did the same thing we did [kinesiology], that wouldn’t be so bad.” On one hand, Nicole is exposed on a daily basis to the breadth of interdisciplinary neuroscience research. On the other hand, she feels intellectually isolated because there are no other kinesiologists in her building. As a third-year student with an engineering background concluded, “I liked working in a lab with people trained as
164 biologists, but they think differently. Sometimes the thinking they use to approach a problem just makes no sense to me.” Interdisciplinarity, academic culture, and disciplinary integration In terms of negotiating the academic structure, the breadth of the program often proved to be more frustrating than intellectual stimulating. While the neuroscience program is officially located on the main campus, some 20 percent of students work in research laboratories in other locations, such as the medical school campus or the affiliated vision and hearing research center. As I explain later in this chapter, several intellectual and social activities are organized to help doctoral students negotiate the program breadth, but not all students are able to take advantage of them. For one student, who is the only neuroscientist in a lab of doctoral biology and pharmacology students on the medical school campus, “It is really isolating to be away from the main campus and from the other neuroscientists. I don’t ever see them, my classmates, ever since our last class ended. I’m sure they hang out together and have lunch—but I just see the people in my lab.” An international student in her first year of the programs worked with a lab on the main campus. When I asked her if she ever considered working with a professor in another location, she explained, “I tried to contact some professors on the [medical school campus]. But I don’t have time to go back and forth—I just can’t do this. So I just give up. I just stayed here.”
165 The distance between neuroscience laboratories has an impact on more than just student experiences. The distance is not simply structural; it is also a cultural division. As one neuroscience professor who worked on the main campus explained: [The distance] is a terrible problem. We essentially do it, to satisfy the provost who wants to say we have an integrated program, but it’s an enormous waste of time to travel back and forth between the two campuses….I’ve been at the university since 1989, and I’ve been on [the medical school campus] maybe 3 or 4 times. I just got an email for a meeting there today. I’m not going to go. I don’t see an easy solution to it; [the medical school campus] might as well be in another life space. During my first visit to the medical school campus, I was struck by the clinical, human element of neuroscience which I perceived to be missing from the main campus. Walking through the halls of the cancer facility on the medical school campus and informally talking to doctors who worked on issues of brain, spinal cord, and nervous system cancers, the goal of neuroscience was (to an outside observer) startlingly clear. In my fieldnotes from my first visit to the medical school campus, I wrote, “Somehow, being surrounded by doctors in white lab coats with stethoscopes reinforces to me in a way that nothing has done before that this is a study about science.” Such a distinction is not absolute, of course. On the main campus, Glenhaven hosted an interdisciplinary Alzheimer’s research center that worked with Alzheimer’s patients from the community. The affiliated off-campus research laboratory treats patients with degenerative auditory disease. Culture and identity in higher education is bound in context—time, space, and location (Valimaa, 1998). The disciplines are structurally embodied through
166 such facilities as the neuroscience building at Glenhaven; faculty and students physically represent often abstract knowledge concepts. Amanda worked in a psychology laboratory, and embodied the overlaps between cognitive neuroscience and psychology. Nicole worked in the boundaries between kinesiology and biology. The overlap exists because students bring with them a set of research interests, and align with a professor on those interests. By understanding how doctoral students in neuroscience practice interdisciplinarity, we gain a greater understanding of their values and beliefs. In the neuroscience program at Glenhaven, the practice of interdisciplinarity occurs through a series of required courses, seminars, and conferences as well as the daily routine of a research laboratory. “Knowledge is a social construct undergoing interpretation and change on a variety of levels and in a variety of social contexts,” concluded Tierney (1991, p. 212). “As organizational participants construct their reality, they also construct what counts as knowledge.” Positioning oneself as an interdisciplinary researcher can bring about academic rewards (such as tenure and promotion), tangible professional effects (such as conference papers or books), and intellectual outcomes (including intellectual stimulation, a broader understanding of a research topic, and new epistemologies) (Lattuca, 2001). For the doctoral students in this dissertation, academic rewards and tangible professional effects were often the most immediate concern.
167 Students expressed both positive and negative opinions regarding the possible professional implications of completing an interdisciplinary doctoral degree. Madeleine, who graduated from the program in 2004 and recently accepted a postdoctoral position, stated, “Neuroscience is such an interdisciplinary topic that everyone is interested in it. Everyone can find a little niche to fit in. And because of that, it has a lot of appeal.” A second-year international student said, “When biology comes into a marriage with the computational theories, the most interesting thing would be the brain. And the most promising field would be neuroscience, so that’s why I chose it.” Another international student noted, “In the end, which lab you worked in and what kind of paper you wrote is more important than the department where you graduated.” These students who were optimistic about the impact of an interdisciplinary doctoral degree on their professional outcomes felt that neuroscience was a highly regarded field of study. In addition, their research laboratory, dissertation topic, and advisor were ultimately more important considerations than the degree program. Anna, a first-year student, concluded, “When you apply for the jobs, you have to write what you did your dissertation on, and they get a sense of what kind of techniques you know and things like that. So I guess at the end [the title of the degree] doesn’t make a difference.” Some students were unsure how an interdisciplinary career in neuroscience should be conceptualized and how their degree would prepare them for their first professional positions. These concerns were related to skills and training gained
168 during the program, and how such knowledge would be applied after graduation. Not all students were optimistic that an interdisciplinary doctoral degree in neuroscience would have positive professional outcomes. Such fears were a recurring topic during my interviews with students. One student, preparing to defend his dissertation, explained, “I don’t plan on continuing the research I am doing now. It’s hard to find something that complements electrophysiology [his field], so that is a little bit hard for people to start over. You are an expert in this, and then have to go back to ground zero in that. But I think that is what you have to do.” In addition, students expressed concern over securing a disciplinary academic position as an interdisciplinary scholar. Other students were more interested in an industry research position; those students who perceived their skills to be outside the core biological base of neuroscience were uncertain as to their job prospects outside of the academy. “I question how I can be marketable,” said one student, who started the program in 2000 and works in a very small subfield of neuroscience focused on neural anatomy of a unique animal species. “Why should they hire me when they can have someone who has done cell cultures for the past five years?” Gloria, a first-year student, concluded, “I wonder if it is because neuroscience is so new. I mean, none of our faculty have a Ph.D. in neuroscience.” In chapter two, I outlined two types of interdisciplinary socialization: one, where individuals receive a disciplinary doctorate and engage in interdisciplinary research over the course of their career; and two, where the doctoral program is structured as an interdisciplinary education. As
169 Gloria noted, the lack of faculty role models who engaged in an interdisciplinary doctoral program can be discouraging for some students. Interdisciplinarity, knowledge context, and disciplinary integration The exposure to the breadth of information under the interdisciplinary neuroscience label is essential to train researchers in the field. But simply providing students with the information does little to put it into context. Knowledge is always contextual; that is, students interpreted the information based on their individual experiences and research interests. As I previously noted, most students entered the program with a focus on a particular area of neuroscience. Few, if any, students would undertake a drastic change across the continuum of identities. Knowledge and information outside of a student’s area of research was simply not significant to his or her daily practice of neuroscience. Diane, a recent graduate of the program, focused on behavioral neuroscience. She reflected on the required core course in electrophysiology, which is a study of the electrical charges of neural behavior. “The hardest module probably always for me will be electrophysiology,” she concluded. “I will never model cell firing, so no, was that necessary? Understanding physiology— it was a foreign language.” Jonathan felt that his focus on psycholinguistics and computational neural modeling placed him outside what he perceived to be the core biological knowledge of neuroscience. He was required to attend seminars featuring a variety of neuroscience researchers, even though the majority of such presentations were well
170 outside his area of research. “I’m always amazed I retained enough knowledge to understand even a little bit of some of those things,” he confided. Compared to Jonathan, Victor felt more responsibility to understand and retain information presented in the core curriculum. “I want to be able to model a human being [in my research],” he concluded. “When you are trying to do that, you have to know how the biology works.” The challenge for effective interdisciplinary socialization is not simply exposure to the information, but also how such information is acted upon and placed into context. Victor’s classroom learning was enhanced by its connection to his laboratory experience. The program administrators recognize the difficulty students experience in assessing all the resources available to them in the program. In recent years, the university instituted a tram system to carry students to various locations, such as the medical school campus, on a regular schedule. Seminars and conferences on the main campus are broadcast to specified locations at the medical school. One fifthyear student at the medical school explained, “It was the going back and forth [between the different campuses] that cut out your time. And now we have videoconferencing, so it is only an hour, rather than the two or three hours required before with travel.” This student first started working on the medical school campus during her first year in the neuroscience program. Along with several other students and professors, she lobbied the program administration for more integration between the two campuses. Instead of a three-hour drive to the main campus to attend a guest
171 seminar, she now has a short walk across the medical school campus to a spacious auditorium. “More people go to the events now, students and faculty,” she concluded. The program also actively supports the neuroscience graduate organization, in which many students participate. The organization has monthly meetings, pizza lunches, and a weekly afternoon tea for faculty and students. Most of these events are held on the main campus. The weekly afternoon tea, for example, is designed to allow faculty and doctoral students to socialize in an informal setting. “They have to make us get out of the lab and go,” one first-year student confided. “I’ll go mainly for the food, but sometimes I can have a nice conversation with someone.” The afternoon tea is held in the main neuroscience building. “The only way I go to stuff like that, is if I happen to be on the main campus for some other reason,” a third-year student who works on the medical school campus stated. “And really, I’m rarely there, so I just don’t go.” Several doctoral students also take an active role in the recruitment and orientation of new students, and plan numerous off-campus social events for first-year students. In addition, at the end of the spring semester, the program hosts an off-campus weekend retreat for faculty and students. “The retreat is an excellent way for students to get to know each other,” explained Dr. Matthews, the psychology professor. “In psychology, we don’t have that because students enroll with much more in common than neuroscience.”
172 Scientific culture consists of multiple components, including material, conceptual, and social elements (Delamont, Parry, & Atkinson, 1999; Hacking, 1992) that are represented through institutional structures such as departments. The socialization into science is “an all-encompassing immersion into an institutional setting” (Campbell, 2003, p. 900). Doctoral neuroscience students are socialized into both the institution of science and the university. I previously discussed the relevance of institutional structures related to interdisciplinary space and location. In terms of the institution of science, the interdisciplinary nature of neuroscience can result in difficulties for students in terms of community integration. Jonathan never felt like a member of the linguistics department during his two years as a student there. Even after he transferred into neuroscience, he felt a stronger sense of belonging with other neurolinguists than with his fellow doctoral students. “Knowledge is the prime commodity of academic life,” Becher concluded. “It is the nature of knowledge itself which gives shape to …the working patterns of academic communities” (1990, p. 337). With his strongly held beliefs against animal research, Jonathan was distinctly removed from the predominant patterns of laboratory research in neuroscience. His work in a relatively small component of the interdisciplinary breadth of neuroscience resulted in further isolation. The context of student learning, integration, and socialization is shaped by laboratory arrangements and contact with other practitioners. For Jonathan, this context was limited. Megan experienced a similar
173 time in her research laboratory, which was located in an isolated area and staffed by only one student and her advisor. Successful integration into the multiple communities that constitute neuroscience can be beneficial to student development. Nicole, a fourth-year student who works in close proximity to scientists from other disciplines, is part of a large research laboratory; her professor actively seeks collaborative projects with scientists across campus. While Jonathan felt his neuroscience interests placed him outside the interdisciplinary community, Nicole’s background in cell biology and biochemistry fostered her enthusiasm for neuroscience. She struggled, however, with her research topic during her first three years in the program. Nicole’s laboratory utilizes rodent models to determine how the stress axis is controlled by the time of day—for example, why some individuals are more productive at selected tasks during specific times. Her initial projects resulted in very poor outcomes. “The experience was super traumatic,” she recounted. Her lack of progress and her advisor’s support of collaborative research motivated Nicole, as she explained: As I was done with my third year, I still didn’t have anything, so I hooked up with a guy in kinesiology…and they have these insulin clamps. Basically, they are able to hold the blood sugar constant. They just put in these catheter and pumps or what not. And so I started talking to them about using insulin as a stimulus in my project. I like it because it is physiological. So I’ve been working on that for the past two years. It is better for me, because I at least have some measure that the techniques are really working, because I measure [the rats’] blood sugar. A grad student in [the kinesiology] lab is the one who taught me how to do all of this stuff.
174 Although Nicole’s collaborative experience has ultimately been rewarded, the experience has also challenged her perception of knowledge. “The guy in kinesiology, he is below the neck, and we are above the neck,” she stated. “And you realize there is a whole body down there. And [the kinesiology graduate student] comes in and talks about the pancreas, and I think, ‘Where is that organ? Wow…the pancreas. What could that do?’ [laughter] Sometimes I am just overwhelmed.” For Nicole, the integration of disciplines fostered by the interdisciplinary program shaped the direction of her research and challenged her identity as a scientist. Students do not passively collect knowledge over the course of their program. Instead, they actively shape their own learning experiences through community integration. “[Students] attribute meaning…through processes of interpretation that are mediated by patterns of social interaction centered on training,” Campbell wrote (2003, p. 899). Successful integration of various disciplines ensures that students are exposed to epistemologies and methodologies preferred in multiple areas of study, and enables students to utilize those concepts as a means of furthering interdisciplinary topics. Larry, a first-year student with a background in engineering and biology, selected his laboratory because his advisor, a molecular biologist, encouraged a “mechanical, electrical approach” to biology that other professors dismissed. “All along in biology,” Larry noted, “I have been interested in the idea of a cell as part of a mechanical system. Cells opening, turning, shifting, changing…”
175 His current advisor encourages Larry to integrate the principles of molecular biology, biophysics, and engineering in his research. Interdisciplinarity, external influences, and disciplinary integration Significant elements of socialization for interdisciplinary scientists often mirrored those of their peers in traditional disciplinary programs. As a process of active social engagement, socialization is dependent on involvement with a professional community. Attending professional conferences and submitting articles for publication are a crucial component of doctoral training (Delamont & Atkinson, 2001). Conferences and journal articles serve as a means of disseminating one’s research as well as networking and name recognition. The Society for Neuroscience represents the professional community of neuroscientists. A first-year student said, “Pretty much everyone in the neuroscience program goes to the conference. It is a huge thing.” Another student noted, “[The conference] is a good thing about neuroscience, because it brings in so many people, you are pretty sure to meet someone you can talk to about your work.” As I discussed previously in this chapter, the Society for Neuroscience does not represent the sole professional community for neuroscience. Neuroscience students engage in a range of other professional associations. One student, who is preparing to defend his dissertation, explained, “I think what is ideal is to go to two meetings a year, to go to Neuroscience and then a smaller meeting. The Neuroscience [conference] does expose me to new things that I probably wouldn’t be
176 exposed to at a smaller meeting.” When I asked students what conferences they attended in addition to the Society for Neuroscience, the answers reflected the depth and range of the field: Research and Society on Alcoholism, Biophysical Society, The Society for Nicotine and Tobacco Research, International Meeting for Autism Research, Society for Behavioral Neuroendocrinology, Academy of Aphasia, and Molecular Cognitive Symposia, to name a few. I draw two conclusions from the range of conferences for neuroscience students. First, as one first-year student said, “You are always reminded of [the interdisciplinary nature of neuroscience] when you go to these conferences because there are so many things you can do, and so many ways you can ask questions.” While the Society for Neuroscience conference represented the students’ emerging identification as a neuroscientist, their participation in other professional associations served as a connection to a constituent discipline, a multiple reference group. In addition, faculty advisors were influential in determining in which associations students were involved and to what extent. Not only did the faculty advisor commonly pay a student’s travel expenses, but the advisor also determined what research should be presented at a particular conference. A second-year student said, “[My advisor] presents his research at Neuroendocrinology, so that is probably another one for me to go to—when I’m ready.” Another student who works in psychology added, “My advisor basically said I need to pick which conference I
177 want to be associated with, either aging or neuroscience. I seem to be the only one who thinks I can do both.” A summary of disciplinary/community integration and interdisciplinary socialization Ultimately, students identified several positive intellectual outcomes which resulted from participation in an interdisciplinary doctoral program. First, students recognized an ability to engage in the production of new knowledge. Alex, a firstyear student introduced in chapter one, said, “I am interested in behavior, human behavior in particular. I think it is interesting how we see the world. And I am interested in science, I have an engineering kind of bent, too. So, it seems to kind of mesh well.” Second, the ability to create unique areas of knowledge specific to individual interests as well as connect one’s research to the work of others was highly valuable. Lisa started the program in 2001. When asked about the intellectual outcomes of interdisciplinarity, she responded, “If I know what somebody does, then I don’t have to be an expert on it. I just know enough to know the things that they do, and I can develop a collaboration with that person, a working relationship, and cover that much more ground. Whatever question it is we want to answer.” In addition, participation in an interdisciplinary doctoral program often changed students’ perspective of the disciplines. Students gradually gained a new perception of the knowledge they gained as an undergraduate. A first-year student explained, “I started as a math major, and ended up with a degree in psychobiology. But now, I am
178 gaining a good, broad, strong sense of neuroscience. The goal of neuroscience is to understand how the brain works, and you need all of those areas to come together.” Conclusions In this chapter, I presented three vignettes drawn from my interviews and observations of students to illustrate how such concepts as knowledge acquisition, identity development, and community/disciplinary integration are experienced by doctoral students in an interdisciplinary neuroscience program. The data presented here demonstrates the nature of the disciplines as “social groupings” (Lattuca, 2001) shaped by perception and interaction. The doctoral experience of neuroscience students at Glenhaven was one of continual negotiation—between individual expectations, faculty demands, professional responsibilities, and perceived disciplinary boundaries. It is significant to recognize that students exhibited a range of interdisciplinary experiences. For those students who worked closely to the core of neuroscience knowledge (i.e., molecular or cellular biology, physiology, and neuroanatomy), identity development and community negotiation occurred with a different intensity compared to those peers who worked further outside this foundation. In many ways, the barriers between the disciplines at Glenhaven had been lowered by the formal creation of an interdisciplinary program in neuroscience, easing the flow of knowledge, ideas, and individuals across various communities. Such interaction is essential for the production of scientific knowledge (Hall, 2004).
179 Yet students still struggled to define themselves as “interdisciplinary scientists.” The following chapter considers this struggle by returning to the research questions which guided this dissertation, and examining theoretical implications for interdisciplinary knowledge, graduate education, and doctoral student socialization.
180 CHAPTER FIVE UNDERSTANDING INTERDISCIPLINARY SOCIALIZATION “I don’t know how you want to manage this,” Jason tells me as we sit awkwardly across from each other. “I have some things I want to tell you. So you tell me what you want to know, and then I’ll tell you what else I think you should know.” I was first introduced to Jason’s somewhat abrupt demeanor in our earlier email correspondence. An international student from Spain, he initially enrolled in Glenhaven’s doctoral program in engineering six years ago. After several frustrating semesters, Jason decided to transfer to neuroscience. Shortly after I turn on the tape recorder, he reveals his next professional step: Jason is transferring back to engineering, adding at least another two years onto his graduate career. He confides, “I estimate I can get out of here in two years, but that is a bad thing. Eight years it will have taken me to earn this degree. That is something bad.” I am initially uncertain how to respond to Jason’s disclosure. His shoulders sag slightly in defeat; his gaze shifts away from mine, and then he unexpectedly stands. “Do you want to see the lab?” he asks. Before I can respond, he walks over to a corner of the room, motioning me to follow. We stand beside each other as Jason reaches for a handle, adeptly pulling on a swivel door that encircles us. For a moment, there is only darkness, and then we step into a small room, softly awash in a single, low-wattage safelight. “What do you do here?” I ask, impressed by the array of computers and scientific equipment. “We work with animal retinas,” Jason
181 responds, “and they are extremely sensitive to light. I do most of the computer work, modeling, with the data we get from here. How does the brain work? How does the retina send an image to the brain? It’s a fascinating question.” As Jason describes the research—the intricacies of retina, its relation to neural functions, how he uses the data in computational modeling, the joy he feels working with neural models—the awkwardness from his disclosure diminishes. His voice is animated, and he seems completely at ease. “I’m not sure I understand,” I tell Jason when we finally leave the small lab. “You really seem to enjoy your work. Why are you going back to engineering?” The room is very quiet as he considers my question. “I came to Glenhaven to understand how the brain works. And I thought I would use different engineering techniques to do that. But engineering is not science,” he concludes. A steady staccato of water dripping from the nearby sink fills the silence between his words. “I wanted to do research, and engineering did not support that. I decided to go into neuroscience. In neuroscience, you only have to take two core courses, and afterwards, you do all the research that you want. That’s what I wanted.” Still unsure, I ask, “So what changed for you? Why are you going back?” He answers: Everyone in neuroscience I know like me, people who work in psychophysics and modeling, they come out of neuroscience and are unsure of where to work. And in industry, with a degree in neuroscience, it is problematic, if you don’t have biological training. I am a person who knows mathematical tools, and how to apply them, and can understand physiological problems… [but] I don’t know biology. If I had to start over, I would have stayed in engineering, and spent my free time trying to satisfy my curiosity by looking at neuroscience problems, but still be in engineering. I would take my data to people in neuroscience, and see what they could tell me... because I am not a neuroscientist.
182 For many individuals enrolled in the neuroscience program at Glenhaven, participation in an interdisciplinary community is a significant component of the doctoral student experience, one that yielded positive outcomes. For some students, however, such as Jason, the interdisciplinary breadth of neuroscience was not a natural integration of disciplinary knowledges or a necessary element in producing neural research. Interdisciplinarity was instead perceived as a deterrent to his intellectual and professional development. The doctoral students in this dissertation exhibited a range of interpretations regarding their interdisciplinary community. My goal in this chapter is to draw conclusions from student narratives; specifically, I define interdisciplinary doctoral student socialization in the neuroscience program at Glenhaven in relation to previous literature regarding socialization in the disciplines. I first discuss interdisciplinary doctoral student socialization in specific stages which were introduced in the previous chapter: knowledge acquisition, identity development, and disciplinary/community integration. Next, I return to the research questions which guided this dissertation and offer conclusions regarding disciplinary and interdisciplinary doctoral student socialization. After exploring these themes, I outline limitations of this study and offer suggestions for future research. Understanding doctoral student socialization in interdisciplinary programs The recent literature regarding the doctoral student experience has focused on how individuals are socialized to key academic and professional roles (Austin, 2002a; Girves & Wemmerus, 1988; Golde & Dore, 2001; Weidman & Stein, 2003).
183 Understanding doctoral student socialization requires recognition of numerous significant factors, including the influence of the institution and the discipline. As an organizing factor of student experience, disciplines tend to exhibit unique cultural characteristics. Epistemological features, issues of language and communication, and preferred values and beliefs are all related to the concept of the discipline. The dominant feature of doctoral education is the development of specialized knowledge within a particular discipline. In this dissertation, I considered the influence of academic community on doctoral student socialization by studying an interdisciplinary doctoral program. How is the socialization process influenced when students navigate the boundaries of multiple disciplinary communities in pursuit of the Ph.D.? Knowledge acquisition, identity development, and disciplinary/community integration are significant areas of research related to doctoral student socialization (Antony, 2002; Austin, 2002a; Golde, 2000). These components of socialization reflect the nature of doctoral education as a process of individual negotiation occurring within a specific social context. Doctoral students construct their professional identities as part of a unique and multi-dimensional social exchange. For students enrolled in an interdisciplinary doctoral program, this process can be complicated by the nontraditional integration of multiple disciplines. How students construct and engage with knowledge, define their professional identities, and determine their reference groups is dependent on this integration.
184 Interdisciplinarity and knowledge acquisition Through the acquisition of knowledge, doctoral students understand and identify with role expectations advanced by the disciplinary culture. “Culture is the product of social relations of the participants within an organization,” noted Tierney and Bensimon (1996, p. 15). Doctoral students gain status as a member of the disciplinary community by internalizing both formal and informal knowledge. This sense of belonging is dependent on acclimating to cultural expectations and demonstrating knowledge proficiency. Completing a required series of courses, engaging in research with a faculty mentor, and connecting with peers, institutional faculty, and other disciplinary colleagues are significant components of knowledge acquisition. Aspects of the program’s organizational structure, such as the mission and academic requirements, can impact student socialization (Weidman et al., 2001). Regardless of a program’s focus (either a single disciplinary doctorate, or a more interdisciplinary structure), the organizational purpose of doctoral programs is particularly relevant to student socialization; the mission influences program characteristics, faculty involvement, and student requirements. Before students enroll in a doctoral program, they are exposed to the departmental mission through the program’s website, its application and recruitment materials, and correspondence with faculty. In chapter four, I outlined the mission of the Glenhaven doctoral program in neuroscience. The program seeks to encourage “a breadth of interests and training” related to neuroscience. In addition, “close contact between faculty and
185 students is considered of major importance in this highly interdisciplinary field.” Glenhaven’s neuroscience program brought prospective doctoral students to campus for a three-day interview and recruitment weekend, which gave potential students an opportunity to interact with current students and faculty. The interdisciplinary breadth of interests and training fostered by Glenhaven’s neuroscience program as well as the contact between faculty and students was significant in terms of anticipatory socialization. Many of the first-year students reported that the recruitment and admissions process at Glenhaven positively influenced their decision to enroll in the program. Such students cited the richly interdisciplinary nature of the program, the interaction between students and faculty, and the supportive peer culture as initial impressions. Students also demonstrated an awareness of the national reputation of Glenhaven’s program. They noted that, although other neuroscience programs were more highly ranked by various academic and reputational standards, Glenhaven’s interdisciplinary structure was strongly appealing. This stage of anticipatory socialization is significant for doctoral student development, as students “begin to assume the values and attitudes of the group they wish to join” (Austin, 2002b, p. 96; Bess, 1978; Van Maanen, 1976). Students become aware of how a particular program is regarded in a larger cultural context— within an area of inquiry, for example, or by funding agencies and industry. While the significance of reputation and initial contact with incumbent students and faculty is important for anticipatory socialization in all disciplines, it can be particularly
186 relevant in terms of student sense-making for an interdisciplinary area such as neuroscience, which can be manifested through multiple and diverse organizational structures.6 In preparation for application, students identified which program was best suited for their particular emphasis in the field. In interviews conducted for this dissertation, several students cited what they viewed as research emphases of the Glenhaven neuroscience program that influenced their decision to enroll. Weidman et al. (2001, p. 56) concluded, “The structure of each discipline or field encourages various student responses based on normative expectations and valued outcomes.” The doctoral neuroscience program at Glenhaven appealed to many students based on its interdisciplinary structure. The program actively seeks applicants with diverse academic backgrounds and professional research experience. During my interviews with students, the diversity reflected in the peer cohort was commonly assumed to be a benefit of studying in an interdisciplinary program. Not everyone agreed with this assessment, however, as I noted in the previous chapter. The disagreement is significant. Such students felt that a more homogenous peer environment would allow them to share details of their own research as well as have more “in common” with their peers. While students could identify what other areas of neuroscience in which their peers worked, and who they might go to with questions or concerns outside of their research area, such interaction appeared to be minimal. 6
A 2003 survey of neuroscience programs found that 40% were located within multiple schools/departments of the university; 28% were solely in the arts and sciences; and 22% were within a school of medicine (ADNP, 2003).
187 Peers can provide a rich source of information for doctoral students. Becker, Geer, Hughes, and Strauss (1961) defined the positive nature of collective socialization, such as through the cohort model at Glenhaven, as resulting in “group consciousness.” Weidman et al. further argued, “Group homogeneity eases students into the new culture… [and] increases peer solidarity” (p. 62). A certain number of students, however, felt excluded from this peer solidarity. While agreeing that the organizational structure at Glenhaven allowed them to identify peers who could serve as informational resources, they also noted that their personal interests in neuroscience were often assumed to be far removed from the perceived biological emphasis of the program. Because the neuroscience program actively seeks applicants with diverse range of interests and experience, often the only thing that students share with each other is an overly broad interest in neuroscience—a term that can have multiple connotations. As opposed to the more homogenous nature of the disciplines, the heterogeneity fostered by the interdisciplinary nature of the program fostered discontent in terms of how some students experienced socialization. Doctoral students such as Jason, who worked in computational modeling and identified with engineering; Jonathan, who transferred to the neuroscience program from linguistics; Amanda, with interests in linguistics and cognitive psychology; and Victor, with a strong background in computer science, expressed concern over how their more biological-oriented peers in the neuroscience program interpreted their background. They often felt disconnected from faculty, and
188 were frustrated by the assumption that they should hold specialized knowledge in fields outside of their specialization. Such perception is significant to the question of how multiple disciplines are integrated in a single field of study, what bodies of knowledge remain primary to the topic, and what knowledge is emphasized by an interdisciplinary community. For most interdisciplinary doctoral neuroscience students at Glenhaven, contact with the faculty was a positive element of socialization. This finding is supported by previous literature on doctoral student socialization (Anderson, 1998; Gottlieb, 1961; Tinto, 1993). Golde concluded, “The primary agents of socialization and integration are the faculty” (2000, p. 201). In an interdisciplinary area such as the neuroscience program at Glenhaven, however, doctoral student socialization is not only enhanced by purposeful contact with faculty, but also significant interaction with faculty from multiple disciplines. This multi-disciplinary interaction, according to most students, did not regularly occur. Several first-year students noted that they had chosen the neuroscience program at Glenhaven because of its richly diverse, interdisciplinary structure. “When everyone is thinking the same way, it truly stagnates,” said one first-year student. “Having the other professors and students here really helps that.” But outside of the required core classes, which were taught by a diverse group of faculty, students had little if any regular interaction with faculty outside their primary area of research. Because of the breadth of the program, students have little opportunity for engagement with professors other than their
189 primary advisor and those faculty who worked in closely related fields to the student’s area of research. The dimension of serial socialization identified by Van Maanen and Schein (1979) concluded that faculty can serve as role models for students throughout their doctoral career, positively influencing socialization. The interdisciplinary structure of Glenhaven’s neuroscience program only increased the significance of structured contact with faculty. Overall, students lacked a broad connection with faculty in the program. Such interaction occurred primarily in two formats: first, through the core curriculum required of doctoral students and second, through mandatory laboratory rotations. The short modules which comprised the core class were each taught by a different member of the neuroscience faculty, representing a specific discipline and area of research within neuroscience. While some individuals expressed frustration over the amount and manner of the material presented, the course offered many students the only chance to interact with core neuroscience faculty outside of the student’s area of research. The laboratory rotation also provided students the opportunity to interact with a professor in a more intimate research environment. Students generally did not select rotations outside of their research interest; such interaction was bound by the student’s background and previous experience. Rotations allowed students to work closely with several faculty for a short period of time before committing to an advisor and a research topic, thus exposing them to various possible identities and interdisciplinary approaches to knowledge production.
190 In terms of socialization, the close contact with faculty through advising and laboratory work encouraged student socialization to a specific area within neuroscience. Most students did not develop an extensive cross-disciplinary network of faculty and peers during the program. During my interviews with students, several individuals mentioned that they knew very few of the affiliated neuroscience faculty beyond their primary advisor. Some parallels exist in terms of disciplinary socialization. For example, a doctoral student in biomedical engineering at a large research institution can be isolated from her peers in civil engineering, mechanical engineering, computer science, or any number of other academic departments within the engineering school. Each discipline (such as engineering) includes a variety of specializations, or subdisciplines, which do not always share an overlap of knowledge. I draw two conclusions from the lack of extensive cross-disciplinary interaction between students and faculty in the interdisciplinary neuroscience program. First, first-year students commonly spoke of their initial expectation that they would experience close contact with faculty from multiple disciplines as part of their program. Yet once enrolled in the program, the core course offered students the best (and sometimes only) opportunity to have this interaction. Extensive contact with faculty was naturally limited to the primary advisor and other faculty within the constituent discipline identified by the student. However, I argue that extensive contact with faculty from multiple disciplines was less important to interdisciplinary
191 socialization than the student’s primary advisor. Various professors emphasized the breadth of the neuroscience perspective, the integration of bodies of knowledge, and the significance of collaboration to different degrees. Collaborative research is an essential requirement for the production of interdisciplinary knowledge. An ideal result of interdisciplinary socialization in neuroscience is that individuals are aware of the need for collaboration to advance knowledge. Interdisciplinarity and identity development The pace of the interdisciplinary neuroscience program influenced doctoral student socialization, similar to influences found in more traditional disciplinary programs; the degree of time and energy required of the student in terms of meeting the requirements of the program is positively related to socialization and identity development. Weidman et al. (2001, p. 63) concluded, “Investment increases largely as a result of faculty and student interaction as the student reaches to meet faculty standards and expectations.” The core neuroscience curriculum at Glenhaven exposed doctoral students to a large amount of information in a short period of time. Although much debate existed among both the students and the faculty in terms of how much of this information they were expected to master, students were aware that the knowledge presented in the core classes had been identified as significant by the faculty. Consider the answers students gave when asked what knowledge is important for neuroscientists. Common responses identified neural structure, the role of ion channels in neural function, the critical role of hormones, and the
192 fundamentals of neuroplasticity. For neuroscience students such as Jason (introduced at the beginning of this chapter), whose background knowledge and research interests had little overlap with these topics, the core course presented the most direct exposure to areas of specialized knowledge that the student was likely to receive during their doctoral education. I return to Klein’s (1990, p. 183) statement— successful interdisciplinarity depends upon knowing “what information to ask for and how to acquire a working knowledge of the language…pertinent to a given problem.” The core course allowed students to gain this “working knowledge” as part of their identity development. Faculty, particularly the student’s primary advisor, played a particularly significant role in terms of identity development and socialization for the interdisciplinary neuroscience students at Glenhaven. This finding is similar to previous research regarding the socialization of doctoral students in the discipline. Faculty ultimately “have a major responsibility for shaping a professional selfimage” as part of the doctoral student’s development (Bragg, 1976; Katz & Hartnett, 1976; Rosen & Bates, 1967; Tinto, 1993; Weidman et al. 2001, p. 66). Within the interdisciplinary neuroscience program at Glenhaven, faculty played a similar role for doctoral students: shaping dissertation topics and research interests, influencing student schedules and laboratory activities, and directing students towards bodies of literature and relevant research techniques. Beyond these expected influences, however, the neuroscience faculty were particularly significant for some students in
193 terms of shaping individual perspective regarding research topics; that is, some faculty modeled the importance of collaborative research by engaging in such practices, and involved doctoral students in research that spanned disciplinary boundaries. Not all faculty encouraged or recognized collaboration. For those faculty who did, however, students reported that such socialization positively impacted their perspective of neuroscience as an interdisciplinary field. Collaboration was not only advocated in abstract terminology, but also manifested through actual practice. Hall (2004, p. 4) concluded that the opportunity to combine different disciplines in research is a hallmark of effective socialization in an interdisciplinary field such as neuroscience. Just as disciplinary identity commonly originates from academic work, so is interdisciplinary identity related to academic work, which supports the significance of collaborative, integrative research as part of the student experience. I return to an argument I first presented in chapter four—examining interdisciplinary socialization requires a focus not strictly on the boundaries that separate various bodies of knowledge, but on the student’s perception of how those bodies of knowledge are joined. Much of the previous literature on interdisciplinarity has maintained this structural emphasis and considered the degree of integration as the most important characteristic of interdisciplinary knowledge (Apostel, Berger, Briggs, & Michaud, 1972; Newell, 1998). The analysis from a cultural perspective differs. Students frequently evoked the symbolic identity of a neuroscientist. They
194 chose to enroll in the neuroscience program because of its “cutting edge” reputation, furthering the conception of interdisciplinary knowledge as inherently advanced. Students also possessed a disciplinary identity, based on their previous professional and academic experiences; that is, students had previously formed a definition of the disciplines, how one discipline related to the other, and how their self-image as a scholar/researcher “fit” into this structure. Ultimately, however, students developed a multidisciplinary identity. Cornell (2000, p. 50) defined this approach as “narratives of connection, focused not on the boundaries—on what separates people—but on connection, on the intertwined patterns of descent that muddy boundaries, fuzz differences, and create shared narrative space.” The shared interdisciplinary space between neuroscience students and faculty was typically more authentic than the structural boundaries of the disciplines. The structure and pace of Glenhaven’s interdisciplinary neuroscience program reflects other doctoral programs in the sciences; after the completion of coursework, students became more invested in the work of their laboratory and more isolated from the larger peer community. The completion of a dissertation is the goal for Ph.D. students, regardless of disciplinary affiliation. “The dissertation,” concluded a 1995 report on the graduate training of scientists and engineers, “as a demonstration of ability to carry out independent research, is the central exercise of the Ph.D. program” (COSEPUP, ¶ 3.7). After completion of coursework, however, the neuroscience students at Glenhaven reported that peers did remain an important
195 part of their social community. First, the program administration supported a host of activities, seminars, social events, and other gatherings that encouraged students to maintain connection to their peers. The student organization was particularly active. One meeting of the student forum that I attended had some 45 attendees—over half of the students in the program. Weekly seminars and afternoon teas were common and generally had a strong student representation. For many students, such interaction created a viable “neuroscience community” on campus in which they could identify as a member. Those students who worked in the primary neuroscience facility or elsewhere on the main Glenhaven campus were more likely to note the saliency of a larger neuroscience peer community. Students on the medical school campus still remained somewhat isolated from their neuroscience peers, and were less likely to travel to main campus for social events. In addition, a student’s laboratory peers served as a primary means of socialization as a student progressed through the program. The definition and composition of this community varied according to the individual student and her research interests. The composition of one’s immediate peers is significant. For example, some labs were comprised solely of doctoral students from the neuroscience program. Jason’s lab, which I profiled in the introduction to this chapter, consisted of doctoral students from neuroscience, biology, and engineering. Jonathan, who originally enrolled in the doctoral linguistics program at Glenhaven, worked closely with a professor and doctoral student from linguistics even after his
196 transfer to neuroscience. I also introduced Amanda in chapter four, who was the only neuroscience student working in a lab comprised of faculty and doctoral students from psychology. The fact that these peer colleagues were commonly enrolled in other doctoral programs at Glenhaven, representing a range of disciplines, was integral to a student’s definition of the interdisciplinary foundation of neuroscience and their interdisciplinary identity development. Some students identified multiple reference groups—those within the neuroscience program, and those colleagues within the relevant constituent discipline. Interdisciplinarity and disciplinary/community integration Knowledge is inherently contextual, influenced by social processes. Tierney (1991, p. 212) concluded, “Knowledge is a social construct undergoing interpretation and change on a variety of levels and in a variety of social contexts.” As doctoral students construct their individual involvement in a community, they also form a basis for their understanding of knowledge. With opportunities for greater involvement in the community, doctoral students are more likely to persist to degree completion and report greater satisfaction with their graduate education (Bair, 1999; Bair, Haworth, & Sandfort, 2004; Golde, 1996; Lovitts, 2001). A challenge related to interdisciplinary socialization is not simply to expose students to a wide breadth of information, but also to contextualize how such knowledge is acted upon in practice; this socialization process calls upon student involvement. In this study, such
197 involvement not only influenced a student’s satisfaction with their degree program, but also shaped how they perceived of the interdisciplinary nature of neuroscience. As a process of active social engagement, socialization is dependent upon involvement with a professional community. Attending professional conferences and submitting articles for publication are a crucial component of doctoral training (Delamont & Atkinson, 2001). Conferences and journal articles serve as a means of disseminating one’s research as well as networking and name recognition. “Attending conferences is a part of becoming socialized into the profession,” Dolan, Kropf, O’Connor, and Ezra argued (1997, p. 754). “Presenting at conferences is crucial not only for receiving feedback about research, but also for networking with established scholars.” The Society for Neuroscience represents the professional community of neuroscientists. Almost every doctoral student interviewed for this study referenced the annual conference of the Society for Neuroscience (SfN). Some professors in the program encouraged their doctoral students to attend the conference, and typically wrote papers for presentation with students. This socialization process is similar to that of traditional disciplinary doctoral programs, where students attend professional conferences as part of their scholarly development. The Society for Neuroscience does not represent the sole professional community for neuroscience. Because of its interdisciplinary foundation, neuroscience students are engaged in a range of other professional associations. In response to the question of what conferences they had either attended or expected to
198 attend as a doctoral student, individuals gave a range of responses. While the Society for Neuroscience conference represented the students’ emerging identification as a neuroscientist, their participation in other professional associations served as a connection to a constituent discipline. Faculty advisors were also influential in determining in which associations students were involved and to what extent. A relatively small percentage of the doctoral students in the program attended both the SfN conference as well as a smaller annual meeting. While this was related to the nature of the research and funding of the faculty advisor, students’ perceptions of “neuroscience” were also significant. Some students, while familiar with the SfN, did not attend the annual conference, believing that their research was not central enough to neuroscience to be relevant for the conference. Reflecting this perspective, one doctoral neuroscience student concluded, “The Cognitive Psychology conference is really nice—[because] it is less on the neuroscience. I mean, you don’t get many neuroscientists at a place like that.” My point here is not simply that some doctoral students attended the annual neuroscience conference, others attended multiple conference, and a very few do not attend any event. Instead, I argue that where a doctoral student becomes involved in terms of professional affiliation is strongly related to their socialization. For all students, attending conferences was a social norm. Where students attended (and the reasons why individual chose to attend one conference or another),
199 however, is important to how they defined their professional identity in an interdisciplinary field. I return to this discussion in the following section. Academic journals also represented an important focus for doctoral student socialization. Similar to other doctoral programs in the sciences, the neuroscience program at Glenhaven emphasized the significance of reading journals as a means to understand current research; the program offered several journal clubs which met on a regular basis. The clubs were organized by the various research emphases of the program, including vision neuroscience, neurophysiology, developmental neurobiology, molecular neurobiology, and cognitive neuroscience. Beyond attendance at journal clubs, however, understanding the hierarchy of journals and the content emphasis of various titles was important for doctoral students in the program. Several advanced students explained that their research would be appropriate to publish in only a select number of journals, and also noted why their work would be inappropriate for others. While many of these journals were from the constituent disciplines of neuroscience, only certain journals published research that focused on neuroscience. Comparing disciplinary and interdisciplinary socialization Much of the theoretical literature regarding interdisciplinarity concentrates on the difficulties faced by scholars who work outside of disciplinary boundaries. Becher and Trowler (2001) noted that, while certain disciplines may exhibit similar features related to knowledge (i.e., the hard/pure sciences, or the soft/applied social
200 sciences), disciplines occupy unique territories within the institutional context. However, Klein (1990) argued that Geertz’s concept of blurred genres reflected the increasingly permeable boundaries of the disciplines. At the beginning of this study, I theorized that interdisciplinary doctoral student socialization would require the negotiation of disciplinary boundaries and territories. I instead concluded that doctoral students in an interdisciplinary doctoral program shared many of the same socialization experiences as their peers in disciplinary doctoral programs. This conclusion is similar to that of Lattuca (2001) in her study of the conceptions of interdisciplinarity based on faculty engaged in such work. “The processes by which [individuals] do interdisciplinary work greatly resemble the processes by which they do disciplinary work,” Lattuca wrote (p. 250). “Differences often amount to variations on a theme rather than distinctive ways of accomplishing academic work.” Doctoral students enrolled in the interdisciplinary neuroscience program at Glenhaven based on their previous undergraduate or professional experience in the sciences. They felt that the program was best structured to allow them to pursue their particular interests. The students entered as a cohort; progressed through a short series of required courses; completed comprehensive/qualifying examinations and a dissertation; and served as research/teaching assistants with a faculty advisor. They attended professional conferences; some students worked with their advisor and colleagues on papers which were submitted to academic journals. Issues of financial support, the balance between professional and personal lives, and the development of
201 scientific proficiency were all highly salient for these students. Often students struggled to explain their research to those outside the institution, including family and friends. They expressed great concern over their future, debating the requirements for a faculty career or an industry position. The doctoral students in this study identified with themes widely agreed upon in the literature regarding graduate student experiences, including a lack of systematic advising and mentoring, multiple and conflicting messages, concerns about academic life, lack of systematic preparation for a full array of professional responsibilities, lack of adequate knowledge of (and preparation for) diverse career choices, and infrequent opportunities for guided, purposeful reflection (Austin, 2002b). Table 6 (adapted in part from Weidman, Twale, and Stein, 2001) compares components of disciplinary and interdisciplinary doctoral student socialization organized by the themes presented earlier in this chapter: knowledge acquisition, identity development, and community/disciplinary integration. I draw on characteristics of disciplinary doctorates presented by Weidman et al. (2001). (Considering the different characteristics exhibited by disciplinary knowledge outlined in chapter two, and the focus of this dissertation on doctoral student experiences in the sciences, it is important to note that this comparative graphic refers to disciplinary doctoral programs in the sciences as opposed to fields in the social sciences, humanities, and professions.)
202 Table 6: Disciplinary/interdisciplinary doctoral student socialization Structural element
Department/Program
Disciplinary science doctoral
Interdisciplinary science
programs
doctoral programs
Academic role learning,
In addition: Expose students to
research competence
the breadth of the field (knowledge/research techniques), support mastery of depth
Faculty functions
Sort and select by entrance
In addition: Expose students to
exams and rigorous standards,
foundations of constituent
role is less formal and more
disciplines
advisory; relationships vary Curriculum
Immersion into the discipline
Introduction to breadth of the
and academe, research model
field, immersion into area of research interest, largely individualized curriculum
Student autonomy
Student peer culture
Mostly assistantships,
Mostly assistantships,
supervised as research assistant
supervised as research assistant
Formal full-time cohorts
In addition: Student can also become integrated into peer culture of constituent discipline
Professionalization
Role models and mentors in
Different: Faculty role models
academe, academic rigor, meet
can be difficult to locate;
faculty standards
faculty can encourage collaborative research
203 Three questions guided this dissertation. I briefly respond to each question, and then draw conclusions from their implications. 1) How do doctoral students in an interdisciplinary program define their professional identity? 2) How do these doctoral students navigate disciplinary cultures to engage in interdisciplinary scholarship? 3) What skills, beliefs, and attitudes does interdisciplinary work in a doctoral program foster? Identity: I anticipated that doctoral students in an interdisciplinary program would struggle to concurrently hold dual identities, both as a neuroscientist and as a member of a relevant constituent discipline. However, this dilemma was salient for a very small number of individuals. Most of the doctoral neuroscience students at Glenhaven created identities related to their research interest, academic experience, and disciplinary background that spanned disciplinary boundaries. Students seemed less concerned over where such identities might fit in terms of a disciplinary community, and more aware of their general development as a scientist. For these students, disciplinary boundaries have been extensively blurred. An important caveat should be made, however—while doctoral students at Glenhaven reflected a deconstruction of disciplinary boundaries in terms of knowledge and scientific research, they were concerned about the persistent disciplinary culture of the academic institution.
204 Disciplinary culture and interdisciplinary development: Many students were unsure how an interdisciplinary career in neuroscience should be conceptualized and how their degree would prepare them for their first professional positions. These concerns were related to skills and training gained during the program, and how such knowledge would be applied after graduation. How would their symbolic identity as an interdisciplinary neuroscientist fit within the disciplinary structure of the university? Not all students were optimistic that an interdisciplinary doctoral degree in neuroscience would have positive professional outcomes. Such fears were a recurring topic during my interviews with students. Many shared Jason’s attitude. Jason, who I introduced in the opening of this chapter, made drastic decisions in terms of his enrollment and duration in graduate school based on his perception of the marketability of a neuroscience degree and his individual skills. In chapter two, I outlined two types of interdisciplinary socialization: one, where individuals receive a disciplinary doctorate and engage in interdisciplinary research over the course of their career; and two, where the doctoral program is structured as an interdisciplinary education. As some students noted, the lack of faculty role models who engaged in an interdisciplinary doctoral program can be discouraging. Skills, beliefs, and attitudes fostered through interdisciplinarity: The outcomes of academic work are related to academic benefits, such as tenure and promotion; professional contributions, such as books, conference papers, or research; and intellectual advantages, such as new epistemologies or research techniques
205 (Lattuca, 2001). Doctoral students working in an interdisciplinary area of inquiry are particularly concerned with academic rewards and professional contributions, as both relate to the disciplinary norm of the academic community. Several positive intellectual outcomes were identified by students, including the ability and expertise to draw on the strengths of multiple disciplines in knowledge production; the ability to assemble new areas of knowledge and research based on individual interests; and the interdisciplinary connections to a broad range of other brain researchers. Students largely felt prepared to work as part of a collaborative research effort related to neuroscience. In addition, participation in an interdisciplinary doctoral program often changed students’ perspective of the disciplines. Students gradually achieved a new perspective on the knowledge they gained as an undergraduate. I return to a distinction I first made in chapter two regarding the individual interpretation of culture. Berger and Luckmann summarized the social construction of reality thusly: “Everyday life presents itself as a reality interpreted by [wo]men and subjectively meaningful to them as a coherent world” (1966, p. 19). Individuals may therefore define, prioritize, and invoke multiple identities during social engagement. For example, I played multiple roles during the data collection, analysis, and writing of this dissertation: graduate student, educational researcher, author, interviewer, and non-neuroscientist, among others. The students also invoked multiple identities during our interactions. This relationship between subjective, social construction and personal identity is particularly relevant to understanding
206 how doctoral students define themselves as members of the academic community. Identity emerges from the interaction between the individual and society; in the case of this dissertation, between doctoral students and the university, more specifically the neuroscience program. In relation to doctoral student identity development, the university exists as a social construction. Students experience unique interpretations and interactions with the university culture that shape the perception of their identity. Rather than a struggle to simultaneously hold dual (and sometimes conflicting) identities, the doctoral students in this dissertation described the negotiation of shifting cultures and discourse: amassing, comprehending, and demonstrating the requisite knowledge and skills needed for a range of role performances, performances that change over time. The challenge of an interdisciplinary field such as neuroscience is the acquisition of language, skills, and techniques necessary for membership in the interdisciplinary community, but also the maintenance of connections to the nearest constituent discipline (Hall, 2004; Hyman, 2004). This awareness enables doctoral students to navigate the shifting cultures and discourse. I previously noted that knowledge, language, and discourse give value to those individuals that hold them—individuals may express a claim to community membership based on these factors. Consider the example of Glenhaven doctoral students who attended multiple professional conferences. Some students noted that they felt excluded from the Society for Neuroscience conference; they could not understand in any real depth the content of posters or papers presented. Other
207 students claimed that they felt more comfortable at smaller conferences with a strictly defined focus relevant to their research. Students noted that not only did their research agenda determine which conferences they would attend, but also their faculty advisor. Disciplinary identities are created in part by culture and knowledge shared between multiple individuals. In this regard, culture is a narrative that can be continually negotiated as individuals define their personal role in the community. Interdisciplinary identities are formed through a similar process. The conflict that emerged in regards to interdisciplinary socialization for doctoral students was often the conflict between the disciplinary structure of the university, the constructed nature of knowledge, and the personal development of identity which occurs during graduate education. Limitations of study Forty neuroscience students were interviewed for this study. During this dissertation’s eight-month timespan, the figure represented approximately half of the total number of doctoral neuroscience students enrolled at Glenhaven. Although the number of years a student had been enrolled in the program was a consideration during the research design, 25 students who participated in this study (63%) were in their first three years of the program. An additional seven students (18%) were in year four. Those students who were in year five and beyond (preparing a dissertation, primarily engaged in laboratory research, and searching for a professional position after graduation) provided different narratives than students in the first few years of
208 graduate study. I interviewed three students who had recently graduated from the program. The inclusion of more recent graduates as well as a longitudinal analysis of students enrolled in the program would likely have provided different perspectives than those presented here. (A list of students interviewed and named in this dissertation, their year in the program and their research interests is included in the appendix.) A more inherent limitation of this dissertation resulted from my decision to solely interview doctoral students and faculty in an interdisciplinary neuroscience program. I did not do a complementary study of students and faculty in a traditional disciplinary program. As I outlined in chapter two, interdisciplinarity is generally understood in relationship to the disciplines. “There is an inherent paradox when talking about interdisciplinarity,” concluded Klein (1990, p. 77). “Our vocabulary— indeed, our entire logic of classification—predisposes us to think in terms of disciplinarity.” While a direct comparison between a doctoral student in biology, for example, and a student from Glenhaven’s interdisciplinary neuroscience program would not necessarily have been valid, a dual case study could have provided compelling areas for analysis. Instead of conducting a complementary study of the disciplines as an area of comparison, however, I organized the theoretical framework for this dissertation as a disciplinary understanding of socialization; that is, previous research on doctoral student socialization has almost exclusively concentrated on disciplinary doctorates. Future research should explore this inherent relationship
209 between disciplinary and interdisciplinarity. I now turn to a discussion of future directions for research in terms of the doctoral student experience, doctoral student socialization, and the construction of interdisciplinary knowledge. Future directions for research Universities, federal agencies, and foundations have increasingly encouraged interdisciplinary research and knowledge production as a response to the complexity of social problems. Caruso and Rhoten concluded, “Leading scientists and bureaucrats state unequivocally that the challenges and stimulation of struggling to exchange ideas with people from other disciplines will lead to major scientific breakthroughs and increase our knowledge of the world” (2001, p. 2). Caruso and Rhoten further outline what has been the major topics of research regarding interdisciplinarity, including 1) the influence of institutional bias towards the disciplines; 2) the struggle to define interdisciplinary success using disciplinary terminology; 3) questions of how to achieve consensus and common understanding regarding complex topics; and 4) the problem of shared resources, funding, and dissemination. My dissertation has contributed to this growing body of literature by outlining how doctoral students are trained as interdisciplinary scientists within the disciplinary culture of the university. My research design was influenced by the goal of understanding the cultural construction of interdisciplinarity from the perspective of doctoral students. In this section, I offer three guidelines for future research
210 regarding interdisciplinarity, knowledge production, and doctoral student socialization. Undertake longitudinal studies I have presented a case study, consisting of 40 student narratives, complemented by faculty interviews, observations, and relevant document analysis. The data collection occurred over an eight-month span, a specific period of time in the lives of these students and the program. I argued throughout this chapter that all knowledge is contextual, bound in a specific time and place. The data contained here reflects those same conditions. Additional longitudinal data would provide a more complete understanding not only of how interdisciplinary doctoral students develop over the course of their program, but also their career development as interdisciplinary scientists. Where will the students profiled in this dissertation assume their first professional positions? What are the implications of their training as an interdisciplinary researcher in an academic culture structured by the disciplines? What industry positions will they assume? Given their interdisciplinary training, how will their future research agenda change? And what factors will change it? Such questions are, of course, situated in the larger context of postsecondary education (How will academic restructuring affect degree programming and knowledge production within the university?) as well as society (How will such scientific innovations as stem cell research and treatments for neurodegenerative brain diseases affect the ways in which we train doctoral students?). In addition, as I
211 previously noted, collecting such data from doctoral students in both interdisciplinary and disciplinary science programs could provide a more holistic perspective and provide for greater understanding of the challenges facing all scientists. Design research projects with collaborative investigators In chapter three, I discussed how my position as a social science researcher and doctoral student in education influenced the data collection and analysis in this study. I reiterate my conclusion—scientific expertise is not a necessary prerequisite for understanding the work of scientists. It is important to note, however, that while I did not share the student’s expertise in specific bodies of knowledge, I did preliminary reading regarding neuroscience to ensure that my questions were informed and relevant to student experiences. In general, students provided rich and detailed information when I asked them to explain their work to me. Excited to share their work with an outsider, most of their students were concerned with my comprehension, and patiently reiterated responses regarding complex theoretical foundations and scientific techniques. These students were excited about sharing their emergent expertise. As an expert, the ability to explain one’s work to others outside of the field of research is crucial. Interdisciplinarity, the production of scientific knowledge, and the training of scientists is a focus of research and programmatic activity at multiple levels. Organizations from the social and natural sciences have focused on these areas in
212 recent collaborative work. For example, the Higher Education Research Program at the Social Science Research Council examines “innovative, interdisciplinary, and integrative—or I3—approaches to graduate training” (SSRC, 2005). The goal of the SSRC research program is to provide empirical data on a broad scale to study the conditions, processes, and outcomes of I3 programs. Such research is needed to determine the theoretical foundation for training graduate students in interdisciplinary programs. Early work by the I3 program supports one of the conclusions of this dissertation, that “many [students] still feel the tension between the scientific promise of the interdisciplinary path and the academic prospect of the tenure track” (Rhoten & Parker, 2004, p. 2046). In addition, the Carnegie Initiative on the Doctorate named neuroscience as one of its six disciplines for study. While the CID does not explicitly focus on interdisciplinarity and knowledge production, the program does examine how doctoral students are socialized into the profession of their various areas of study. The National Science Foundation funds the Integrative Graduate Education and Research Traineeship Program (IGERT), which supports interdisciplinary training for graduate students in the sciences and engineering. According to the NSF, “The program is intended to catalyze a cultural change in graduate education, for students, faculty, and institutions, by establishing innovative new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries” (NSF, 2006). Each of these examples illustrates how collaborative methodologies can
213 enhance research design and our understanding of interdisciplinarity and doctoral student socialization. The examples also demonstrate the array of individuals, foundations, and government agencies studying interdisciplinarity and the doctoral student experience. More collaborative research should be undertaken on a broad scale to understand doctoral student development related to interdisciplinary programs. Expand the framework of socialization Socialization theory has been commonly employed by researchers in recent decades to understand doctoral student development. Antony summarized, “Any discussion about what students need to know speaks to closely held conceptions about how doctoral students should be professionally developed or socialized” (2002, p. 350). Theories of socialization conceptualize how the organization shapes an individual’s decision-making, behavior, and development. As a theoretical framework to understanding the development of faculty (Tierney & Bensimon, 1996), medical doctors (Becker, Geer, Hughes, & Strauss, 1963; Hafferty, 1991), lawyers (Guinier, Fine, & Balin, 1997), and other professionals (Van Maanen & Schein, 1979), the value of socialization theory has been documented across multiple topics. I found socialization theory to be a useful foundation for understanding doctoral student experiences in an interdisciplinary program. However, such theory is limited in its ability to determine the influence of groups external to the university on student development. For example, during the writing of this dissertation,
214 California voters approved Proposition 71 (the so-called Stem Cell Initiative) that allocated $3 billion in tax-free state bonds to the development of embryonic stem cell research. Although the funding has been stalled by several lawsuits, researchers at California’s colleges and universities stand to receive up to $295 million a year to study cell colonies developed from five-day old human embryos. Due to the potential of stem cell research to investigate issues of aging, neural degeneration, and human disease, neuroscience as a field of inquiry is directly influenced by Proposition 71 and the public debate regarding stem cells. Several students mentioned the possible impact of stem cell research during our interviews, and reflected on how such advances would affect their career. By expanding the framework of socialization, researchers can more adequately theorize about such relationships between the public, policy organizations, and the academic institution, and how such relationships might impact the development of doctoral students in the sciences. Conclusion The objective of Ph.D. programs—to train future scholars and researchers within the disciplines or professions—is increasingly faulted for fostering intellectual depth at the expense of breadth. Working as part of collaborative research teams, producing interdisciplinary knowledge, and integrating theory and practice are perceived to be necessary responses to the escalating import of globalization and social change (Etzkowitz & Leydesdorff, 2000; Nowotny, Scott, & Gibbons, 2001). “The specialization of the degree raises concern, particularly when there is a
215 simultaneous need for greater connectedness among scholars,” concluded Wulff and Austin (2004, p. 286). Social problems cross disciplinary boundaries, requiring researchers to engage in broad, interdisciplinary work. In this study, I sought to understand the process of doctoral student socialization in an interdisciplinary neuroscience program. My goal in this dissertation has been to determine how doctoral students interpret and navigate the culture of an interdisciplinary neuroscience program, and to outline what effect such experience has on the socialization process. Interdisciplinary scholars continually negotiate between multiple identities: their symbolic identity (here, as a neuroscientist), their disciplinary identity, and their multidisciplinary identity. Identities are invoked as a response to the university culture and perception of disciplinary boundaries. The picture of interdisciplinary work presented in this dissertation reveals the ambiguity of disciplinary boundaries and the significance of defining multiple identities as one foundation of socialization.
216 REFERENCES Afifi, A., & Bergman, R. (1998). Functional neuroanatomy: Text and atlas. New York: McGraw-Hill. Alexander, J. (2003). The meanings of social life: A cultural sociology. Oxford: Oxford University Press. Anderson, M. (Ed.) (1998). The experience of being in graduate school: An exploration. New Directions for Higher Education, 101. San Francisco: Jossey-Bass. Angrosino, M. (2005). Recontextualizing observation: Ethnography, pedagogy, and the prospects for a progressive political agenda. In N. Denzin and Y. Lincoln (Eds.), The handbook of qualitative research (3rd ed.) (pp. 729-746). Thousand Oaks: Sage Publications. Antony, J. (2002). Reexamining doctoral student socialization and professional development: Moving beyond the congruence and assimilation orientation. In J. Smart (Ed.), Handbook of theory and research, Vol. XVII (pp. 349-380). New York: Agathon Press. Apostel, L., Berger, C., Briggs, A., & Michaud, G. (Eds.) (1972). Interdisciplinarity: Problems of teaching and research in universities. Nice, France: Centre for Educational Research and Innovation, Organisation for Economic Cooperation and Development. Aram, J. (2004). Concepts of interdisciplinarity: Configurations of knowledge and action. Human Relations, 57(4), 379-412. Association of Neuroscience Departments and Programs (ANDP) (2003). Survey of neuroscience graduate, postdoctoral, & undergraduate programs. Retrieved November 4, 2005 from: http://www.andp.org/surveys/reports/2003/survey03report.pdf Atkinson, P., & Coffey, A. (2002). Revisiting the relationship between participant observation and interviewing. Handbook of interview research: Context & method (pp. 801-814). Thousand Oaks, CA: Sage Publications.
217 Austin, A. (1990). Faculty cultures, faculty values. In W. Tierney (Ed.), Assessing academic climates and cultures. New Directions in Institutional Research, No. 68. (pp. 61-74). San Francisco: Jossey-Bass. Austin, A. (2002a). Assessing doctoral students’ progress along developmental dimensions. Paper presented at the annual meeting of the Association for the Study of Higher Education, Sacramento, CA. Austin, A. (2002b). Preparing the next generation: Graduate school as socialization to the academic career. The Journal of Higher Education, 73(1), 94-122. Bair, C. (1999). Doctoral student attrition and persistence: A meta-synthesis. Unpublished doctoral dissertation, Loyola University (Chicago). Bair, C., Haworth, J., & Sandfort, M. (2004). Doctoral student learning and development: A shared responsibility. NASPSA Journal, (41)3, 709-727. Baxter Magolda, M. B. (1992). Knowing and reasoning in college: Gender related patterns in students’ intellectual development. San Francisco, CA: JosseyBass. Beauchamp, M. (2002). Functional MRI for beginners (Review). Nature Neuroscience, 5(5):397-398. Becher, T. (1987). Disciplinary discourse. Studies in Higher Education, 12(3), 261274. Becher, T. (1990). The counter-culture of specialization. European Journal of Education, 25(3), 333-346. Becher, T., & Trowler, P. (2001). Academic tribes and territories: Intellectual enquiry and the culture of the disciplines (2nd ed). Buckingham: Society for Research into Higher Education and Open University Press. Becker, H. (1970). Sociological work: Method and substance. Chicago: Adline Publishing. Becker, H. (1984). Art worlds. Berkeley: University of California Press. Becker, H., & Strauss, A. (1956). Careers, personality, and adult socialization. American Journal of Sociology, 62, 253-263.
218 Becker, H., & Geer, B. (1958). The fate of idealism in medical school. American Sociological Review, 28, 50-56. Becker, H., Geer, B., Hughes, E., & Strauss, E. (1961). Boys in white: Student culture in medical school. Chicago: University of Chicago Press. Behar, R., & Gordon, D. (Eds.) (1995). Women writing culture. Berkeley: University of California Press. Berg, B. (1995). Qualitative research methods for the social sciences. Needham Heights, MA: Allyn and Bacon. Berger, P., & Luckmann, T. (1966). The social construction of reality: A treatise in the sociology of knowledge. Garden City, NY: Anchor Books. Bess, J. (1978). Anticipatory socialization of graduate students. Research in Higher Education, 8(4), 289-317. Biglan, A. (1973). The characteristics of subject matter in different academic areas. Journal of Applied Psychology, 57, 195-203. Blau, P. (1955). The dynamics of bureaucracy. Chicago: The University of Chicago Press. Bourdieu, P. (1977). Cultural reproduction and social reproduction. In J. Karabel and A. Halsey (Eds.), Power and ideology in education (pp. 487-511). New York: Oxford University Press. Bourdieu, P. (1986). The forms of capital. In J. Richardson (Ed.), Handbook of theory and research for the sociology of education (pp. 241-258). New York: Greenwood Press. Bowen, W., & Rudenstine, N. (1992). In pursuit of the Ph.D. Princeton: Princeton University Press. Bragg, A. (1976). The socialization process in higher education. Washington, DC: American Association for Higher Education. (ERIC-AAHE Research Report 76-7) Braxton, J., & Hargens, L. (1996). Variation among academic disciplines: Analytical frameworks and research. In J. Smart (Ed.), The handbook of theory and research in higher education (pp. 1-46). New York: Agathon Press.
219
Brim, O., & Wheeler, S. (1966). Socialization after childhood: Two essays. New York: John Wiley and Sons. Bruss, K. V., & Kopala, M. (1993). Graduate school training in psychology: Its impact upon the development of professional identity. Psychotherapy, 30, 685–691. Campbell, R. (2003). Preparing the next generation of scientists: The social process of managing students. Social Studies of Science, 33(6), 897-927. Carnegie Foundation for the Advancement of Teaching (1989). Survey among colleges and university faculty. New Jersey: The Wirthlin Group. Carnegie Initiative on the Doctorate (2005). Preparing stewards of the discipline. Retrieved November 29, 2005 from http://www.carnegiefoundation.org/master/sub.asp?key=29&subkey=473 Caruso, D., & Rhoten, D. (2001). Lead, follow, get out of the way: Sidestepping barriers to the effective practice of interdisciplinarity. White paper published by the Hybrid Vigor Institute. Retrieved December 3, 2004 from http://www.hybridvigor.net/interdis/pubs/hv_pub_interdis-2001.04.30.pdf Clark, B. (1983). The higher education system: Academic organization in a crossnational perspective. Berkeley: University of California Press. Clarke, A. (1991). Social worlds/arenas theory as organizational theory. In D. Maines (Ed.), Social organization and social process: Essays in honor of Anselm Strauss (pp. 119-158). New York: Aldine de Gruyter. Coffey, A., Holbrook, B., & Atkinson, P. (1996). Qualitative data analysis: Technologies and representations. Sociological Research Online, 1(1), http://www.socresonline.org.uk/socresonline/1/1/4.html Cornell, S. (2000). That’s the story of our life. In P.R. Spickard and W.J. Burroughs (Eds.), Narrative and multiplicity in constructing ethnic identities (pp. 41–53). Philadelphia, PA: Temple University Press. COSEPUP (Committee on Science, Engineering, and Public Policy) (1995). Reshaping the graduate education of scientists and engineers. Washington, DC: National Academy Press.
220 Cresswell, J. (1994). Research design: Qualitative and quantitative approaches. Thousand Oaks: Sage Publications. Daresh, J., & Playko, M. (1995). Alternative career formation perspectives: Lessons for educational leadership from law, medicine, and training for the priesthood. Paper presented at the annual conference of the University Council for Educational Administration, Salt Lake City, UT. Delamont, S., Parry, I., & Atkinson, P. (1999). The doctoral experience: Disciplines, disciples, and the doctorate. London: Routledge UK. Delamont, S., & Atkinson, P. (2001). Doctoring uncertainty: Mastering craft knowledge. Social Studies of Science, 31(1), 87-107. Delkeskamp, C. (1977). Interdisciplinarity: A critical appraisal. In H. Englehardt and D. Callahan (Eds.), The foundation of ethics and its relationship to science (Vol. 2) (pp. 324-354). New York: Hastings Center. Denison, D. (1996). What is the difference between organizational culture and organizational climate? A native’s point of view on a decade of paradigm wars. Academy of Management Review, 21, 619-654. Dolan, J., Kropf, M., O’Connor, K., & Ezra, M. (1997). The future of our discipline: The status of doctoral students in political science. PS: Political Science & Politics, 751-756. Dumont, J.P. (1992). Visayan vignettes: Ethnographic traces of a Philippine island. Chicago: University of Chicago Press. Eisenhart, M., & Howe, K. (1992). Validity in educational research. In W.M. LeCompte, W. Millroy, and J. Preissle (Eds.), Handbook of qualitative research in education (pp. 643-680). San Diego: Academic Press. Emerson, R., Fretz, R., & Shaw, L. (1995). Writing ethnographic fieldnotes. Chicago: University of Chicago Press. Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: From national systems and “mode 2” to the triple helix of university-industry-government relations. Research Policy, 29(2), 313-330. Fielding, N., & Lee, M. (2002). New patterns in the adaptation and use of qualitative software. Field Methods, 14(2), 197-216.
221 Fisher, D. (1993). Fundamental development of the social sciences: Rockefeller philanthropy and the United States Social Science Research Council. Ann Arbor: University of Michigan Press. Fontana, A., & Frey, J. (2005). The interview: From neutral stance to political involvement. In N. Denzin and Y. Lincoln (Eds.), The handbook of qualitative research (3rd ed.) (pp. 695-728). Thousand Oaks: Sage Publications. Foucault, M. (1970).The order of things: An archaeology of the human sciences. London: Routledge. Fry, J. (2004). The cultural shaping of ICTs within academic fields: Corpus-based linguistics as a case study. Linguistics and Linguistic Computing, 19(3), 303319. Geertz, C. (1973). The interpretation of culture. New York: Basic Books. Gerholm, T. (1990). On tacit knowledge in academia. European Journal of Education, 25(3), 263-271. Girves, J. E., & Wemmerus, V. (1988). Developing models of graduate student degree progress. Journal of Higher Education, 59(2), 163-189. Golde, C. (1996). How departmental contextual factors shape doctoral student attrition. Unpublished doctoral dissertation, Stanford University. Golde, C. (2000). Should I stay or should I go? Student descriptions of the doctoral attrition process. The Review of Higher Education, 23(2), 199-227. Golde, C., & Gallagher, H. (1999). The challenges of conducting interdisciplinary research in traditional doctoral programs. Ecosystems, 2(4), 281-285. Golde, C., & Dore, T. M. (2001). At cross purposes: What the experiences of doctoral students reveal about doctoral education. Retrieved November 1, 2004 from http://www.phd-survey.org Gottlieb, D. (1961). Processes of socialization in American graduate schools. Social Forces, 40, 124-131.
222 Guba, E., & Lincoln, Y. (2005). Paradigmatic controversies, contradictions, and emerging confluences. In N. Denzin and Y. Lincoln (Eds.), The handbook of qualitative research (3rd ed.) (pp. 191-216). Thousand Oaks: Sage Publications. Guinier, L., Fine, M., & Balin, J. (1997). Becoming gentlemen: Women, law school, and institutional change. Boston: Beacon Press. Hacking, I. (1992). The self-vindication of the laboratory sciences. In A. Pickering (Ed.), Science as practice and culture (pp. 29-64). Chicago: The University of Chicago Press. Hafferty, F. (1991). Into the valley: Death and the socialization of medical students. New Haven: Yale University Press. Hall, Z. (2004). Graduate education in neuroscience: Maintaining through change. Menlo Park, CA: The Carnegie Initiative on the Doctorate, The Carnegie Foundation. Harding, S. (1991). Whose science? Whose knowledge? Thinking from women’s lives. Ithaca, NY: Cornell University Press. Harris, R., Giard, J., & Pijawka, D. (2003). Interdisciplinary doctoral education in environmental design: Assessment of programs, issues, structure, and vision. Paper presented at the 3rd Annual Conference on Doctoral Education in Design. Retrieved November 4, 2005 from http://www.idemployee.id.tue.nl/g.w.m.rauterberg/conferences/CD_doNotOp en/DED/d_final_paper/d_04.pdf Holstein, J., & Gubrium, J. (1995). The active interview. Thousand Oaks, CA: Sage Publications. Hutchings, P., & Clarke, S. (2004). The scholarship of teaching and learning: Contributing to reform in graduate education. In D. Wulff and A. Austin (Eds.), Paths to the professoriate: Strategies for enriching the preparation of future faculty (pp. 161-176). San Francisco, CA: Jossey Bass. Hyman, S. (2004). Neuroscience and the doctorate: The challenges of multidisciplinarity. Menlo Park, CA: The Carnegie Initiative on the Doctorate, The Carnegie Foundation.
223 Jarvinen, M. (2000). The biographical illusion: Constructing meaning in qualitative interviews. Qualitative Inquiry, 6(3), 370-391. Johnson, B., & Harvey, W. (2002). The socialization of black college faculty: Implications for policy and practice. Review of Higher Education, 25(3), 297314. Kandel, E., & Squire, L. (2001). Neuroscience: Breaking down scientific barriers to study brain and mind. Annals of the New York Academy of Science, 935, 118135. Katz, J., & Hartnett, R. T. (Eds.). (1976). Scholars in the making: The development of graduate and professional students. Cambridge, MA: Ballinger. Klein, J. (1990). Interdisciplinarity. Detroit: Wayne State University Press. Klein, J. (1996). Crossing boundaries: Knowledge, disciplinarities, and interdisciplinarities. Charlottesville: University of Virginia Press. Knorr Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Cambridge: Harvard University Press. Kockelmans, J. (Ed.) (1979). Interdisciplinarity and higher education. University Park, PA: Pennsylvania State University Press. Koschmann, T., Kelson, A. C., Feltovich, P. J., & Barrows, H. S. (1996). Computersupported problem-based learning: A principled approach to the use of computers in collaborative learning. In T. Koschmann (Ed.), CSCL: Theory & Practice in an Emerging Paradigm (pp. 83-124). Hillsdale, NJ: Lawrence Erlbaum. Kuhn, T. (1996/1962). The structure of scientific revolutions (3rd ed.). Chicago: University of Chicago Press. Labinger, J., & Collins, H. (2001). The one culture? A conversation about science. Chicago: University of Chicago Press. Latour, B. & Woolgar, S. (1979) Laboratory life: The construction of scientific facts. Princeton: Princeton University Press. Lattuca, L. (1996). Envisioning interdisciplinarity: Processes, contexts, and outcomes. Unpublished doctoral dissertation, University of Michigan.
224 Lattuca, L. (2001). Creating interdisciplinarity: Interdisciplinary research and teaching among college and university faculty. Nashville: Vanderbilt University Press. Lattuca, L. (2003). Creating interdisciplinarity: Grounded definitions from college and university faculty. History of Intellectual Culture, 3(1). Available online from: http://www.ucalgary.ca/hic/website/toc/tableofcontentsvol3.htm Lenoir, T. (1997). Instituting science. Palo Alto, CA: Stanford University Press. Lincoln, Y. (2001). Varieties of validity: Quality in qualitative research. In J. Smart (Ed.), Higher education: Handbook of theory and research XVI (pp. 25-72). New York: Agathon Press. Lindholm, J. (2003). Perceived organizational fit: Nurturing the minds, hearts, and personal ambitions of university faculty. The Review of Higher Education, 27(1), 125-149. Lortie, D. (1975). Schoolteacher: A sociological study. Chicago: University of Chicago Press. Lovitts, B. (2001). Leaving the ivory tower: The causes and consequences of graduate school attrition. Lanham, MD: Rowman & Littlefield. Mansilla, V. (2005). Assessing student work at disciplinary crossroads. Change, 37(1), 14-21. Mansilla, V., & Gardner, H. (2003). Assessing interdisciplinary work at the frontier: An empirical exploration of ‘symptoms of quality.’ Retrieved November 29, 2005 from http://www.interdisciplines.org/interdisciplinarity/papers/6 Marshall, C., & Rossman, G. (1999). Designing qualitative research (3rd ed). Thousand Oaks: Sage Publications. Massey, D. (1999). Negotiating disciplinary boundaries. Current Sociology, 47(4), 512. Merriam, S. (1998). Qualitative research and case study applications in education. San Francisco: Jossey Bass. Merton, R. (1957). Social theory and social structure. Glencoe, IL: Free Press.
225 Merton, R., Reader, G., & Kendall, P. (Eds.) (1957). The student physician. Cambridge, MA: Harvard University Press. Mervis, J. (2005). Biocomplexity blooms in NSF’s research garden. Science, 286(5447), 2068-2069. Messer-Davidow, E., Shumway, D., & Sylvan, D. (Eds.) (1993). Knowledges: Historical and critical studies in disciplinarity. Charlottesville: University of Virginia Press. Mishler, E. (1979). Meaning in context: Is there any other kind? Harvard Educational Review, 49, 1-19. Mourad, R. (1997). Postmodern philosophical critique and the pursuit of knowledge in higher education. Westport, CT: Bergin & Garvey. Nahapiet, J., & Ghosal, S. (1998). Social capital, intellectual capital, and the organizational advantage. The Academy of Management Review, 23(2), 242266. National Science Foundation (2006). Integrative graduate education and traineeship program: Call for proposals. Retrieved February 2, 2006 from http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=12759&from=fund Neumann, R. (2001). Disciplinary differences and university teaching. Studies in Higher Education, 26(2), 135-146. Neumann, R., & Becher, T. (2002). Teaching and learning in their disciplinary contexts: A conceptual analysis. Studies in Higher Education, 27(4), 405417. Newell, W. (Ed.) (1998). Interdisciplinarity: Essays from the literature. New York: College Entrance Examination Board. Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. New York: Oxford University Press. Nowotny, H., Scott, P., & Gibbons, M. (2001). Re-thinking science: Knowledge and the public in an age of uncertainty. Cambridge: Polity Press.
226 Nyquist, J., Manning, L., Wulff, D., Austin, A., Sprague, J., & Fraser, P. (1999). On the road to becoming a professor. Change, 31(3), 18-27. Nyquist, J., & Woodford, B. (2000). Re-envisioning the Ph.D.: What concerns do we have? Seattle, WA: University of Washington, Center for Instructional Development and Research. Olesen, V. (2005). Early millennial feminist qualitative research: Challenges and contours. In N. Denzin and Y. Lincoln (Eds.), The handbook of qualitative research (3rd ed.) (pp. 235-278). Thousand Oaks: Sage Publications. Palmer, C. (1999). Structures and strategies of interdisciplinary science. Journal of the American Society for Information Science, 50(3), 242-253. Palmer, C. (2001). Work at the boundaries of science: Information and the interdisciplinary research process. Dordrecht: Kluwer. Pantin, C. (1968). The relations between the sciences. Cambridge: Cambridge University Press. Parsons, T. (1951). The social system. New York: Free Press. Peshkin, A. (2001). Angles of vision: Enhancing perception in qualitative research. Qualitative Inquiry, 7(2), 238-253. Pickering, A. (Ed.) (1992). Science as practice and culture. Chicago: The University of Chicago Press. Pillow, W. (2003) Confession, catharsis, or cure? Rethinking the uses of reflexivity as methodological power in qualitative research, Qualitative Studies in Education, 16(2), 175–96. Pinch, T. (2001). Do science studies undermine science? Wittgenstein, Turing, and Polanyi as precursors for science studies and the science wars. In J. Labinger and H. Collins (Eds.), The one culture? A conversation about science (pp. 1326). Chicago: The University of Chicago Press. Polkinghorne, D. (2005). Language and meaning: Data collection in qualitative research. Journal of Counseling Psychology, 52(2), 137-145. Reinharz, S. (1979). On becoming a social scientist. San Francisco: Jossey-Bass.
227 Reis, R. (2000, September 29). Interdisciplinary research and your scientific career. The Chronicle of Higher Education. Available online: http://chronicle.com/jobs/2000/09/2000092903c.htm Rhoten, D., & Parker, A. (2004). Risks and rewards of an interdisciplinary research path. Science, 306(5704), 2046. Rorty, R. (1998). Truth and progress: Philosophical papers (Volume Three). Cambridge: Cambridge University Press. Rosaldo, R (1989). Culture and truth: The remaking of social analysis. Boston: Beacon Press. Rosch, T., & Reich, J. (1996). The enculturation of new faculty in higher education: A comparative investigation of three academic departments. Research in Higher Education, 37(1), 115-131. Rosen, B., & Bates, A. (1967). The structures of socialization in graduate school. Sociological Inquiry, 37, 71-84. Ross, A. (Ed.) (1996). The science wars. Durham, NC: Duke University Press. Rossini, A., & Porter, F. (1985). Peer review of interdisciplinary research proposals. Science, Technology, and Human Values, 10(3), 33-38. Rubin, H., & Rubin, I. (1995). Qualitative interviewing: The art of hearing data. Thousand Oaks, CA: Sage Publications. Schwandt, T. (1997). Qualitative inquiry. Thousand Oaks: Sage Publications. Shapin, S. (1996). The scientific revolution. Chicago: University of Chicago Press. Social Science Research Council (2005). Integrative, interdisciplinary graduate education: New concepts for assessment. Retrieved December 7, 2005 from http://www.ssrc.org/programs/knowledge/higher_ed/grad_ed/ Society for Neuroscience (2004). About SfN. Retrieved December 2, 2004 from http://web.sfn.org/Template.cfm?Section=AboutSFN Society for Neuroscience (2005). Association of neuroscience departments and programs: Neuroscience training programs. Retrieved November 29, 2005 from http://www.andp.org/programs/programs.htm
228 Spillman, L. (2002). Introduction: Culture and cultural sociology. In L. Spillman (Ed.), Cultural sociology (pp. 1-16). Malden, MA: Blackwell Publishers. Spradley, J. (1979). The ethnographic interview. New York: Holt, Rinehart, and Winston. Tierney, W. (1991). Academic work and institutional culture: Constructing knowledge. Review of Higher Education, 14(2), 199-216. Tierney, W. (1997). Organizational socialization in higher education. The Journal of Higher Education, 68(1), 1-16. Tierney, W., & Rhoads, R. (1994). Faculty socialization as cultural process: A mirror of institutional commitment. Washington, DC: The George Washington University. (ASHE-ERIC Higher Education Report No. 93-6) Tierney, W., & Bensimon, E. (1996). Promotion and tenure: Community and socialization in academe. Albany, NY: State University of New York Press. Tierney, W., & Lincoln, Y. (Eds.) (1999). Representation and the text: Reframing the narrative voice. Albany: State University of New York Press. Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition. Chicago: University of Chicago Press. Traweek, S. (1988). Beamtimes and lifetimes: The world of high energy physicists. Cambridge: Harvard University Press. Trowler, P., & Knight, P. (1999). Organizational socialization and induction in universities: Reconceptualizing theory and practice. Higher Education, 37(2), 177-195. Valimaa, J. (1998). Culture and identity in higher education research. Higher Education, 36(2), 119-138. Van Maanen, J. (1976). Breaking in: Socialization to work. In R. Dubin (Ed.), Handbook of work, education, and society (pp. 67-130). Chicago: RandMcNally College Publishing. Van Maanen, J. (1988). Tales of the field: On writing ethnography. Chicago: University of Chicago Press.
229 Van Maanen, J., & Schein, E. (1979). Toward a theory of organizational socialization. Research in Organizational Behavior, 1, 209-264. Vosskamp, W. (1986). From scientific specialization to the dialogue between disciplines. Issues in Integrative Studies, 4, 17-36. Wallerstein, I. (2003). Anthropology/sociology and other dubious disciplines. Current Anthropology, 44, pp. 453-465. Weidman, J., Twale, D., & Stein, E. (2001). Socialization of graduate and professional students: A perilous passage. New York: John Wiley and Sons. (ASHE-ERIC Higher Education Report No. 28-3) Weidman, J., & Stein, E. (2003). Socialization of graduate students to academic norms. Research in Higher Education, 44(6), 641-656. Weiland, S. (1995). “Belonging to romanticism”: Discipline, specialty, and academic identity. Review of Higher Education, 18(3), 265-292. Weitzman, E., & Miles, M. (1995). Computer programs for qualitative data analysis. Thousand Oaks, CA: Sage Publications. Whitley, R. (1977). Changes in the social and intellectual organization and social organization of the sciences. In E. Mendelsohn, P. Weingart, and R. Whitley (Eds.), The social production of scientific knowledge, Volume I. Dordrecht: D. Reidel Publishing Company. Wolcott, H. (1990). Writing up qualitative research. Thousand Oaks: Sage Publications. Woodrow Wilson National Fellowship Foundation (2001). The responsive Ph.D.: An initiative to improve the doctoral experience in the arts and sciences. Retrieved November 1, 2002 from http://www.woodrow.org/responsivephd Woodrow Wilson National Fellowship Foundation (2005). Innovations in U.S. doctoral education: Executive summary. Retrieved December 3, 2005 from http://www.woodrow.org/newsroom/News_Releases/WW_RespPhD_execsu m_w_caselist.pdf
230 Wulff, D., & Austin, A. (2004). Future directions: Strategies to enhance paths to the professoriate. In D. Wulff and A. Austin (Eds.), Paths to the professoriate: Strategies for enriching the preparation of future faculty (pp. 267-292). San Francisco, CA: Jossey Bass. Yin, R. (2003). Case study research: Design and methods (3rd ed). Thousand Oaks: Sage Publications. Zhao, C., Golde, C., & McCormick, A. (2005). More than a signature: How advisor choice and advisor behavior affect doctoral student satisfaction. Paper presented at the American Educational Research Association annual conference, Montreal, Canada.
231
APPENDIX A LIST OF STUDENTS WHO PARTICIPATED IN THE STUDY I interviewed 40 doctoral neuroscience students for this study. The table profiles those individuals who were identified by name in the dissertation. The names are pseudonyms in order to maintain confidentiality and student anonymity. Student
Year started
Research area
1
Alex
2004
Retinal prosthetic
2
Jennifer
2004
Cellular/molecular neurobiology
3
Lisa
2001
Aging brain degeneration and its relationship to disease
4
David
2001
Drug action on a cellular and molecular level
5
Kacey
2003
6
Gloria
2004
The molecular and cellular aspects of proteins Neural development, axons, and the spinal cord
7
Madeline
Graduated in 2004
Language and brain cognition
Other information Works extensively with computer modeling Background in biology, worked at NIH Works on medical school campus; spent one year working at NIH before graduate school Former president of the graduate student neuroscience group Left the program shortly after our interview Enjoys classwork, but is overwhelmed by the breadth of neuroscience Currently a psychology instructor at a public, teaching
232 university 8
Esther
Neural behavior of hormones
9
Walter
2003
10
Jonathan
2003
11
Megan
Graduated in 2002
12
Larry
2004
13
Amy
2004
Computational neuroscience
14
Nicole
2001
Neurobiology and neuroanatomy
15
Jacob
2004
Neural engineering and artificial intelligence
16
Victor
2004
Human vision system
Cognitive neuroscience (language and linguistics) Postdoctoral position in pharmacy Cellular physiology
Completed a master’s degree in neuroscience prior to Ph.D. International student; received a M.D. in his home country and was a practicing physician Ethically opposed to animal research Completed a M.S. degree in psychology Original interest in neural engineering has changed Pursuing computational research, despite her background in biology Originally enrolled in the Ph.D. program in biology before transferring to neuroscience Sees himself as an engineer; struggles to place himself within neuroscience An engineer, has struggled to
233
17
Christopher
2002
Cognitive science and visual systems
18
Amanda
2004
Cognitive studies of reading and dyslexia
19
Diane
Graduated in 2005
Neurobiology
20
Kaitlyn
2002
The relationship between neural circuits and motivation
21
James
2004
Neural engineering
22
Lauren
2001
Neurodegenerative disease
21
Wang
2003
Visual cortex
22
Jason
2002
Computational modeling of the visual system
master biological knowledge Hopes that the doctoral program will give him a chance to look at many issues from multiple perspectives Has little interaction with neuroscience peers; works in psychology lab Older student. Mother of two young children Completed twoyear NIH fellowship for minority students before graduate school Extensive experience in computer science International student; secured postdoctoral position working with stem cells Enrolled at Glenhaven because of its interdisciplinary emphasis on biology and computer science Moved from doctoral program in engineering to neuroscience
234 APPENDIX B STUDENT CONSENT FORM INFORMED CONSENT FOR NON-MEDICAL RESEARCH
****************************************************************** CONSENT TO PARTICIPATE IN RESEARCH (Students)
Identity and knowledge production: Re-conceptualizing doctoral student socialization in the interdisciplinary sciences You are asked to participate in a research study conducted by Karri A. Holley, Ph.D. candidate, and William G. Tierney, Ph.D., from the Rossier School of Education at the University of Southern California. The results of this study will be used for a doctoral dissertation. You were selected as a possible participant in this study because your enrollment in the NSGP neuroscience graduate program at USC. A total of 40 subjects will be selected from all doctoral students enrolled in the NSGP program. Your participation is voluntary. You should read the information below, and ask questions about anything you do not understand, before deciding whether or not to participate. PURPOSE OF THE STUDY The goal of this study is to understand doctoral student socialization within interdisciplinary degree programs. This study focuses on neuroscience programs to understand how doctoral students became socialized in an interdisciplinary culture. The challenge for neuroscience is to gain adequate knowledge and training from various fields of study. Of particular relevance for this study, therefore, is how doctoral students “become” neuroscientists. How do they process the collected knowledge relevant for research on the brain to become experts in the field? Given the multiple perspectives fostered by neuroscience, such as biology, engineering, computer science, and psychology, how do doctoral students define the field of neuroscience?
235 PROCEDURES If you volunteer to participate in this study, we would ask you to do the following things: 1. Participate in one interview lasting from one hour (minimum) to two hours (maximum). The interview will be audiotaped. You may agree not to be audiotaped and still participate in this study. You will be asked questions regarding your decision to enroll in a neuroscience doctoral program, your understanding of neuroscience as a field of study, your involvement with faculty and peers in the program, and your specific area of research interest within neuroscience. 2. Participate in a focus group consisting of other doctoral students enrolled in the NSGP program. There will be a maximum of eight students in the focus group. The meeting will be audiotaped. Consent to be audiotaped is required for focus group participation. The group will be asked questions regarding academic perspectives of neuroscience, experiences with faculty in the program, experiences with peers in the program, and the development of research interests within neuroscience. I will ask for your participation in the focus group after your interview. It is not required. You may complete the interview and not participate in the focus group. 3. I am also conducting observations of select class rooms, laboratory work, out-ofclass meetings, and formal department events. Observations will only be done with the permission of the department and the faculty. You may request not to participate in these observations. POTENTIAL RISKS AND DISCOMFORTS There are minimal reasonable or foreseeable risks, discomforts, or inconveniences involved with participation in this study. You may feel uncomfortable responding to questions about your enrollment in a doctoral degree program. You may refuse to answer any question and still remain in the study. The researcher will conduct interviews convenient to your schedule. You are free to end your participation in this study at any time. Interviews and focus groups will be audiotaped. During the interview, you may request not to be audiotaped at anytime, and still remain in the study. Consent to be audiotaped is required for participation in the focus group. The larger social benefits to individual participation outweigh the risks. The study will offer a greater understanding of the nature of interdisciplinary knowledge and
236 the institutional culture of interdisciplinary programs. The study will also provide insight into the culture of neuroscience and the organization of such programs. POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY When the study is completed, the project will provide a strong basis for understanding the socialization experiences of doctoral students in interdisciplinary degree programs. Little research has been conducted on how students engage in interdisciplinary areas of study and subsequent effects on their professional identity as scholars and future faculty. Your participation in this study helps to understand how doctoral students experience socialization in their program. You may not directly benefit from participating in this research study. PAYMENT/COMPENSATION FOR PARTICIPATION You will not be paid for participating in this research study. CONFIDENTIALITY Any information that is obtained in connection with this study and that can be identified with you will remain confidential and will be disclosed only with your permission or as required by law. The research data collected in this study will be stored in locked file cabinets in the office of the principal investigator. Data will also be stored on the passwordprotected computers of the principal investigator. To ensure confidentiality, pseudonyms will be used for all subjects. With your consent, interviews and focus groups will be audiotaped. Audiotapes will be transcribed by the researcher. Original audiotapes will be stored in locked file cabinets in the office of the principal investigator. Transcripts will be saved on the password-protected computers of the principal investigator. In addition, notes will be taken during the interviews and focus groups. The notes will be transcribed by the principal investigator. Original notes will be stored in locked file cabinets in the office of the principal investigator. Transcripts will be saved on the passwordprotected computers of the principal investigator. The data collected for this study will be destroyed after 3 years. Transcripts from the interview will be available upon request to you for review and comments.
237 You will be assigned a pseudonym that will be used in subsequent analysis and discussion of the research. When the results of the research are published or discussed in conferences, no information will be included that would reveal your identity. PARTICIPATION AND WITHDRAWAL You can choose whether to be in this study or not. If you volunteer to be in this study, you may withdraw at any time without consequences of any kind. You may also refuse to answer any questions you don’t want to answer and still remain in the study. The investigator may withdraw you from this research if circumstances arise which warrant doing so. IDENTIFICATION OF INVESTIGATORS If you have any questions or concerns about the research, please feel free to contact: Principal Investigator: William G. Tierney, Ph.D. Director, Center for Higher Education Policy Analysis Rossier School of Education University of Southern California (213) 740-7218
[email protected] Co-Principal Investigator: Karri A. Holley, Ph.D. Candidate Rossier School of Education University of Southern California (213) 740-1515
[email protected] RIGHTS OF RESEARCH SUBJECTS You may withdraw your consent at any time and discontinue participation without penalty. You are not waiving any legal claims, rights or remedies because of your participation in this research study. If you have questions regarding your rights as a research subject, contact the University Park IRB, Office of the Vice Provost for Research, Grace Ford Salvatori Building, Room 306, Los Angeles, CA 90089-1695, (213) 821-5272 or
[email protected].
238 SIGNATURE OF RESEARCH SUBJECT I understand the procedures described above, and I understand fully the rights of a potential subject in a research study involving people as subjects. My questions have been answered to my satisfaction, and I agree to participate in this study. I have been given a copy of this form.
□ I agree to be audiotaped for this study. □ I do not agree to be audiotaped for this study. □ I agree to participate in the focus group and be audiotaped.
Name of Subject
SIGNATURE OF INVESTIGATOR I have explained the research to the subject or his/her legal representative, and answered all of his/her questions. I believe that he/she understands the information described in this document and freely consents to participate. Name of Investigator Signature of Investigator
Date of Preparation: March 2, 2005 – Non-Med ICF USC UPIRB # 05-03-070 Expiration Date: February 24, 2006
Date
239 APPENDIX C FACULTY CONSENT FORM INFORMED CONSENT FOR NON-MEDICAL RESEARCH
****************************************************************** CONSENT TO PARTICIPATE IN RESEARCH (Faculty)
Identity and knowledge production: Re-conceptualizing doctoral student socialization in the interdisciplinary sciences You are asked to participate in a research study conducted by Karri A. Holley, Ph.D. candidate, and William G. Tierney, Ph.D., from the Rossier School of Education at the University of Southern California. The results of this study will be used for a doctoral dissertation. You were selected as a possible participant in this study because your affiliation with the NSGP neuroscience graduate program at USC. A total of 10 individuals will be selected from all faculty affiliated with the NSGP program. Your participation is voluntary. You should read the information below, and ask questions about anything you do not understand, before deciding whether or not to participate PURPOSE OF THE STUDY The goal of this study is to understand doctoral student socialization within interdisciplinary degree programs. This study focuses on neuroscience programs to understand how doctoral students became socialized in an interdisciplinary culture. The challenge for neuroscience is to gain adequate knowledge and training from various fields of study. Of particular relevance for this study, therefore, is how doctoral students “become” neuroscientists. How do they process the collected knowledge relevant for research on the brain to become experts in the field? Given the multiple perspectives fostered by neuroscience, such as biology, engineering, computer science, and psychology, how do doctoral students define the field of neuroscience?
240 PROCEDURES If you volunteer to participate in this study, we would ask you to participate in the following: 1. Participate in one interview lasting from one hour (minimum) to two hours (maximum). The interview will be audiotaped. You may request not to be audiotaped and still participate in the study. You will be asked questions regarding your academic background and interest in neuroscience, your opinions of doctoral student socialization in neuroscience and faculty roles in the process, and your professional assessment of neuroscience training offered to doctoral students. POTENTIAL RISKS AND DISCOMFORTS There are minimal reasonable or foreseeable risks, discomforts, or inconveniences involved with participation in this study. You may feel uncomfortable responding to questions about your mentoring relationship with students. You may refuse to answer any question and still remain in the study. The researcher will conduct interviews convenient to your schedule. You are free to end your participation in this study at any time. At anytime during the interview, you may request not to be audio-taped and still remain in the study. The larger social benefits to individual participation outweigh the risks. The study will offer a greater understanding of the nature of interdisciplinary knowledge and the institutional culture of interdisciplinary programs. The study will also provide insight into the culture of neuroscience and the organization of such programs. POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY When the study is completed, the project will provide a strong basis for understanding the socialization experiences of doctoral students in interdisciplinary degree programs. Little research has been conducted on how students engage in interdisciplinary areas of study and subsequent effects on their professional identity as scholars and future faculty. Your participation in this study helps to understand how doctoral students experience socialization in their program. You may not directly benefit from participating in this research study. PAYMENT/COMPENSATION FOR PARTICIPATION You will not be paid for study participation.
241 CONFIDENTIALITY Any information that is obtained in connection with this study and that can be identified with you will remain confidential and will be disclosed only with your permission or as required by law. The research data collected in this study will be stored in locked file cabinets in the office of the principal investigator. Data will also be stored on the passwordprotected computers of the principal investigator. To ensure confidentiality, pseudonyms will be used for all subjects. With your consent, interviews and focus groups will be audio-taped. Audiotapes will be transcribed by the researcher. Original audiotapes will be stored in locked file cabinets in the office of the principal investigator. Transcripts will be saved on the password-protected computers of the principal investigator. In addition, notes will be taken during the interviews and focus groups. The notes will be transcribed by the principal investigator. Original notes will be stored in locked file cabinets in the office of the principal investigator. Transcripts will be saved on the passwordprotected computers of the principal investigator. The data collected for this study will be destroyed after 3 years. Transcripts from the interview will be available upon request to you for review and comments. You will be assigned a pseudonym that will be used in subsequent analysis and discussion of the research. When the results of the research are published or discussed in conferences, no information will be included that would reveal your identity. PARTICIPATION AND WITHDRAWAL You can choose whether to be in this study or not. If you volunteer to be in this study, you may withdraw at any time without consequences of any kind. You may also refuse to answer any questions you don’t want to answer and still remain in the study. The investigator may withdraw you from this research if circumstances arise which warrant doing so. IDENTIFICATION OF INVESTIGATORS If you have any questions or concerns about the research, please feel free to contact:
242 Principal Investigator: William G. Tierney, Ph.D. Director, Center for Higher Education Policy Analysis Rossier School of Education University of Southern California (213) 740-7218
[email protected] Co-Principal Investigator: Karri A. Holley, Ph.D. Candidate Rossier School of Education University of Southern California (213) 740-1515
[email protected] RIGHTS OF RESEARCH SUBJECTS You may withdraw your consent at any time and discontinue participation without penalty. You are not waiving any legal claims, rights or remedies because of your participation in this research study. If you have questions regarding your rights as a research subject, contact the University Park IRB, Office of the Vice Provost for Research, Grace Ford Salvatori Building, Room 306, Los Angeles, CA 90089-1695, (213) 821-5272 or
[email protected]. SIGNATURE OF RESEARCH SUBJECT
I understand the procedures described above, and I understand fully the rights of a potential subject in a research study involving people as subjects. My questions have been answered to my satisfaction, and I agree to participate in this study. I have been given a copy of this form.
□ I agree to be audiotaped for this study. □ I do not agree to be audiotaped for this study.
Name of Subject Signature of Subject
Date
243
SIGNATURE OF INVESTIGATOR I have explained the research to the subject and answered all of his/her questions. I believe that he/she understands the information described in this document and freely consents to participate.
Name of Investigator Signature of Investigator
Date (must be the same as subject’s)
244 APPENDIX D STUDENT INTERVIEW PROTOCOL I. Personal experiences Tell me a little about your undergraduate experiences. Why did you decide to enroll in this neuroscience program? What were your other options? What adjustments did you have coming out of your undergraduate program into this neuroscience area? What areas did you feel particularly strong in, and what did you feel like you had to catch up on? How do you balance the different requirements in your personal life and your academic program? How would you define yourself professionally? How might others define you? II. Program/research experiences How would you define your research interests? Has that changed since you started the program? If so, how? What influence has the faculty had on your research agenda? With what faculty do you interact? Tell me about your rotation experience. What was your experience as a student in the core course? What suggestions might you have for improving the course? Do you think such a course should be required of all neuroscience students? What knowledge from the core course do you use in your research? Tell me a little about your lab and the other students you work with. If the other doctoral students in your lab are not enrolled in neuroscience, what (if any) differences exist in research agendas, daily activities, and faculty interaction?
245 If I followed you for a day in the lab, what would I see you do? What new techniques have you had to learn for your research? Could you do this same research and be enrolled in another doctoral program—not in neuroscience? Do you interact with students outside of the neuroscience program? Do you notice any differences between those students and your peers in the neuroscience program? What do you share in common with the other neuroscience students here? What conferences do you attend regularly, or plan to attend? What conferences does your faculty advisor attend? What journals would be appropriate to submit your work to? What journals does your faculty advisor normally submit their work to? What journals do you read on a regular basis? Tell me how you have seen this program change since you have been enrolled. What type of position do you hope to secure after graduation? Do you feel prepared to secure such a position? Why or why not? III. Questions regarding neuroscience How would you define neuroscience? What do you see as the future of neuroscience? If neuroscience is defined as an interdisciplinary field of inquiry, how much do you feel you have to know about, or should know, about all these other parts of the field? What benefit might such knowledge be to you? Do you ever feel like you are enrolled in an interdisciplinary program? In what ways? Administratively, could you see this program existing any differently than it is now?
246 APPENDIX E FACULTY INTERVIEW PROTOCOL Tell me briefly about your research. How does that fit into your definition of neuroscience? Tell me how you came to be affiliated with the neuroscience program here. How has your research changed over the course of your career? How many students are working in your lab currently? Are all the students enrolled in the neuroscience program? Do you work differently with students enrolled in different programs? What is your opinion of laboratory rotations for new doctoral students? What advice would you give to prospective doctoral students who are considering enrolling in either an interdisciplinary program such as neuroscience or a single discipline doctoral program? Tell me about the neuroscience courses that you teach. What approach do you take for teaching students in neuroscience? Is this approach different when you teach students in a primary discipline? Tell me about the composition and content of the core classes. What level of interaction do you have with doctoral students enrolled in the neuroscience program? What is your opinion about the distance between the two campuses and its effect on the neuroscience program? How would you describe the significance of such concepts as disciplinarity and interdisciplinarity? What knowledge would you expect all the neuroscience students to know? What degree of familiarity is required with such knowledge? What are the interdisciplinary features of neuroscience? What would you say is the future of neuroscience?
