Applying Psychology Disciplinary Knowledge - Higher Education

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Applying Psychology Disciplinary Knowledge to Psychology Teaching and Learning

A review of selected psychological research and theory with implications for teaching practice Lucy Zinkiewicz Nick Hammond Annie Trapp University of York

Report and EvaluationReport Series and No 2 Evaluation Series 2 MarchNo 2003 March 2003

Contents Abstract

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Introduction

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Applying Disciplinary Knowledge to Teaching Practice

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Teaching practice informed by research knowledge The use and disuse of research-informed teaching practice

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Research-Informed Psychology Teaching

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The need for a discipline-specific approach Psychology disciplinary knowledge and teaching practice Barriers to research-informed teaching in psychology The nature of disciplinary knowledge in psychology Operationalising and evaluating psychological theory Resistance to change Approaches to research-informed practice in psychology teaching The problem-driven approach The knowledge-driven approach Integrating the two approaches

9 9 10 11 11 12 13 13 13 14

Selected Disciplinary Research with the Potential to Inform Teaching

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Theories of development Piaget’s cognitive development theory (genetic epistemology) Vygotsky’s sociocultural theory of cognitive development Cognitive development in adults Implications for teaching Student diversity Intelligence and reasoning Guilford’s structure of intellect theory Sternberg’s triarchic theory of successful intelligence Gardner’s multiple intelligences Student learning styles Student approaches to learning Need for cognition Creativity Implications for teaching Personality Trait approaches Theoretical approaches Implications for teaching Cross-cultural differences Implications for teaching Learning and thinking Behaviouristic approaches The personalised system of instruction Implications for teaching Experiential approaches Active learning Problem-based learning Case studies Implications for teaching Cognitive approaches Thinking and reasoning Gestalt theory Implications for teaching Schema theory Implications for teaching General cognitive skills Implications for teaching

15 15 15 16 17 18 18 18 18 19 19 21 22 22 23 23 23 24 26 26 27 27 27 28 30 30 31 32 32 33 33 33 33 34 34 35 35 36

Biases in cognition Implications for teaching Metacognition Implications for teaching Memory Information-processing theory Connectionist models Self-referencing Implications for teaching Learning Subsumption theory Implications for teaching Constructivism Situated learning Cooperative learning Implications for teaching Gagné’s information-processing model of learning Implications for teaching Transfer of learning Implications for teaching Social learning approaches Implications for teaching

36 37 37 38 38 38 42 42 42 43 43 44 44 46 47 49 49 49 50 50 51 52

Motivation Intrinsic and extrinsic motivation Maslow’s hierarchy of needs Herzberg’s two-factor theory Expectancy theory Self-determination theory Attribution theory, locus of control and self-efficacy Goal orientation Implications for teaching

52 52 54 54 55 56 57 57 58

The social context Group processes Group development and structure Communication within groups Group norms and conformity Social loafing Implications for teaching Intergroup relations Stereotyping and prejudice Intergroup contact Implications for teaching Persuasion and attitude change Cognitive dissonance theory The elaboration likelihood model Implications for teaching Leadership Implications for teaching

59 59 59 60 61 62 62 62 62 63 64 64 64 65 66 66 67

Barriers to and facilitators of learning Arousal and emotion Anxiety Stress Psychotherapy Resilience Implications for teaching

68 68 68 70 71 71 72

Assessing student learning Implications for teaching

73 74

Conclusion

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References

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Abstract This report explores how psychology research, theory and knowledge can be and has been applied to learning and teaching in psychology, with the aim of enabling more effective application of such disciplinary knowledge to psychological teaching practice. Because of this focus it is not a comprehensive overview of every psychological theory or knowledge base with implications for psychological teaching, but a brief outline of some key theories that have inspired or fed into psychology teaching or have the potential to do so. Its target audience is psychology teaching staff within the UK university sector, but it may be of interest to educators in different disciplines, sectors and countries. The report begins with a brief discussion of the nature of research-informed teaching practice, and the opportunities it offers, as well as reasons for its disuse (including the tacit nature of much practitioner knowledge, and lack of ownership of innovations). Research-informed teaching in psychology is then focused on, and particular barriers to the application of psychology theory and research to teaching are discussed. Problem-driven and knowledgedriven approaches to the application of psychological knowledge to practice are described, and their strengths and weaknesses delineated. The main body of the report is an overview of a variety of psychological theories and research findings with pedagogical applications, highlighting implications of this knowledge and research to psychology teaching practice. Selected examples of the application of this knowledge to practice can be found throughout this section, boxed to make them easier to find. The report concludes with a call for evaluation of the effectiveness of research-informed teaching practice, and for psychology practitioners to share their own such teaching practice. A full reference list is also attached.

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Introduction This research report, based on the findings of the ‘Integrating pedagogic research into teaching practice in psychology’ project funded by the Learning and Teaching Support Network Development Fund, explores how psychology research, theory and knowledge can be and has been applied to various aspects of psychology teaching. The aim of the project is to enable more effective application of such knowledge to the learning and teaching of psychology. The present report focuses not on psychological knowledge as course content, but as the conceptual framework supporting innovations in psychological teaching practice. It is about how this knowledge can and does inspire new course structures, classroom activities, assessments, feedback mechanisms, web-based activities, and other aspects of teaching in psychology. In order to do this, it reviews not just the published literature relating to researchinformed psychological teaching practice, but also explores some recent examples of this within higher education (HE) in more depth. Because of its focus on implications of research and theory for teaching, this report does not aim to be a comprehensive overview of every psychological theory or knowledge base with implications for teaching, but a brief outline of some key theories that have inspired or fed into psychology teaching. Little prior knowledge of psychology is assumed, to make the report as broadly accessible as possible. While some readers may choose to read through the report from beginning to end, it is structured in such a way that the reader can dip into it at any point, and hopefully still find it comprehensible and useful. While this report is primarily aimed at those teaching psychology in HE, it may also be useful for educators in psychology in further education, professional training, and secondary education, as well as for educators in other disciplines. Although its intended audience is a UK one, many of the examples of psychology teaching discussed are non-UK ones, and it anticipated that non-UK psychology educators may also find this report to be of some use. The report is complemented by the project’s website (http://ltsnpsy.york.ac.uk/ LTSNPsych/r2p.htm), which features case studies on current research-informed psychology teaching practice in the UK, reflective tools for educators in psychology, and an online database where practitioners can share their own research-informed teaching practice. We would like to invite you to explore the website, and to use it to contact LTSN Psychology with any feedback or suggestions you may have concerning the issues raised in this report, the project as a whole, or the project website. This report begins, in the next section, with a brief discussion of the nature of researchinformed teaching practice, and the particular possibilities and problems it offers in the psychology teaching arena. This is followed by an overview of a variety of psychological theories and findings with pedagogical applications, highlighting applications of these theories to psychology teaching practice, with boxed examples of when such theories have been thus applied. A full reference list is also attached.

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Applying Disciplinary Knowledge to Teaching Practice Teaching practice informed by research knowledge In the context of discussions about the scholarship of teaching and scholarly teaching, teaching based on research knowledge (both theory and method) is often known as researchled or research-based teaching. However, as McGuinness (1999) discusses, the term ‘research-led teaching’ has assumed various meanings, and can refer to: • Teaching about specific research topics which are being studied by an academic at a point in time; • Teaching which emphasises the cutting edge research/developments in one’s own area of research; • Teaching more generally in one’s own area of scholarship; • Teaching with an emphasis on research methods/processes or ways of accumulating knowledge in a particular discipline; • Teaching as ‘inquiry-based’ learning versus more didactic approaches to teaching; • Designing degree programmes which capitalise on current research expertise in a school or across schools. However, there is another sense in which teaching practice can be based on research knowledge, and that is where teaching and curriculum uses evidence derived from pedagogical and other disciplinary theory, research and inquiry – for example, designing an assessment task on the basis of published education research – or utilises research methodologies to evaluate the effects of educational interventions. This type of educational practice could also be appropriately termed ‘research-informed teaching practice’, to differentiate it from the former type of practice. It is such research-informed teaching practice that is focused on in the present project.

The use and disuse of research-informed teaching practice The interest in research-led and research-informed teaching reflects a trend in HE towards building upon established research expertise and performance and utilising it in the increasingly competitive teaching quality market, with an increasing recognition that the scholarly and professional nature of university teaching is an aspect of the disciplinary expertise of academics (Barrie, Buntine, Jamie, & Kable, 2001). It also reflects the increasing pressures for teaching quality to be accountable. Research-informed teaching has the potential to improve teaching and learning in a number of different ways. When one’s teaching practice is based on theory and research knowledge, this can enhance learning through the use of more effective teaching and learning methods. It can also provoke students to consider how course content has been utilised and/or manifested in the teaching methods used, and models the application of theory to practice (Norton, 2002). Research-informed teaching may also foster enthusiasm in educators, particularly where the research area concerned is a passion of theirs, and/or tied into their research output. Academics who are research-oriented may value teaching that is related to their research more than other areas of teaching (Coate, Barnett, & Williams, 2001).

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However, until recently it has been unusual for educators to apply research findings to the practice of their profession (Laurillard, 1993). For example, in the school context, Galton (2000) reported that while 96% of the 302 educators surveyed had seriously considered educational research findings since first qualifying as educators, 23% of these could not subsequently give a single example of research that had influenced them, and most of the (largely psychological) research cited was at least ten years old. Though a similar study has not been conducted in the HE context, it is likely that similar or worse results could be found. There are many reasons for this failure to apply research findings to teaching, including: • Separation of the research and teaching cultures, with strong financial and bureaucratic pressures, in the current climate of UK HE, to treat research and teaching as distinct activities (Coate et al., 2001; Hattie & Marsh, 1996), with teaching generally less rewarded (Huber, 2002); • The traditional view of teaching as a ‘private’ activity, not a matter for scholarly enquiry and communication, in contrast to research as a ‘community’ activity, where practice is shared (Bass, 1999; Huber, 2002); • Ignorance of relevant research findings, compounded by academics’ tendency to turn to colleagues when they encounter problems in their teaching, rather than to the published research (Huber, 2002); • Uncertainty about how research findings can be applied to specific teaching practice; and • Suspicion of generic research activities and findings and their application to teaching practice, particularly if findings are presented in a popularised form that does not give readers a hold on the research and arguments of the original work (Cross, 1998). However, even when academics develop research-informed educational innovations, this does not mean that such innovations will be effectively implemented and/or taken up by other academics, even within the same department or school. Resistance to change in established processes is inevitable in any context, and may be greater in teaching cultures, which may favour inertia over innovation (Bass, 1999). It is also important to consider the perceived ownership of innovations – the processes by which individuals come to feel that the changes of which they are a part are in a real sense ‘their’ changes (Slowey, 1995). For example, Blackwell, Channel and Wilson (2001) describe the same initiative introduced in two contexts: a department with no history of activity in the area, and one with a more favourable and active environment. The initiative was a success in the former, and a failure in the latter, contrary to what might have been expected. Blackwell et al. attribute this to staff ownership and positive attitudes, and leadership support, in the former department, contrasted with a perception of unnecessariness, and leadership attributing the initiative to ‘external forces’, within the latter. Blackwell and Preece (2001) suggest that three social processes appear to be central to generating a sense of ownership: • The way in which the idea is introduced and to whom the participants attribute its genesis; • The extent to which those involved are socially integrated, with common norms of behaviour and understandings of the world; and • The ways in which leaders influence participants’ attributions of why the innovation is occurring, and frame issues such that they mobilise support in particular directions.

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The two researchers also suggest that academic staff unwillingness to adopt teaching and learning approaches or materials developed elsewhere may be due to their first loyalty being to their discipline, or subdiscipline and subject, with loyalty to department and institution coming in second and third. In a context where the growing desire of government to intervene within HE has created a feeling that discipline identity, professional autonomy and collegiality (all of which tend to be valued within academia) are threatened, any initiative with a largerscale feel is viewed with scepticism and suspicion. Working through discipline-based networks such as LTSN Psychology, and creating discipline-specific innovations and staff development, may therefore be the best way to foster the uptake of educational innovations. Based on work within the school context, McLaughlin and Mitra (2001) set out five recommendations for sustaining theory-based educational innovation, which parallel many of the points Blackwell and colleagues make: • Long-term resources must be sufficient to sustain changes, and to evaluate their impact; • Educators need to be inducted into the first principles of the reform, as well as the reform’s activities, materials and strategies, in order to respond to competing pressures or changes in the environment once the ‘special project’ status ends; • A supportive community of practice must be developed, which may require involvement by the whole institution; • Managers/supervisors must have their own reasons for supporting the initiative, as well as their own clearly delineated roles, and these need to be anticipated and built into the design; and • Governing bodies must again have delineated roles, and be supportive. Despite difficulties in achieving these goals, however, work has been done more recently on the application of educational research to teaching practice, particularly in the spheres of physical and natural science teaching at primary, secondary, and tertiary levels (e.g., Barrie et al., 2001). This work has tended to focus on the development of teaching demonstrations and other concrete resources. An important conclusion that can be drawn from these studies is that underlying theory must be contextualised and interpreted within the specifics of the particular learning situation in which it will be applied. Such an approach to research-informed teaching is also taken in the present report, for reasons that will be explored in the following section.

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Research-Informed Psychology Teaching The need for a discipline-specific approach The present report, and much of the work of LTSN Psychology, is an example of what is known as the scholarship of learning and teaching – scholarly research and communication that aims not only to improve teaching and learning in one’s own classroom, but also to improve it beyond one’s local setting by adding knowledge to, and even beyond, one’s discipline (Hutchings & Shulman, 1999). Amongst those working in the area, there is an increasing recognition that much of this scholarship is most effective if done at a disciplinary level, in part because of the importance of one’s discipline to academic identity, and in part because teaching is not a generic technique but a process arising from one’s view of one’s field and what it means to master it (Huber, 2002). Disciplinary styles influence the pedagogical practices used in a discipline, so it is unsurprising that they also influence the choice of pedagogical problems investigated, and the methods of inquiry used in such investigation. Scholars usually begin by following disciplinary models developed for other purposes, when faced with the new task of exploring teaching and learning in their field (Huber, 2002). For example, Cerbin (1996) uses the analogy of a psychological experiment to describe the action research conducted on his psychology subject. Evidence for the success of an intervention, and the standard of proof for determining that an innovation works, also varies by discipline (Huber, 2002). In addition, academics are likely to be more receptive to findings obtained through methods previously used within that discipline, and disseminated through the discipline’s usual routes of communication. For example, psychologists often communicate the findings of their teaching- and learning-related research in the form of conference papers presented at psychology teaching and learning conferences (such as LTSN Psychology’s Psychology Learning and Teaching Conference), and articles in discipline-specific teaching and learning journals (e.g., Psychology Learning and Teaching, Psychology Teaching Review, and Teaching of Psychology).

Psychology disciplinary knowledge and teaching practice In a number of ways psychology is in a special position regarding research into educational practice. Many areas of psychological research are potentially relevant to understanding the processes of learning and teaching, which themselves are strongly psychological in nature. The question ‘what works in teaching and learning?’ is a particularly engaging one for a discipline that focuses on cause and effect relationships (Nummedal, Benson, & Chew, 2002). Many psychologists have some familiarity with the kinds of methods used to evaluate the effects of educational interventions, while psychological research findings can directly inform the design of such evaluations, pinpointing particular questions to be answered (Nummedal et al., 2002). It is not an unreasonable conclusion that bodies of psychological research data and theory can be applied to aspects of educational practice under defined circumstances.

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However, such application of psychological understanding to improving the teaching of psychology is still relatively infrequent (Gale, 1990a, 1990b; Radford, 1992; Watts, 1990), despite an established theory and research literature relevant to teaching, student learning and the teaching environment. As Gale (1990b) puts it: The typical psychology degree on offer today falls very short of the ideal. A major problem, or cause of the problem, is that psychologists have not used psychology itself to design the degree (p. 8). Brown (1997) adds: To be experts on the subject matter of learning and assessment but not to apply that expertise to the learning and assessment of one’s own students is to send conflicting, perhaps hypocritical, messages to them. And those that then become teachers of psychology will probably perpetuate the same approaches (p. 122). This disuse of psychological knowledge is particularly ironic given psychologists’ tendency to encourage evidence-based practice in government and other agencies (Newstead, 2002). The only major exception to this lack of application of psychological knowledge to teaching practice is in the area of learning theory, which serves as the theoretical foundation for numerous innovations in school (e.g., Brown & Campione, 1996) and tertiary (e.g., Doolittle, 1997) education. Other areas of relevant theory and knowledge are much less frequently applied, even by those developing this knowledge, the academic psychology community. This is not to say that psychology teaching staff are not utilising such knowledge in the development of teaching innovations, but that this process may be a largely unconscious one. It is well-recognised that experts in a field, such as psychology lecturers, internalise their knowledge of the field, its rules, values, attitudes, norms, procedures and the knowledge that relates to these procedures so deeply that they take them for granted (Polanyi, 1958, 1967). This taken-for-grantedness is described by Jarvis (2002) as the hardest type of knowledge to get at because experts rarely have the self-awareness to recognise what it is, so it must be painstakingly mined for. As Jarvis puts it: In the complex classroom situation we do not necessarily make our knowledge about teaching and learning explicit to ourselves. However, we need to make our current teaching practice, and the theories and beliefs underpinning such practice, explicit so that new approaches can connect with what the individual knows and holds tacitly (p. 130). It is hoped that the present report will help this process become a more conscious one, and that this will foster more effective teaching and learning in psychology.

Barriers to research-informed teaching in psychology It is interesting to speculate why research knowledge appears to be less frequently explicitly applied to the development of improved teaching practice in psychology than one would expect, given its relevance to teaching and learning. It is likely that a number of factors influence this, in addition to the factors identified above that inhibit the application of research to teaching in all disciplines.

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The nature of disciplinary knowledge in psychology Firstly, psychology is a very large field, which makes it difficult for individuals to have a broad range of knowledge of relevant theories and research findings. The diversity of theoretical models in psychology can make it still more difficult for educators to make predictions regarding behaviour in a particular context (Kremer, 1997), let alone predictions that are specific and accurate enough on which to base practice. Some practitioners may perceive that much of psychology knowledge, particularly that obtained through laboratory experiments, is too theoretical and/or reductionist, and has too little ecological validity, to provide much guidance for practice (Richardson, 1992b; Tomlinson, 1992). In relation to cognitive psychology knowledge, Richardson (1992b) argues that the lack of application of this subdiscipline to education, despite its relevance to teaching and learning, is due to its lack of interest in studying differences between individuals in cognitive development and associated cognitive function, and its tendency to assume that the responsible processes and mechanisms are common to all. For psychology educators with a focus on individual differences and needs of students, such research may appear to have little relevance. In addition, cognitive psychologists have often had little interest in the qualitative and especially in the experiential aspects of human cognition, which are difficult to quantify and verify against objective behaviour. Yet these aspects of cognition, such as student approaches to learning or their perception of the educational context, may strongly impact upon their processes of learning. More important than the nature of psychological knowledge, however, may be the issue of perceived competence in this knowledge. Even when a psychology educator may be aware that there are theories of (for example) motivation of relevance to teaching, they may feel that their knowledge is insufficient to be acted upon, particularly as psychology training and socialisation into the profession emphasise the need for a deep knowledge of an area before it can be further investigated or applied. This is not merely an issue of exposing oneself to possible negative evaluation, but of lack of psychological ownership of the knowledge, which is likely to be an important aspect of perceived self-efficacy in its application.

Operationalising and evaluating psychological theory In addition, while psychologists are methodologically informed and sophisticated, this may sensitise them to the challenges inherent in engaging in and evaluating research-informed practice and deter them from such. It may be difficult to adequately operationalise some psychological theories, particularly those developed on the basis of controlled experimental research, making theory testing problematic. Investigations conducted in the classroom rarely permit the methodological rigour that is traditionally seen as necessary within the discipline to rule out alternative explanations and determine what is responsible for any change (Nummedal et al., 2002). It may even be unethical to manipulate or control aspects of the educational situation or the nature of participants (Huber, 2002). For example, who should or could make up a control group, and how can students be randomly assigned to conditions when timetabling constraints may limit their attendance to particular sessions?

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Even when a theory has been adequately operationalised, and attempts made to control and standardise the implementation of an innovation, the demands of the educational situation may require or otherwise lead to inadequate sample size, loss of consistency in implementation, or other methodological problems, as the case studies associated with this report show (http://ltsnpsy.york.ac.uk/LTSNPsych/r2p.htm). Variable(s) of interest may interact with other variables in the environment, such as the personal characteristics of a tutor, making it harder to attribute any changed outcomes solely to the focal variables. The more complex and large-scale the innovation, the more likely it is that such uncontrolled or uncontrollable factors will impact upon the results. However, Nummedal et al. (2002) argue that the “lofty standard” (p. 174) of the experimental method may not be the most appropriate approach to investigating the impact of researchinformed and other pedagogical innovations in psychology. They argue that those in the discipline who devalue scholarly work on teaching and learning for not meeting this standard miss the most fundamental point about the relationship between research problems and research methodology – that methods per se do not have intrinsic value. Rather, their value is determined by the context of research questions, and should be assessed in terms of the extent to which they serve to provide useful answers to these questions. On a more metatheoretical level, it could also be argued that a theory that is not applicable to and testable in a real-life context may be an inadequate theory (Tomlinson, 1992). As Jarvis (2002) puts it: In the contemporary learning society, where education is become more vocationally oriented… there is still a place for theoretical perspectives but the nature of theory has changed slightly – it is no longer to be applied to practice but tested out by practitioners in practical situations to see whether it works. Theory can only be legitimated in practice situations if it is useful to the practitioners who use it and we can rephrase the old maxim, ‘There is nothing as practical as good theory’ thus: ‘Theory is only good if it is practical’ (p. 130). McLaughlin and Mitra (2001) argue that to bring about effective implementation of theorybased change in classroom practice, theories need to be reconstructed so that they can adapt to the ways in which educators have to function on a daily basis, complete with competing demands – i. e., theories need to become context-sensitive. However, context-sensitive theories may be context-bound, making them difficult to apply in different contexts from those in which they are developed.

Resistance to change In addition, as with research-informed innovations in general, students and other staff members may show resistance to research-informed change in psychology teaching practice, despite it being based on valued research knowledge. The larger the scale of the change, the more likely some resistance will be encountered. While much of this resistance may be due to difficulties associated with changing one’s own established practice – for example, learning new skills, rewriting subjects, or obtaining bureaucratic approval or necessary funding – within the psychology context some of the resistance may relate to the nature of one’s self-concept. If a colleague within one’s department does not see his-or her self as a researcher, or as a scientist-practitioner, they may resist change that is grounded in research and the scientific method. 12

Approaches to research-informed practice in psychology teaching As already noted, the next section of this report focuses on psychological theories with relevance to learning and teaching in psychology, and briefly describes teaching innovations which have some basis in these theories or bodies of knowledge. These innovations take one of two main approaches to the application of psychological knowledge to teaching practice: the problem-driven and the knowledge-driven approaches, each of which will now be described.

The problem-driven approach The problem-driven approach to research-informed practice arises from the need to deal with a particular teaching and/or learning problem that is encountered, including the failure of an intervention based on an aspect of research. In such a situation, when academics start asking questions that the literature may help them formulate and resolve, they are more likely to turn to the expert research (Cross, 1998; Nummedal et al., 2002). Such an approach has parallels with (but differs from) the use of problem-based learning activities in teaching. For example, if lecturers find that students in a particular subject are unmotivated, they may seek ways to deal with this problem, and as a consequence explore what the psychological literature may say regarding motivation and how to foster it in general, and motivation to learn in particular, and devise a research-informed intervention. The results of this intervention may then extend, modify, or even contradict prior understandings, leading to important new research questions (Nummedal et al., 2002). This more reactive approach may be a common way of operating in teaching and other applied fields, where time is limited and problems urgent. Unfortunately, such an approach may lead to innovations not being documented in the literature, or perhaps solely in the general or discipline-specific HE teaching and learning literature. Findings with important implications for the psychological research/theory from which the solution is taken may not be disseminated to the mainstream of psychological research, and may therefore not be applied and built upon. If the methodology used to determine the problem and its solution(s) is that of action research (Norton, 2001b), there may be particular difficulties in getting publication in many mainstream journals with a tradition of publishing experimental and quasi-experimental research. However, innovations taking this approach are likely to be more ecologically valid, and may be more successful, as they are shaped by and for the particular context in which the knowledge is applied.

The knowledge-driven approach By contrast, the knowledge-driven approach focuses on working from one’s knowledge of psychological research and theory to investigate the implications and applications of this theory in the teaching and learning context, and has parallels to the use of classroom activities and assessments in which students are required to apply to a new context theory or knowledge that they have been taught. For example, if one were a social psychologist focusing on intergroup relations, one might explore the implications of research on intergroup contact to foster better relationships between mature-age and younger students in the

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classroom. Such application may be an unconscious process (i.e., one suddenly realises the implications of one’s knowledge base), or a more proactive, systematic approach, perhaps rooted in one’s own research, and exploring its extensions into the educational context. Because of the stronger research/theoretical orientation of those taking on this approach, methods used may be those common in more mainstream experimental or quasiexperimental research (e.g., random assignment to conditions, pre- and post-testing, use of control conditions, etc.). By being rooted in mainstream psychological research, theory, and methodology, there is a greater likelihood of it ‘feeding back’ into the mainstream literature through acceptance for publication in traditional psychological journals. However, if these journals are not also read by the practitioner community, successful innovations may not be taken up by those who may be most in need of them. Even if read by practitioners, the implications of the study to practice may need to be made more transparent, or may not be seen as applicable to other contexts. This may particularly be the case if the study is not conducted in a real-life teaching context, but instead puts psychology students into an experimental setting, as is the case for some of the innovations reviewed in the next section of this report.

Integrating the two approaches Both approaches can be equally valid, provided educators attempt to deal with the limitations of whichever one is chosen. However, in reality few innovations will take entirely one approach or the other, but will take both approaches at some point(s) in the process. For example, some of the case studies collected on the website for this project (see http://ltsnpsy.york.ac.uk/LTSNPsych/r2p.htm) take a mixture of the two approaches. The innovation described in Case Study 2, which focuses on the application of research into academic reading and writing, initially arose from the research interests of two of its main drivers, taking a knowledge-driven approach. Yet there was also an element of being dissatisfied with the previous situation, so to some extent the innovation was also problemdriven. By contrast, the innovation described in Case Study 1 began by taking a more problem-driven approach (motivated by new requirements for explicit assessment criteria), but shifted into a more knowledge-driven approach in order to develop the specific assessment criteria produced. Additionally, as already mentioned, the results of problem-driven interventions, as well as knowledge-driven ones, can have important consequences for the research and theory on which interventions are based, and thereby lead to subsequent knowledge-driven interventions. Further examples of both approaches, taken from the literature, can be seen in the next section of this report.

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Selected Disciplinary Research with the Potential to Inform Teaching As outlined in the previous paragraph, the present section of this report introduces a range of psychological theories and findings with implications for psychology teaching. This is not intended to be a comprehensive review of all theories and findings with relevance to teaching, merely an introduction to some theories with clear implications for the teaching of psychology, and a highlighting of such implications. Interspersed among the overviews of teaching-related theories and research are brief overviews of published reports and conference papers in which some of the reviewed theories have been applied to psychology teaching. These examples of applications are highlighted in boxes, for easy reference.

Theories of development Piaget’s cognitive development theory (genetic epistemology) According to Piaget (1972, 1973), four factors shape cognitive development: maturation (due to genetic forces), equilibration, active experience, and social interaction. Equilibration is the tendency to balance assimilation (responding in terms of previous learning, assimilating new experience to one’s cognitive schemata, see page 34) with accommodation (changing behaviour and/or one’s schemata in response to the environment). Active experience is interaction with real objects and events, allowing the individual to discover things and to construct schemata. Social interaction leads to the elaboration of schemata about things, people and the self. Piaget described cognitive development as moving from concrete, literal thinking (the sensorimotor, pre-operational, and concrete operations stages of development) to abstract, symbolic thought (the formal operations stage). In the formal operations stage, individuals can deal with abstract, hypothetical subject matter, and there is propositional thinking, complete generality of thought, and the development of strong idealism. While Piaget felt that formal operations was reached by ages 11 to 12, some research has shown that only a small proportion of college students actually are in formal operations, with most still in concrete operations. Students in this stage of thinking cannot understand symbolism, hypotheticaldeductive reasoning, synthesis and evaluation, except in a very concrete and literal way, therefore as an educator it is impossible to use curriculum and pedagogy at a formal operational level with students who are still in concrete operations.

Vygotsky’s sociocultural theory of cognitive development While the emphasis in Piaget’s theory is on the internally-driven development of the logical systems underlying the construction of meaning, Vygotsky’s (1962, 1978) theory emphasises the centrality of culture and of social influences in human development, and of the principal invention and main tool of human culture, language. According to Vygotsky, humans create culture, but cultures have lives of their own and powerfully influence us: we are not only culture-producing but culture-produced. They specify what the end product of successful development is, determine what we have to learn and the sorts of competencies we need to

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develop. Psychological development may therefore differ in different periods of history and from one culture to another. Humans move from elementary human functions to higher mental functions such as problem-solving and thinking largely through the influence of culture, as social processes bring about the learning of language, and language ultimately makes thought possible. Language, according to Vygotsky, is the basis of consciousness, making thought possible and regulating behaviour. Without language we are limited to elementary mental functions. But with language we can interact socially, and with social interaction comes what Vygotsky describes as ‘upbringing and teaching’, which is essential for development. Vygotsky also came up with the concept of a zone of proximal growth (or development), a zone of current capabilities with the potential for development and improvement, where a task can be initially done with the help of others but can later be done alone. The task of educators is to arrange for educational activities that lie within this zone – neither too difficult nor too simple and that therefore lead to continued growth. Because this zone varies between individuals, the most effective teaching methods take into consideration individual differences and therefore need to be varied across a class. Tasks within the ZPD require scaffolding, defined as the many different methods educators use to provide support for students as they learn – direction, guidance, support – and which they gradually withdraw as the learner begins to build on previous learning by gradually learning how to learn. Scaffolding is essentially learning through gradual increments as a result of an interactive process of collaboration between educator and learner. Doolittle (1997) discusses how the ZPD also relates to the instructional strategy of cooperative learning, pointing out that the ZPD provides a conceptual basis for explaining the five basic tenets of cooperative learning: positive interdependence, face-to-face interaction, individual accountability, small group and interpersonal skills, and group self-evaluation. On the basis of this discussion, Doolittle presents a series of guidelines or suggestions for using cooperative learning. Vygotsky also emphasised that as education is intended to develop individuals’ personalities, and therefore is linked with the development of creative potential, education should provide opportunities for this creative development. He also emphasised the importance of active learning and collaborative learning, with students as true participants in the teaching/learning process and educators as guides and directors of activity.

Cognitive development in adults While Piaget’s model essentially ends at formal operations, positing little change after this is achieved, Basseches (1984) argues that cognitive development continues after adolescence, reflecting the problems faced in adult life. Instead of becoming more logical, thinking becomes more relative, more attuned to conflict, and more sensitive to moral, ethical, social and political realities – a form of thinking Basseches calls dialectical thinking. Dialectical thinking struggles to create meaning and order by resolving conflict, with the dialectical thinker always aware of other possibilities and recognising that no solution is necessarily absolute and final. Labouvie-Vief (1980) agrees, pointing out that formal logic might be inadequate or even irrelevant for many of the problems that adults face. Mature reasoning requires concrete pragmatics, sensitive to a wide range of possibilities, taking into account what will work and is acceptable, and factoring in social and moral realities.

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Knowles (1984a, 1984b) argues that the differing nature of adult thought means that adult learning (‘andragogy’) requires different learning strategies and teaching techniques from those used in traditional pedagogy. It is argued that: • Adults’ earlier learning is substantial, implicit, assumed, and needs to be built upon through new learning experiences; • Adults are generally self-directed, but also require a climate of trust, collaboration and openness; • They are biased towards learning through problem-solving and experience (including mistakes); • They generally internalise their learning only if motivated by intrinsic factors (see page 52); and • They need to see high practical relevance in order to commit to learning. Andragogy implies an acceptance of the importance of more focused and individualised learning strategies, rather than simply treating everyone homogeneously as a group with common needs and experiences. While this does not mean an end to collective learning experiences that can offer valuable opportunities for shared reflection, it has considerable implications for the nature of learning activities and teaching styles employed.

Implications for teaching While different models of cognitive development have been posited, they lead to many of the same recommendations for psychology teaching in the university context: • Recognise that individual differences in student learning are inevitable; • Focus on the process of students’ thinking, not just its products; only when you appreciate students’ methods of arriving at particular conclusions will you be in a position to provide appropriate learning experiences; • Utilise learning materials and activities that involve the appropriate level of mental operations for students’ current cognitive capabilities; • Exploit adult learning advantages – i.e., use active learning techniques, find materials that reflect student interests, experience and knowledge, build on previous knowledge and skills developed in real life situations, and involve students in the planning and evaluation of their instruction; • Use learning activities and situations that challenge students and require adaptation; scaffolding can assist students to learn how to deal with tasks; • Use examples based on familiar situations (e.g., shopping), before moving onto less familiar contexts (e.g., conducting an experiment); • Discourage students from simply telling stories as a way to make an argument. For example, many students will try to prove their arguments by giving a case study or example from their own experiences (which is not representative); • Provide opportunities for the development of creativity; and • Encourage collaborative learning, and urge students at different levels of performance to help each other learn.

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Student diversity While general processes of development can help instructors match what they teach to the needs of the student, each student is an individual, with a unique combination of abilities and characteristic styles. These differences are important since they can give educators ideas about how to adapt learning experiences for each student’s particular needs. The following subsection of this report highlights some of these individual differences and how they may impact on teaching.

Intelligence and reasoning Traditionally, it has been assumed that the most important factor in learning is inherited or natural intelligence, recognising that motivation, persistence, and other similar factors are important as well. Recently conceptions of intelligence have changed dramatically, however, reflecting the view that among the important components of intelligent activity are cognitive functions that are largely learned, not inherited, and that intelligence is multidimensional and dynamic. This review will now present some general theories of intelligence and their implications for teaching in psychology.

Guilford’s structure of intellect theory Guilford’s (1959) structure of intellect model describes human intellectual functioning in terms of three main aspects: operations, products, and content, with all abilities involving a combination of these three aspects. Because there are five operations, six types of product, and five different kinds of content, there are theoretically 150 distinct human components of intelligence or abilities. Operations (the major intellectual processes of cognition, memory, convergent thinking, divergent thinking, and evaluation) are applied to content (cognitive information which can be visual, auditory, symbolic, semantic, or behavioural) to yield a product (the results of processing information, describable as units, classes, relations, systems, transformations, and implications). Essentially, reasoning skills (convergent thinking), problem-solving skills (divergent thinking), memory operations, decision-making skills (evaluation operations), and language-related skills (cognitive operations) can be subdivided into 30 different abilities or skills. Guilford researched and developed a wide variety of tests to measure the specific abilities predicted by his theory, which provide an operational definition of the many abilities proposed by the theory.

Sternberg’s triarchic theory of successful intelligence Sternberg’s (1985, 1996) theory of intelligence describes intelligence as a balance among selecting, changing and adapting to real contexts, with those who are successful in adapting to the world and having control over it having successful intelligence as opposed to psychometric intelligence. This view of intelligence is triarchic or threefold in nature, in that successful intelligence requires analytic abilities, creative abilities, and practical abilities (which often require the use of tacit knowledge, implicit knowledge that cannot easily be put into words). Intelligence also requires metacognition or ‘executive’ processes, which control the strategies and tactics used in intelligent behaviour (see page 37). According to the theory, successful intelligence is defined by the sociocultural context in which it takes place, and involves adaptation to the environment, selection of better environments, and shaping of the present environment, through a balance of analytical, creative and practical abilities. These abilities are each taught and assessed differently.

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Problem:

Promoting performance

Context:

General psychology

Theory:

Sternberg’s triarchic model of intelligence

Sternberg, Torff and Grigorenko (1998) report that secondary school students taught a tertiary-level psychology subject triarchically performed better than did those taught with traditional instruction (primarily memory-based) or critical thinking instruction (primarily analytically-based). Triarchically taught students did better not only on performance assessments (when they were asked to analyse, create, and apply), but also on standard memory-based multiple-choice items. According to Sternberg and colleagues, teaching triarchically helps students to encode information in multiple ways, making it easier to retrieve (see page 40), and helps students to capitalise on their strengths and weaknesses. Sternberg, Ferrari, Clinkenbeard, and Grigorenko (1996; Sternberg, Grigorenko, Ferrari, & Clinkenbeard, 1999), again using high school students taught college psychology, found that if students were taught in a way that at least partially matched their pattern of abilities, their performance on tests of achievement (multiplechoice memory, analytical, creative, and practical) was better than if there were a mismatch between teaching, assessment and ability.

Gardner’s multiple intelligences Gardner (1983, 1993, 1998) suggests that we have not one but at least seven, probably eight, and perhaps even ten largely unrelated kinds of intelligence: logical-mathematical, linguistic, musical, spatial (pictures and images), bodily-kinaesthetic, interpersonal, and intrapersonal (self-knowledge) – and probably naturalist, and possibly spiritual and existential intelligences. These intelligences represent not only different content domains but also learning modalities. Gardner also emphasises the cultural context of multiple intelligences, pointing out that each culture tends to emphasise particular intelligences. While there is no direct empirical support for the theory, Gardner (1983) presents suggestive evidence from many domains, including biology, anthropology and the creative arts. According to Gardner, students need all these intelligences to deal with problem-solving, so assessment of abilities should measure all forms of intelligence, not just linguistic and logical-mathematical. Learning and teaching should focus on the particular intelligences of each person, encouraging individuals to use their preferred intelligences in learning, and educators should use a variety of instructional activities appealing to different forms of intelligence.

Student learning styles Each person has a personal and unique learning style, their characteristic and consistent approach to organising and processing information, and preferences for how they like to learn and the pace at which they learn. The purpose of learning styles research is to identify clusters of people who use similar patterns for perceiving and interpreting situations, and use this information to adjust educational environments to make them more efficient and successful. In addition, research suggests that learning styles are not fixed and deterministic, but can be modified over time and for different purposes in different classroom contexts. As a number of authors have noted (e.g., Montgomery & Groat, 1998; Rayner & Riding, 1997), a large number of taxonomies of learning styles and instruments used to measure them have been developed. In an attempt to make some sense of the research, Curry (1987, 1990) suggests there are four types of learning style model: personality models (focusing on 19

how differences in personality shape orientations towards the world); information-processing models (how information-processing preferences affect learning); social interaction models (considering ways in which students in specific contexts will behave in the classroom); and instructional and environmental preferences. One of the earliest personality approaches is Witkin’s (1962) field independence-dependence approach, which focuses on an individual’s ability to ‘disembed’ their perception from the effects of context. Field-dependent students prefer interpersonal interactions such as those found in social sciences and humanities, while field-independent students prefer areas involving analytic skills, suggesting they would learn best where environments favour these styles. The Myers-Briggs Type indicator (Myers, 1993; Myers & McCaulley, 1985) is another well-known personality model. Information-processing models include Kolb’s (1984) approach to experiential learning (see page 30), in which he maps out four quadrants and shows how they can serve as stages of holistic learning (individual styles are seen as particular strengths in the process). Honey and Mumford (1988) identified the reflector (who reflects on concrete experience and likes a range of options), the theorist (who reflects on data and information in a systematic way), the pragmatist (who likes to get results, is independent, and practical), and the activist (who enjoys active learning, is interactive and experimental), arguing we prefer to learn in one or two of these ways. Anderson and Adams (1992) focus on analytical versus relational learners, arguing that analytical learners tend to focus on sequential details rather than the overall structure, while relational learners tend to relate all of the information to the overall structure and focus on the interactions involved; some evidence exists that white females tend to have a more relational learning style, while white males are more analytical. Other models include Gardner’s (1983, 1993, 1998) theory of multiple intelligences (see page 19), and Pask’s (1976) taxonomy of serialist (who like to progress through learning step by logical step), holistic (who like the big picture before getting to the details) and versatile learners. Social interaction models include Perry’s (1970) model of intellectual and ethical development through the college years, and Belenky, Clinchy, Goldberger and Tarule’s (1986) women’s ways of knowing, which posits that women prefer different strategies to those recognised and rewarded in typical universities. Instructional preference models include that of Dunn and Dunn (Dunn, 1984; Dunn, Beaudry, & Klavas, 1989; Dunn, Dunn, & Price, 1985), which identifies five dimensions of student learning style preference (environmental, emotional, sociological, physiological, and psychological). Many university departments and educators are actively using the idea of learning style. For example, Smith and Woody (2000) reported an interaction between class format (traditional versus multimedia) and student learning style, with multimedia particularly benefiting students with a high visual orientation. However, the evidence for learning styles is not strong; learning style does not appear to account for much variance in students’ performance. In addition, many of the elements focused on are fairly basic psychological processes, suggesting that the concept of learning styles itself may be somewhat unnecessary.

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Student approaches to learning Approaches to learning can refer to the process adopted prior to the outcome of learning, as originally proposed by Marton and Saljo (1976), or it can refer to predispositions to adopt particular processes, how students report they usually go about learning (Biggs, 1987). In either meaning, an approach to learning has three components: how one approaches a task, the strategy used, and the motive for approaching it in the first place. There are three common approaches to learning – surface, deep and achieving – based on differing conceptions of learning (Marton, Dall’Alba, & Beaty, 1993; Saljo, 1979), and measured by the Approaches to Study Inventory (Entwistle & Ramsden, 1983; Newstead, 1992a; Richardson, 1992a) or, more recently, the Approaches and Study Skills Inventory for Students (Entwistle, Tait, & McCune, 2000). The surface approach has an extrinsic motive, with the task carried out because of either positively – or negatively – reinforcing consequences such as a high mark or failure in a subject. Surface-motivated students focus on what appear to be the most important topics (as defined by examinations) and reproduce them, with rote learning a typical surface strategy. Because of this focus, they do not see interconnections between elements, or the meanings and implications of what is learned. The deep approach is motivated by intrinsic motivation or curiosity, and focuses on the learning process. There is a personal commitment to learning, which means that the student relates the content to personally meaningful contexts or to existing prior knowledge, depending on the subject concerned. Deep processing involves processes of a higher cognitive level than does rote learning: searching for analogies, relating to previous knowledge, theorising about what is learned, and deriving extensions and exceptions. The achieving approach, like the surface approach, is focused on the product, the ego-boosting effect of obtaining high marks and winning prizes. The general strategy is thus to maximise the chances of obtaining high marks. While this (hopefully) involves optimal engagement in the task (like the deep strategy), such engagement is the means not the end (unlike the deep strategy); the nature of the engagement really depends on what earns the most marks. While at any given time surface and deep approaches are mutually exclusive, an achieving approach may be linked to either. Surface achievers, for instance, systematically learn selected details by rote to obtain high marks. Deep achievers, who often are the better students, are organised and they plan their search both for meaning and for high marks. There are two main influences on the student’s development and choice of a certain learning approach: personal factors and the teaching context. On the personal side, some factors in the student’s background or personality seem to be associated with a surface approach (Biggs, 1989) and others with a deep approach (Biggs, 1987). On the teaching side, time pressures, examination stress, and using test items that emphasise low-level cognitive outcomes encourage a surface approach (Norton, Tilley, Newstead, & Franklyn-Stokes, 2001; Ramsden, 1985). By contrast, learner activity, student-student interaction, and interactive teaching, particularly problem-based teaching, encourage a deep approach (Baillie, Porter, & Corrie, 1996; Biggs & Telfer, 1987; Clibbens, 2000). As with student learning style, a student’s learning approach can vary by subject, but can also entirely change. However, such change may require some metacognitive awareness and reflection (see page 37), as well as awareness-raising (Norton & Crowley, 1995).

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Problem: Fostering deeper approaches to learning Context:

Learning skills course

Theories: Approaches to learning Norton and colleagues (Norton & Crowley, 1995; Norton & Dickens, 1995; Norton, Scantlebury, & Dickens, 1999; see Norton, 2001a, for some of the course materials) developed a learning intervention course called Approaches to Learning, which ran in psychology at Liverpool Hope. This aimed to teach students about approaches to learning, and to foster deeper approaches to learning. Norton and colleagues reported that while there was a problem with student attrition, which might suggest some selfselection of more committed students, when Psychology students attended the whole course the intervention had significant beneficial effects on academic performance.

Need for cognition An individual difference that may have some relationship to learning style and approach to learning is need for cognition (NFC; Cacioppo, Petty, Feinstein, & Jarvis, 1996). This is a tendency for people to seek, acquire, think about and reflect back on information to make sense of it, rather than to rely on others and use heuristics (cognitive shortcuts). In their metaanalyses, Cacioppo et al. found that ‘cognisers’ (those high in NFC) substantially outperformed ‘cognitive misers’ in recalling information they had studied, were more likely to assess arguments for substantive merit and engage in scrutinising information, were more likely to be metacognitively aware of cognitive effort spent (see page 37), and in general were more likely to engage in metacognitive control to correct initial misperceptions or biases. Need for cognition seems a good candidate for inclusion as a pervasive yet probably tacit dispositional individual difference that affects metacognitively guided studying.

Creativity While most educational processes involve honing in on a single correct answer – convergent thinking – Guilford (1950) identified the need for divergent thinking, the ability to find different answers or solutions, also known as creativity. Creativity can be seen as the coming together of a number of different processes, rather than a single general ability. While Guilford saw creativity as involving fluency, flexibility, and originality, more recent research such as that of Sternberg (1999; Sternberg & Lubart, 1995) finds that other factors, such as general ability, personality, domain knowledge, thinking style, and motivation, each predict performance on creative tasks. Although current research into creativity varies about the nature of creativity (e.g., Finke, Ward, & Smith, 1992; Sternberg, 1988), there is some agreement that the creative process involves the application of past experiences or ideas in novel ways. For example, Finke et al.’s (1992) Geneplore model sees creativity as having two key phases. In the generative phase, a range of normal cognitive processes (e.g., retrieval, associations, synthesis) operate and can result in pre-inventive structures such as mental images, combinations of verbal information, exemplars and so on. In the exploratory phase such structures are explored and interpreted to assess their creative possibilities, or the process can be repeated to consider more structures and possibilities. The model also emphasises that the overall process involves considering functional constraints on what is needed and the usefulness of what is arrived at.

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Such models of creativity imply that students’ creativity can be fostered if they are encouraged to use these types of techniques and processes (e.g., Macaranas, 1982; Pike, 2002). On the basis of her research into creativity, Amabile (1996) suggests that it may be valuable to train individuals in the use of creativity heuristics that guide problem-solving and invention, such as rearranging or juxtaposing elements of a problem; brainstorming; making the familiar strange and the strange familiar; and generating hypotheses by using analogies, accounting for exceptions, and investigating paradoxes.

Implications for teaching While different models of intelligence and learning differences have been posited, they lead to similar recommendations for psychology educators: • Assist students in becoming aware of and exploiting their differences in strategies and styles, as this can empower them; • Consider modifying one’s teaching style to fit a broader range of students, which requires being self-reflective about one’s pedagogical goals and strengths in teaching. Options include different social groupings, alternative activities, more complex projects that incorporate all styles, and the use of communication and information technologies; • As the reality is that it is impossible to cater for individual differences to a huge extent in HE, remember that not all learning style preferences are always useful in all contexts in helping learners reach their learning goals; • Gradually introduce class activities that stretch student capabilities in order to help them accommodate a greater variety of styles; • Attempt to foster in students more complex abilities, such as those involved in divergent thinking, evaluating, arriving at implications, and responding practically to the world; • Make clear the links between required intellectual performance and real world behaviour in context; and • Provide explicit instruction in strategies for coping with novel tasks and situations.

Personality As educators know, student personality can have a substantial impact on behaviour in the educational context. Some of the research evidence for this is reviewed below.

Trait approaches Personality theories have the potential to illuminate psychological teaching as well as research. Research into academic success reveals significant correlations between a number of personality traits and academic success. For example, Wolfe and Johnson (1995) found that conscientiousness was a significant predictor of college entrant marks, and in general unstable introverts tend to do better in higher education, possibly because unstable students are more motivated to work (Anthony, 1983). Certain personality factors may also correlate with success in certain subjects, with Entwistle (1972) finding that high performing social science students (e.g., psychology students) were intermediate on both extraversion and stability, contrasting with stable introverts (best at natural sciences or history) and unstable introverts (best at engineering and languages). Such findings suggest that it may be useful to incorporate measures of such traits into academic and vocational counselling. Another personality trait that has been shown to be of relevance to education is selfmonitoring, the extent to which people monitor (observe, regulate, and control) the public appearances of self they display in social situations and interpersonal relationships (Snyder,

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1974). Self-monitoring is a proposed explanation for why we sometimes do not behave in ways that are consistent with our attitudes – those high in self-monitoring may be more influenced by behavioural cues within the social context than by their own attitudes and beliefs (Snyder & Swann, 1976). This conception of self-monitoring is similar to that of selfconsciousness (Fenigstein, Scheier, & Buss, 1975), with high self-monitors high in public selfconsciousness and low self-monitors high in private self-consciousness. According to Snyder, self-monitoring is an individual difference, and he therefore constructed and validated a scale to measure this (Snyder, 1974). However, regardless of level of self-monitoring, Snyder and Kendzierski (1982) found that when the relevance of people’s attitudes in a particular situation is highlighted to them, people are more likely to behave in ways that are consistent with their attitudes than if the relevance of their attitude is not highlighted. Problem: Increasing responsibility and improving performance within the classroom Context:

Introductory psychology

Theories: Self-monitoring research Waehler, Kopera-Frye, Wiscott and Yahney (1999), in an introductory psychology course, manipulated students’ self-monitoring through the use of journals to enhance self-awareness, and found that in the self-monitoring condition students achieved higher test scores and engaged in fewer disruptive behaviours – essentially, they were more responsible within the classroom, presumably behaving in ways consistent with their attitudes and values as well as with classroom norms. Similarly, Light, McKeachie and Lin (2002) found that, when psychology students’ self-monitoring was enhanced during an exam by instructing them to self-score the adequacy of their answers, their performance was significantly better than that of students in the control condition.

As with student learning style, which in some cases may be personality-related (see page 20), students may benefit from the opportunity to assess themselves on various personality scales that have some predictive relationship with academic success and/or preference for particular learning activities.

Theoretical approaches More theoretical approaches to personality, such as humanistic or person-centred psychology (e.g., Rogers, 1969; Rogers & Freiberg, 1994), may also be useful in informing teaching practice in HE. Unlike trait theories of personality, which are relatively rigid, humanistic psychology enables educators to emphasise the possibilities and processes of change in the way students and educators learn things and behave. According to this approach, people have inbuilt potentialities, which can be realised both through personal therapy and education, so as to promote personal renewal and socialisation. The fully functioning person, who is able to live fully in and with their feelings and reactions and is open to a range of their own needs and external demands, is constructive and trustworthy. This has implications for education, in that the learner is actively and naturally promoting their own best development in socially harmonious ways. According to Rogers (1969; Rogers & Freiberg, 1994), when the individual is fully themselves, they cannot help but be realistically socialised, as the need to be liked by others and the tendency to give affection are as strong as the impulses to strike out and seize for oneself.

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A key element of humanistic psychology, facilitation, has permeated through experiential approaches to learning such as student-centred learning, role modelling, apprenticeship and reflective practice. Facilitators help learners get in touch with their internal capacities to learn and to make sense of their experiences, value such experience and make it the basis on which other types of learning occur. The principle of holistic education is central to both parties in facilitation, embracing and affirming complexity, inclusion and diversity and resisting reductionism. Another more theoretical personality approach that has been utilised in HE (Provost & Anchors, 1987) is the Myers-Briggs Personality Type, which is based on Jung’s (1971) personality theory. Jung observed that people tend to behave in predictable ways, what he called ‘types’. Each type varies on a number of personality dimensions, three of which he identified: extroversionintroversion, sensing-intuition and thinking-feeling. His work was expanded by Myers-Briggs and Briggs (Myers, 1993), who added a fourth dimension – judging-perceiving – and developed the Myers-Briggs Type Indicator (Myers & McCaulley, 1985). Within education, the Myers-Briggs Type tends to be utilised as a learning style, which can be used to help students determine their strengths and weaknesses in learning (see page 20). Jensen (1987) suggests that lecturers themselves become aware of their personality type, and continue predominantly to teach consistently with their type – according to Jensen, Jung referred to teachers falsifying their type as “educational monstrosities” (p. 188) – but to add some flexibility. Thus, introverted lecturers could provide more time for class discussion, intuitive ones include more facts (though concentrate on theories and concepts), thinking lecturers praise as well as challenge, and so on. Problem: Fostering understanding and application of personality theories, fostering self-actualisation Context:

Personality psychology

Theories: Jungian Type theory, humanistic psychology Ware (2001) uses Jungian Type theory (the Myers-Briggs Personality Type) to teach a senior-level personality theory course, employing the theory in every element from the writing of the syllabus and conduct of the class, to the ways of evaluating learning and students’ evaluation of the course. Smith and McIntosh (2001) offered a course in humanistic and transpersonal psychology, as part of a traditional undergraduate curriculum, and found that scores on Shostrom’s (1964) Personal Orientation Inventory (which aims to measure values and behaviours of importance in the development of the self-actualising individual) provided evidence that students grew in self-actualisation after taking the course.

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Implications for teaching Several recommendations for teaching practice emerge from the literature on personality: • Try to enhance students’ self-monitoring through the use of activities such as educational attitude scales, reflective journals and self-evaluation; • Consider incorporating measures of personality traits or types that are good predictors of academic performance into academic counselling and student self-assessment activities (e.g., personal development planning); and • Reflect on the impact of your own personality on your teaching and your relationship with students.

Cross-cultural differences While the same basic principles of learning, motivation and effective instruction apply to all learners, variations in language, ethnicity and race can all influence learning. Research into crosscultural psychology (whether focusing on differences between cultures, and/or between a dominant culture and subcultures in the same community) has the capacity to have a great impact on psychology teaching in HE. For example, research shows that for Hmong tribespeople from the mountains of Laos, who are used to working cooperatively and to looking to their educators for direction and guidance, ways of working that emphasise self-directedness and internal locus of control will be experienced, initially at least, as dissonant and anxiety-producing (Podeschi, 1990). However, their liking for materials focusing on personal concrete experience fits well with experiential approaches to learning. Other research (e.g., Earley, 1989) shows that social loafing within small groups is not as likely or as a great a problem in more collectivist cultures as opposed to individualistic ones such as the UK. Cross-cultural research reveals that careful attention to ethnicity and other factors in the instructional setting enhances the possibilities for designing and implementing appropriate learning environments. When learners perceive that their individual differences in abilities, backgrounds, cultures and experiences are valued, respected and accommodated in learning tasks and contexts, levels of motivation and achievement are enhanced. One way of fostering this perception, and thereby enhancing student performance and comfort, is the use of educators drawn from their own ethnic communities – ‘teaching their own’ is a common theme surfacing in case studies of multicultural learning (Brookfield, 1986; Podeschi, 1990). Cross-cultural issues in psychology teaching are focused on in Collingridge (1999), who discusses teaching international students, and suggests some solutions for overcoming various barriers; Gloria, Rieckmann and Rush (2000), who present pedagogical concerns and strategies for lecturers teaching ethnic- or culture-based courses in psychology; and Hill (2000), who discusses ways to incorporate a cross-cultural perspective into psychology curricula. The challenges of teaching in another country, and strategies for adapting instruction to address the pedagogical obstacles, are specifically addressed in Sommer and Sommer (1991), Miserandino (1996), and Shatz (2000). Problem: Fostering diversity Context:

General psychology

Theories: Cross-cultural psychology, social learning theory Wheeler, Ayers, Fracasso, Galupo and Rabin (1999) discuss the challenges faced in devising and teaching a curriculum based on cross-cultural psychology, and provide specific strategies for creating and sustaining a diversity-sensitive classroom climate. They present a technique based on modelling appropriate diversity-sensitive behaviours that involves the use of language and course content to model respect for several forms of diversity. 26

Implications for teaching Research into cross-cultural psychology leads to a number of recommendations for teaching, including: • Try to accommodate cross-cultural diversity in learning tasks and assessment practice, and model respect for and valuing of such diversity in interactions with students; • Question your theories and assumptions regarding the universality of learning and other theories, and if possible explore this practice with people from non-dominant ethnic groups; and • Encourage your department or school to employ staff drawn from major ethnic subcultures in your community.

Learning and thinking One of the most relevant bodies of psychological research to teaching is that of learning and thinking, with a number of theoretical approaches taken to these topics over time. The following subsection of this report explores some key approaches, and their implications for teaching practice.

Behaviouristic approaches Thorndike’s (1906, 1932) connectionist or trial-and-error learning theory assigns an important role to both practice and rewards in bringing about learning. In the absence of previous learning, behaviour will take the form of trial-and-error, with attempted responses affected by readiness (due to maturation, previous learning and motivation), set or attitude (i.e., preexisting tendencies to react in given ways, which can be affected by culture), experience with analogous settings, classical conditioning, or significant elements in the situation. Those behaviours that lead to a satisfying state of affairs will be strengthened and become more likely to reoccur in that situation – they have been ‘learned’. Such connections become strengthened with practice and weakened when practice is discontinued. Teaching is therefore a matter of shaping the responses of the learner through using instructional procedures such as modelling, demonstration and reinforcement of closer approximations to the targeted response. Transfer of such learning depends upon the presence of identical elements in the original and new learning contexts – i.e., transfer is always specific, never general. In comparison with Thorndike’s form of behaviourism, reinforcement is the key element in Skinner’s (1953, 1954) operant conditioning theory – not just the type of reinforcement, but also the schedules of reinforcement and their effects on establishing and maintaining behaviour to be learned. According to Skinner, behaviour that is positively reinforced will reoccur (e. g., Tuckman, 1996b), with intermittent reinforcement such as the use of unannounced quizzes particularly effective (Connor-Greene, 2000; Graham, 1999; Ruscio, 2001; Thorne, 2000). Information should be presented in small, gradual steps, in the form of question and answer frames, so that responses can be reinforced (shaping). Educators should require that the learner make a response for every frame, and ensure they receive immediate feedback and that good performance in the lesson is paired with secondary reinforcers such as verbal praise, prizes and good marks (Skinner, 1968). If possible, the difficulty of the questions should be arranged so that the response is always correct and hence gains positive reinforcement. In many cases the most effective reinforcer of a behaviour is the pleasure inherent in engaging in it – the subject has enough intrinsic incentive value to motivate learning. Intrinsic 27

reinforcers of this type can be distinguished from extrinsic reinforcers, reinforcement given to motivate people to engage in behaviour in which they might not otherwise engage. There is some evidence that reinforcing people for behaviours that they would have done without reward, where rewards are provided regardless of standard of performance, can undermine long-term intrinsic motivation. However, for most tasks there is little basis for concern that use of extrinsic reinforcers will undermine intrinsic motivation. Problem: Promoting learning Context:

Undergraduate psychology

Theories: Conditioning theory Heckler, Fuqua and Pennypacker (1975) investigated the role of fading in college student learning. They compared the use of fading (gradually changing one stimulus controlling performance to another stimulus, in this case by reducing the amount of direction) for teaching complex verbal statements, with learning by a non-fading method, and with learning through trial-and-error (the control condition). Learning under the fading procedure was significantly better than in the other conditions. Using a computer programme, Renkl, Atkinson and Maier (2000, Experiment 2) utilised a similar technique (successively introducing more and more elements of problem-solving into a series of example problems, until learners were solving whole problems on their own). They found that fading fostered learning when compared to an example problem condition (where learners were exposed to worked examples followed by similar problems to be solved). This effect appeared to be due to a lower number of errors in solution steps in the fading condition than in the example problem condition.

The instructional model that best reflects the tenets of behaviourism is referred to as direct instruction. The hallmark of direct instruction is the active and directive role assumed by the educator, who maintains control of the pace, sequence and content of the lesson (Baumann, 1988). In direct instruction, academic tasks are analysed to determine their component parts, and the curriculum is carefully sequenced to ensure that students acquire the necessary prerequisite skills before the introduction of more advanced material, with students provided with much feedback, distributed practice and review. Examples of direct instruction include teaching machines, programmed instruction (individualised instruction methods in which students work on self-instructional materials at their own levels and rates) and simple computer-based teaching methods such as drill-and-practice programmes.

The personalised system of instruction The personalised system of instruction (PSI, also known as the Keller Method; Keller, 1968, 1974, 1985) is an instructional approach based on behavioural analysis principles. It was designed to utilise what was known about the functional relations between behaviour and the environment, and is based upon what was known about student behaviour as it is maintained by contingencies of reinforcement. The basic features of PSI include: • The go-at-your-own-pace feature, which permits students to move through the course at a speed suitable for their ability and time demands (Carroll, 1963); • The unit perfection requirement for advancement, which lets the student advance to new material only after demonstrating mastery (similar to Bloom’s (1968, 1971) mastery learning); • The use of lectures and demonstrations as vehicles of motivation rather than as sources of critical information; 28

• The related stress upon the written word in educator-student communications; and • The use of proctors (teaching assistants), to give quizzes and tests, which permits repeated testing (which can be of any form, not just true/false or multiple-choice), immediate scoring, almost unavoidable tutoring, and, it was claimed, an enhancement of the personal-social aspect of the educational process. Unlike in traditional instruction, students work through a series of modules at their own pace, focusing on the textbook and individual work-through study guides (including objectives, study procedures and questions), rather than a lecture (which is generally not given). As students complete a module they are tested, and immediate and personalised feedback provided by the proctor, with an opportunity to review and retest. Lectures are limited, providing for interaction and motivation more than content-dispensing. Although PSI was devised in the 1960s, educational technologies allow similar systems to be designed and efficiently delivered today, with computer-based or internet-based modules allowing richer resources to be provided. PSI has been reviewed in a number of contexts, including Reboy and Semb (1991), and Buskist, Cush and DeGrandpre (1991). Kulik, Kulik and Cohen (1979, 1990) conclude, based on meta-analysis of data from more than 300 studies, that PSI is an effective form of instruction if used in a form similar to that devised by Keller. The research regarding direct instruction suggests that while it is an effective means of teaching factual content, there is less evidence that this instruction transfers to higher-order cognitive skills such as reasoning or problem-solving. Meta-analysis (Guskey & Pigott, 1988; Kulik, Kulik, & Bangert-Downs, 1990), as well as less systematic reviews (Slavin, 1987), reveals that, by itself, mastery learning is reasonably effective. Enthusiasm for PSI has diminished for a number of reasons, including the greatly increased workload; the change in required lecturers’ behaviour from didactic educator to manager of student learning; the different use and meaning of marks, which may confuse administrators and lead to inflation of marks; the impact on subsequent units or modules; and increased enrolments. However, the major problem encountered, as PSI was popularised, was poorly designed and often pre-packaged materials being labelled PSI. PSI materials should be constructed by those with a full understanding of the basic principles of operant conditioning. However, many teaching machines were not designed in this way, but were poorly constructed. In addition, the acquisition of higher-order thinking skills was not explicitly a part of the model, which focused on lower-order knowledge acquisition.

Problem: Accommodation to individual needs Context:

Introductory psychology

Theories: Behavioural theory Brothen, Wambach and Hansen (2002) describe a PSI system for an introductory psychology course, incorporating computers, that makes accommodation to students’ individual needs, including those of students with disabilities.

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Implications for teaching Research into behaviourism leads to a number of recommendations for psychology educators: • Carefully consider students’ pre-existing attitudes and readiness before beginning to teach them; • Teach for generalisation of learning by stressing connections among ideas, reinforcing desired outcomes, and encouraging practice; • Decide what behaviours are wanted and reinforce these and only these; • Tell students what behaviour is wanted, and why these desired behaviours are being reinforced; and • Reinforce appropriate behaviour as soon as possible after it occurs, as delayed reinforcement is less effective than immediate reinforcement.

Experiential approaches Experiential methods of teaching and learning have existed from ancient times. What is new is not so much the methods, but their acceptance in mainstream contemporary education. The modern philosophical base that gave rise to experiential learning practice in HE since the 1970s has its origin in Dewey’s (1938) progressive education, education of the whole person through experience, involving the education of equals, changes in self-concept, readiness to learn, and a problem-centred orientation to learning. With the humanistic approach to psychology, experiential learning was rediscovered and formalised by Rogers (1969), who was also influenced by his experiences as a psychotherapist. The assumptions underlying experiential learning that Rogers (1969; Rogers & Freiberg, 1994) identified, on the basis of humanistic learning theory, are that: • Human beings have a natural potentiality for learning; • Significant learning takes place when the subject matter is perceived to be relevant by the student; • Much significant learning is acquired through doing; • Learning is facilitated when the student participates responsibly in the learning process; • Self-initiated learning, involving the whole person of the learner, feelings as well as intellect, is the most pervasive and lasting; • Creativity in learning is best facilitated when self-criticism and self-evaluation are the primary means of assessing progress or success, and evaluation by others is of secondary importance; • Learning proceeds faster when threat to the self is low; and • The most socially useful learning in the modern world is learning the process of learning, a continuing openness to experience and incorporation into oneself of the process of change. These educational principles come alive with the use of Kolb’s experiential learning cycle (Kolb, 1984; Kolb, Rubin, & McIntyre, 1971). This is a useful shorthand to describe the experiential learning process. It describes a sequence of four stages (concrete experience; reflective observation; abstract conceptualisation; and active experimentation; leading back again to concrete experience and so forth), arguing that we make sense of concrete experiences by reflecting on them, developing our ideas, and then acting on the basis of our new learning. According to Rogers, the role of the educator is to facilitate such learning, by setting a positive climate for learning, clarifying the purpose of the learning, organising and making available learning resources, balancing intellectual and emotional components of learning, and sharing feelings and thoughts with learners, but not by dominating.

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Currently, experiential learning tends to be used as an umbrella term for a range of related approaches to learning: active learning, learning-by-doing, action learning, humanistic learning, holistic learning and so on. The focus on individual learners rather than on the learning material itself emphasises the holistic nature of learning, and while different learning cycles are identified in various perspectives, each emphasises the central notion that experience is the key to learning and personal control. However, its ubiquitous nature belies its underlying complexity; despite considerable academic research and practical inquiry, it is an area of learning that remains little understood (Markee, 1997). Yet as with any other learning approach, if it is to be effective it needs to be well-organised and purposeful, grounded in an understanding of learning processes.

Active learning Research into memory (see page 39) shows that information that is deeply processed, elaborated, organised and connected to pre-existing knowledge is better recalled. By fostering such processing of information, active learning – in which students work things out for themselves and participate in discussions, activities and projects that require understanding of and application of course material – has been shown in a number of psychology teaching studies to improve learning, memory and performance (e.g., Baillie, Porter, & Corrie, 1996; Butler, Phillmann, & Smart, 2001; Clibbens, 2000; DeNeve & Heppner, 1997; Dolinsky, 2001; Falchikov, 1995; Hinkle et al., 2001; Kellum, Carr, & Dozier, 2001; Kreiner, 1997; Kremer, 1997; Perry, Huss, McAuliff, & Galas, 1996). For example, Birchmeier and Bakker (2002) found that, in comparison to students enrolled in a traditional section of a psychology course, students in the active learning section perceived material to be more valuable and reported marginally higher levels of motivation, with levels of active engagement predicting motivation and perceived learning outcomes. Problem: Promoting learning Context:

Social psychology

Theories: Active learning principles Integrating internet technology and the principles of active learning, Sherman (1998) suggested that students in advanced courses should develop web-based learning modules to be used in the instruction of beginning students, and that these beginning students should review the modules in progress, providing online and face-to-face feedback to the advanced students and active learning for both beginning and advanced students. Sherman and colleagues (Hinkle et al., 2001; Wolfe, Crider, Mayer, McBride, & Sherman, 1998) implemented this process with advanced and beginning social psychology students, Hinkle et al. requiring students in advanced social psychology courses to produce modules on various topics in social psychology. These modules were presented to beginning social psychology students as an instructional tool. Results indicated that beginning students devoted significant time and consideration to the internet materials, and evaluated them and the learning process favourably, with a majority indicating that their understanding of the internet material was better than or comparable to that gained by studying a textbook. The students also manifested significantly increased learning. These findings were not qualified by students’ gender, class standing, computer use experience, or attitudes towards computer use.

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However, despite the clear evidence for the effectiveness of active learning, Gale (1990a) points out that the standard approach to teaching psychology at discipline level – which even 10 years on is still dominated by lectures and other didactic teaching techniques – is likely to produce students who are largely passive learners, at least at undergraduate level.

Problem-based learning Problem-based learning (PBL) is one specific active learning technique that has often been used in psychology, and can be quite effective (Vernon & Blake, 1993), with a growing body of research demonstrating that PBL can enhance transfer of concepts to new problems (Norman & Schmidt, 1992). It challenges students to ‘learn to learn’, working cooperatively in groups with guidance from the instructor to seek solutions to real-world problems. These problems are used to engage students’ curiosity and initiate learning of the subject matter. PBL prepares students to think critically and analytically, and to find and use appropriate learning resources. PBL has strong links to constructivism (see page 44), and is frequently considered to be a constructivist learning technique (e.g., Savery & Duffy, 1995). Problem: Fostering transfer of knowledge Context:

Educational psychology

Theories: Active learning principles, problem-based learning theory Cerbin (1996, 2000a, 2000b) describes his experience converting an educational psychology course to a PBL format. The course is built around complex, open-ended problems instead of being built sequentially around a series of topics. The problems are created to focus on domains of subject matter in the course, and to invite transfer of knowledge by drawing on the same subject matter in different contexts. Rather than being in control of the information and telling students everything in advance, Cerbin provides students with some reading and writing assignments in preparation for working on the problem, then responds to students’ attempts to interpret and solve the problem, providing information that is necessary to elaborate or clarify material read. As he puts it, he does “a good deal of just-in-time teaching” (p. 14, Cerbin, 2000a). When each problem is solved, Cerbin collects the work and analyses it, looking for evidence that understanding of the course material is there, and to what extent, by investigating the quality of explanations given. Unfortunately Cerbin does not report any concrete results of the intervention, so its success cannot be evaluated. The course portfolio for his course is available at Cerbin (1998). Other PBL case studies in psychology can be found in Bernstein (2002) and Hmelo-Silver (2000).

Case studies Case studies are another commonly used active learning technique. Analysing case study material promotes analytic inference and critical thinking (McDade, 1995), broadens students’ perspectives on psychological issues, fosters independent learning and facilitates in-depth understanding of material. Within psychology and other disciplines, its use correlates with positive learning outcomes such as increased student engagement, problem-solving abilities, writing skills and decision-making skills (e.g., Cabe, Walker, & Williams, 1999; Fisher & Kuther, 1997; Perkins, 1991; Witte, 1998). Leonard, Mitchell, Meyers and Love (2002) provide guidelines for implementing this technique within introductory psychology, recommending instructors determine the goals for the exercise before selecting a topic; narrow the topic area to address it appropriately in the case study; use/develop a well-written, multilayered but not

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overly complex story that contains important details so that students can engage substantively with the problem; and add an inquiry section containing a logical sequence of questions to allow students to apply their knowledge to the case.

Implications for teaching The experiential learning approach leads to a number of recommendations for teaching practice: • Support students during experiential learning by demonstrating good thinking, asking open questions, clarifying ideas, providing more information and giving feedback; • Provide students with practice in exercising and managing basic cognitive skills (metacognition), such as recognising important information, organising that information, connecting the information with what they already know, and being aware of whether information has been recognised, organised and connected; • Demonstrate a new skill yourself, before asking students to practise it; • Before a learning activity, point out what you want students to notice; • Provide structure for students to discover things on their own, by setting clearly defined learning tasks, guidance and practice in solving many different forms of problem; • Use tasks that are just challenging enough, as tasks that are too easy do not lead to learning, and those that are too hard are frustrating; and • Ensure students have the requisite background knowledge necessary for active learning by requiring them to do some initial reading, screening a video, or getting in a guest speaker.

Cognitive approaches With increased interest in human information-processing in complex cognitive activity, the cognitive perspective on learning has assumed prominence. However, there are many cognitive approaches to learning, which are summarised in rough chronological order.

Thinking and reasoning Gestalt theory Gestalt theory (Ellis, 1938; Wertheimer, 1982), which emphasised higher-order cognitive processes in the midst of the behaviourist dominance, focuses on the idea of grouping – i.e., that characteristics of stimuli cause us to structure or interpret a problem in a certain way. The primary factors that determine grouping are proximity and similarity (elements tend to be grouped together if they are close or in some way similar), closure (items are grouped together if they tend to complete some entity), and simplicity (items tend to be organised into simple figures according to symmetry, regularity and smoothness). Because of this grouping tendency, we expect to be able to see things as wholes, and violation of this expectation (such as encountering gaps, incongruities, or disturbances) requires problem-solving behaviour, an attempt to understand the overall structure of a problem. Such holistic initial impressions of objects may then impact on the interpretation of subsequent experiences with and information about the object (Asch, 1946; Kelley, 1950), and may become more resistant to change with time, essentially serving as schemata (see page 34).

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Implications for teaching Gestalt theory leads to several recommendations for psychology teaching practice: • Aim to make initial impressions of a subject or teaching experience as positive as possible, to facilitate further positive interpretations of the situation; • Encourage students to discover the underlying nature of a topic or problem (i.e., the relationship among elements) for themselves; • Highlight gaps, incongruities, and inconsistencies; and • Base your teaching on the laws of organisation: proximity, closure, similarity and simplicity.

Schema theory Schemata (also known as mental models) are complex networks of organised, interconnected information about a domain or topic, that change as we learn and gain experience in the world, and are generally considered to be the fundamental elements upon which all information-processing depends (Bobrow & Collins, 1975). Schemata are also linked to each other, reflecting connections between domains, as well as to heuristics or problem-solving shortcuts. People have remarkably similar schemata for common things and events, such as eating at a restaurant. However, schemata can vary in complexity and organisation, with experts’ schemata complex, hierarchical and highly organised, with specific information grouped under more general ideas, and novices’ schemata more simple and disorganised, even when they contain the same information as do experts’ (Alexander, 1992; Bransford & Johnson, 1972). Experts also know when to use a schema. Schemata affect information-processing in a number of ways. They make learning and memory more efficient, because information is organised (Broadbent, 1975). They set up expectations, including to what stimuli to attend, facilitate understanding, and allow inferences to be drawn from pre-existing knowledge. New information can be more effectively stored if it can be related to prior information, which facilitates subsequent recall by providing cues to memory. When connected to heuristics, schemata serve as a guide to action (Schank & Abelson, 1977). However, schemata can also interfere with thinking, by leading to less deep processing of information, biasing encoding, or interfering with recall of memories; schemaconsistent information is much more likely to be recalled than is schema-inconsistent information (Reisberg, 2001). When initial experiences lead to the formation of a negative schema (such as a negative experience in an introductory psychology class), this may influence uptake and interpretation of subsequent experiences (such as later psychology courses).

Problem: Assessment of students’ knowledge Context:

General psychology

Theories: Schema theory Jacobs-Lawson and Hershey (2002) describe the concept map, a graphic, hierarchically arranged knowledge representation that reflects the content of an individual’s schemata. They describe the basic mapping technique, a number of variations on the technique, and how teaching staff can use concept maps as an adjunct to traditional assessment in psychology and as a means of evaluating students’ knowledge both qualitatively and quantitatively. Based on the results of a comparison between students’ concept maps completed at the beginning and the end of semester, they conclude that the technique is effective at evaluating such knowledge.

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When students have trouble understanding, schema theory suggests four possible problems: • The student does not have a (good enough) schema for the topic; • The student has an appropriate schema, but the teaching/text does not provide the right cues to bring the schema to mind; • The student has retrieved a different schema from that intended by the educator; and/or • The material challenges the student’s schema, and they may need to expand the schema. Adult learners can be resistant to changing well-established schemata and may prefer not to believe or process challenging new information.

Implications for teaching Schema theory and research leads to a number of recommendations for psychology teaching: • Encourage students to engage actively in learning, since understanding depends on schemata, and it is their schemata that will lead to understanding, not yours; • Be aware that students growing up in different cultures and contexts will have different schemata; • Identify and activate students’ prior knowledge and schemata before you teach, and try to integrate new facts and knowledge into pre-existing schemata; • When students know little or nothing about the topic, provide a schema for new material in the form of a concrete, familiar and specific advance organiser (see page 43); • Limit the number of different schemata students have to use at one time. Begin with a simple schema, then add to it; • Model your own use of schemata, for example by drawing on the board/OHT to show how new information fits into an existing schema; • Begin a lesson with a mental map of the topic generated by the class. At the end of the class, add on what students have learnt, and reorganise the diagram (grouping items and concepts) if needed; • Alternatively, ask each student to draw a mental map before and after learning about a topic, as a way of testing what has been learnt and promoting reflective learning; and • Teach students about different sorts of expository prose (e.g., research reports, essays, textbooks), as many students have a model for narratives such as stories, but not for many types of academic writing (Cook & Mayer, 1988).

General cognitive skills Eysenck and Keane (1995) argue that a great deal of cognition depends upon cognitive concepts being activated and linked together in some meaningful way, and consider that this requires some key cognitive or thinking skills. There has long been a debate about whether such cognitive skills are general or specific (Cromley, 2000), with many current researchers feeling that there are very few, if any, general cognitive skills. Eysenck and Keane (1995), for example, argue that the key operations include reasoning (deductive and inductive), inference and decision-making. Many theorists also argue that such general skills cannot be taught directly, because general strategies are too general for most students to apply (Bransford, Sherwood, Vye, & Rieser, 1986). Instead, the teaching of cognitive skills is most effective in the context of real problemsolving in a specific field – what is known as situated cognition (Brown, Collins, & Duguid, 1989). In support of this, research into general cognitive skills programmes shows that they do not significantly improve students’ standardised test scores overall, but only performance on the type of problems learnt in the programme (McMillan, 1987; Perkins & Salomon, 1989).

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However, cognitive and other transferable skills training is rarely done in psychology degree courses, despite the argument that psychology courses may provide unique vehicles for such training (Arnold, Newstead, Donaldson, Reid, & Dennis, 1987; Newstead, 1990), with the acquisition of knowledge, facts and theories instead emphasised.

Implications for teaching Research into general cognitive skills leads to the following recommendations for educators: • Teach students how to solve the type of problems found in the field, within the context of that field, as well as factual knowledge about the field; and • Inform students about the specific cognitive skills they are acquiring in the course of an activity.

Biases in cognition A substantial body of research in cognitive psychology and decision-making is based on the premise that fundamental human cognitive limitations cause people not just to rely on schemata, but to employ various simplifying strategies and heuristics to ease the burden of mentally processing information to make judgements and decisions. These simple rules of thumb are often useful in helping us deal with complexity and ambiguity. Under many circumstances, however, they lead to predictably faulty judgments known as cognitive biases (Tversky & Kahneman, 1974). Within the educational context, biases in evaluation of evidence may have a particular impact. These biases include: • The availability bias (a tendency to remember and prefer more familiar material or answers, and to overestimate the prevalence of more familiar events); • The vividness bias (where information that is vivid, concrete and personal has a greater impact on thinking than does pallid, abstract information that may actually have substantially greater value as evidence); • The belief bias (coming to a favoured conclusion without looking at the evidence, which more often occurs with emotionally charged issues); and • The confirmation bias (a preference for information that confirms one’s own theories and judgements). These biases are surprisingly resistant, remaining to some extent even if individuals are informed of their existence and instructed in principles of reasoning (Evans, Newstead, Allen, & Pollard, 1994), and impressions based on such biases tend to persist even after the evidence that created those impressions has been fully discredited (Ross, Lepper, & Hubbard, 1975). Such faulty reasoning is also more likely on unfamiliar or emotionally charged topics (Reisberg, 2001). However, as mentioned, there is some evidence to suggest that pointing out students’ biased thinking can have an impact on it, perhaps at least partly due to processes of cognitive dissonance (see page 64). Sheldon (1999) suggests that educators see the confrontation of presumptions and personal biases as a secondary agenda in classroom activity. She describes a technique in which students are presented with class discussion stimuli containing ambiguous information regarding gender or sexual orientation, and then monitoring the assumptions students make with regard to such background variables during discussion.

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Implications for teaching Recommendations for teaching derived from research into cognitive biases include: • Provide students with practice in constructing arguments (e.g., providing evidence, making logical conclusions) and getting feedback on these; • Ask students to challenge the evidence – for example, by asking what kind of information could disprove what they believe; and • Ask students to take different points of view in a class discussion or exercise, particularly ones counter to their own beliefs.

Metacognition As we learn about things, so we also learn about learning. Knowledge about our own cognitive processes is known as metacognition, which has two main components: being aware of our thinking (cognitive monitoring), and controlling our thinking and learning strategies in order to change our thinking and learning (cognitive regulation) (Hacker, 1998). The skills of metacognition allow us to direct, monitor, evaluate and modify our own ongoing learning and thinking. Biggs (1985) found that while some students were not skilled at metacognition, students who were capable of metacognitive thought had high general abilities that presumably enabled them to develop and use these skills. However, these skills do not spontaneously develop for most learners, but need to be taught. Educators can foster better, more critical and more creative thinking by fostering learners’ awareness of themselves as knowers and information processors and by teaching them specific cognitive strategies to improve thinking and learning and enable independent learning. According to Vygotsky (1978), we learn to think by incorporating what we hear from others, so giving students feedback while they think out loud may be a very powerful tool to help do this. More than 150 thinking and learning strategies have been identified, and a large number of programmes have been designed specifically to develop metacognition. Such programmes utilise a variety of approaches to teaching, including group learning, individual instruction, modelling of strategies and reflective learning. The literature is replete with experiments that demonstrate gains when students are trained to use a study tactic and compared to peers who study ‘normally’, suggesting that students may be very undereducated about study tactics and strategies and may therefore benefit from direct instruction or supportive scaffolding (Winne & Hadwin, 1998). Three general reading strategies show good results, based on a large number of studies (Cromley, 2000): discussing what is already known about the topic; asking and answering questions as one reads; and summarising what one has read. These strategies work best when they are taught in a structured way using real reading materials, probably because they have students engage actively with reading and really process what is read (Davidson & Sternberg, 1998). While these strategies can take some time to teach, they can be very powerful.

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Problem: Improving examination performance Context:

Introductory psychology

Theories: Metacognition Fleming (2002) investigated whether the use of learning strategies would improve students’ exam performance. Students in one section of an introductory psychology subject were introduced to learning strategies, set individual learning goals, and recorded their learning-related behaviour during the first two units. Students in the control section engaged in non-academic tasks. All students received a lesson on learning at the end of the second unit. Students who had utilised learning strategies obtained significantly greater scores than did control students on the first two and fourth exams; on the third exam differences were not significant.

Implications for teaching Research on metacognition leads to a number of recommendations for teaching: • As reflecting on learning can be most effective when a student is new to the institution or class, consider using discussion and writing about thinking and learning early in the term or semester; • Teach only one learning strategy at a time, as each strategy may take many hours to teach and learn; • Tell students what a particular learning strategy is and why it will improve learning, and demonstrate how and when to use the strategy; • Teach strategies slowly and with many opportunities for students to practise and receive support and feedback, then teach them how to monitor whether or not the strategy is working for them; and • Consider asking students to think out loud as they solve a problem, and suggest other students ask open-ended questions and give feedback on their thinking processes.

Memory Information-processing theory Based on research into human cognition and memory, Atkinson and Shiffrin (1968) put forward information-processing theory, the dominant theory of learning and memory since the mid-1970s, which describes the processing, storage and retrieval of knowledge in the mind, and has a number of implications for teaching and learning (Bjork, 1979). In this model, information that is to be retained must first reach a person’s senses, then be attended to and transferred from the sensory register to the working memory, then be processed again for transfer to long-term memory. Memory itself seems to be made up of at least two parts: working memory (short-term memory), where information is utilised during thinking, and long-term memory, where information is stored permanently. Working memory is small, and stores information quickly, but information is also quickly forgotten, while long-term memory can store huge amounts of information but this is stored and retrieved much more slowly. Theorists generally divide longterm memory into at least three parts: episodic memory (memory of events and experiences), semantic memory (facts, concepts, scripts, problem-solving skills and learning strategies, organised into schemata; see page 34) and procedural memory (knowledge of how to do

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things), with recent brain functional imaging studies confirming that these are different processes (Blakemore & Frith, 2000). Long-term memory and working memory interact continuously, with information constantly moving back and forth between the two (Baddeley, 1998) and knowledge such as word meanings being retrieved from long-term memory when needed by working memory. However, because information must be put into working memory before it can be stored in long-term memory, one can only learn as many things at one time as can fit in working memory – it is the gatekeeper for learning. Other information cannot make it into working memory until one has processed the information that is already there. Research into working memory reveals that it includes both information and processing (thinking), and can hold a combination of either or both (Just & Carpenter, 1992), with poor readers requiring more of their working memory to decode new words rather than retaining more content. However, working memory can only hold about 7±2 items – about seven numbers, five words, or three nonsense syllables – and it only lasts for 10 to 30 seconds (Miller, 1956). An item can last in working memory for about two seconds without any work, but to keep it there longer requires rehearsal, or transfer into longer-term memory, perhaps by making connections between new information and what is already known. By organising or ‘chunking’ new information (for example, by reorganising a list into categories), or by linking it to what is already known, more information can be stored in working memory, though this depends on what is already known. Writing information down also frees up working memory. The research into long-term memory shows that encoding of information into long-term memory involves the processes of rehearsal (elaborative rehearsal, connecting the information to what is already known, rather than simple repetition or maintenance rehearsal), elaboration and organisation. As Craik and Lockhart (1972; Craik & Tulving, 1975; Lockhart & Craik, 1990) put it in their levels of processing theory (an alternative information-processing model that elaborates on some aspects of the Atkinson-Shiffrin model), memory for information reflects the level to which it has been processed. This suggests that course material that is repeatedly processed due to continuous assessment may be better retained than course material assessed through a final examination, as Conway, Cohen and Stanhope (1992) indeed found. More detailed information is easier to remember, being more distinctive, though detailed but irrelevant information can also interfere with the retention of more important ideas. Material that is meaningful, especially if it is personally relevant to the individual and/or related to their own life, is also more likely to be deeply encoded (Baddeley, 1998). Problem: Poor retention of course material Context:

Introductory psychology, cognitive psychology

Theories: Information-processing theory Davis and Hult (1997) found that summary writing during pauses in lectures – a form of generative learning which requires more detailed processing of lecture material – resulted in more durable learning than did reviewing lecture notes during pauses, or taking notes without pauses.

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In addition, according to Paivio’s dual-code theory of memory (Paivio, 1971; Clark & Paivio, 1991), information is also better remembered when it is represented in memory both visually and verbally, corresponding to episodic and semantic memory respectively. Essentially, when more paths are used to get information into memory, so there are more ways to retrieve the information when it is needed. Bransford’s transfer-appropriate processing theory (1979) also shows that the strength and durability of memory depends not only on the depth of processing, but on the similarity between the conditions under which the material was learnt and those under which it is retrieved – essentially, memory is context-dependent. This finding helps to explain why many students can recall and apply rules on a multiple-choice test but are unable to recall or apply the same skills in their own writing. According to Blakemore and Frith (2000), such material recently acquired through experience is consolidated and stored during rapid eye movement (REM) sleep; periods of learning are associated with increased REM sleep, while REM sleep deprivation impairs memory for previously learned material. Problem: Poor retention of course material Context:

Developmental psychology, psychological statistics, abnormal psychology

Theories: Paivio’s dual-code theory of memory In Erwin and Rieppi (1999), instructors taught human development, psychological statistics and abnormal psychology in either a multimedia or traditional classroom. Results showed that, although students in multimedia and traditional classes did not differ on scholastic abilities prior to enrolment, students in the multimedia class averaged higher examination scores than did those in traditional classrooms. Studies also reveal that material learnt via distributed learning – distributed across several study sessions, rather than concentrated in one session (massed learning or practice) – is better remembered than that learnt through massed practice, as it is more likely to be wellintegrated into long-term memory (Dempster, 1988, 1989; Melton, 1970; Underwood, 1974). This is especially true of factual learning. Dempster (1988) argues that even educators are under-educated about this spacing effect, and suggests that students who do not metacognitively monitor their spacing of study sessions (see page 37) may well learn less. They may also draw invalid conclusions about the utility of some study tactics by misattributing weak effects to otherwise effective tactics because they did not engage in spaced study sessions. However, unannounced quizzes are among a number of strategies that academics can use to enhance distribution of studying (Ruscio, 2001; Solomon, 1979). Research shows that information is stored in memory in an organised way, in complex networks of associations. Schemata, cognitive representations of concepts, and their characteristic and defining features (see page 34), are an efficient way to store information. When a schema is activated – for instance, through priming, exposure to a schema-related idea or item – other information related to the schema is also activated, and learnt more readily (Bransford & Johnson, 1972; Collins & Loftus, 1975). In relation to teaching, this means that students will understand better when they have a pre-reading discussion or read about familiar topics, because information is already activated in their memories. Giving students an outline before they read (an advance organiser; see Ausubel, 1963, and page 43) also facilitates recall. However, such advance organisers only work well for topics with an organised structure, and where students already know something about the topic (Mayer, 1979). 40

Students can also have problems when they cannot retrieve stored information from memory. Information that is strongly encoded (deeply processed) is easier to retrieve than that which is less strongly encoded (Bjork & Bjork, 1996). In addition, retrieving information from long-term memory makes the memory stronger and easier to retrieve later on. To retrieve information, it helps to have a cue: a prompt for memory, such as a question or reminder. When material is strongly encoded, both strong cues (e.g., questions that are the same as in the learning situation, or recognition questions) and weak cues (e.g., application questions, or open-ended essay questions) can help retrieve the information. However, with weak encoding only strong cues are effective. Cues that closely match the type of recall in question are most effective. This implies that if students are required to remember the meanings of words, then cues that emphasise meanings are best. Theories of forgetting (see Schacter, Norman, & Koutstaal, 1998) also have a number of implications for teaching. Fading theory, which suggests that information may be forgotten because it has faded or decayed through disuse, suggests that educators should provide students with a variety of opportunities to practise and rehearse what they have learnt. Distortion theory, which focuses on the fact that memories which do not entirely fade are often distorted or confused with other memories, suggests that educators should emphasise the most important and distinct (memorable) aspects of material, as highly distinct material will be more easily and more accurately remembered. Research into retroactive and proactive inhibition, which states that interference from previous (similar) or subsequent learning is an important cause of forgetting, suggests that teaching for generalisation (transfer) may reduce the effects of interference. In addition, people remember best what they hear at the beginning and end of an experience or list (primacy and recency effects), rather than what was in the middle of the experience (Glanzer & Cunitz, 1966). Research from brain injuries and other contexts show that memory skills can be improved by training – for example, in organising items by putting them into categories; relating new information to what is already known; or by remembering lists, rules or instructions using mnemonics (memory devices) such as rhymes, acronyms, key words, drawings, or visualisation (Levin & Levin, 1990). Mnemonics are often best for learning random information that really must be memorised, but can also facilitate more than just rote memorisation of facts (Carney & Levin, 1998; Carney, Levin, & Levin, 1994). Problem: Poor retention of course material Context:

Introductory psychology, psychological measurement

Theories: Mnemonics Carney and Levin (1998) provide a set of mnemonic keyword materials developed for terminology related to neuropsychology. When they compared two versions of their keyword approach to a simple repetition condition, the two mnemonic approaches elicited better results on an immediate definition memory test, as well as on a task requiring application of the material learned. Similarly, VanVoorhis (2002) investigated the effect of using music as a mnemonic device to remember statistical facts. Students in one section of the class learned and sang statistical jingles, whereas students in another section read definitions of the statistical concepts aloud. Results showed that students who learned the jingles scored significantly higher on a short-answer test related to the material, and ratings of jingle knowledge were significantly correlated with test scores.

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Connectionist models A major recent alternative to the information-processing model of memory is that of connectionism (Rumelhart & McClelland, 1986), which proposes that knowledge is stored in the brain in a network of connections, not in a system of rules or as individual bits of information. In this view, experience leads to learning by strengthening certain connections that are functional, and weakening those that are not. Such models are consistent with current research on the brain, which has established that information is distributed in many locations and connected by intricate neural pathways (Blakemore & Frith, 2000; Hendry & King, 1994). However, the implications of connectionism for teaching and learning are not clear, except to suggest that educators emphasise experience-based teaching.

Self-referencing As already described, research shows that the more elaborately material is processed, the better it is retrieved. The most elaborate cognitive framework is what people know about themselves, and this schema increases in size and complexity with age. Because how much is already known affects how easily and well a person can master new material, selfreferencing can be particularly effective in learning (Symons & Johnson, 1987), presumably because the more accessible and differentiated network permits deeper processing of information encoded with a self-referencing strategy. Problem: Improving recall of course content Context:

Introductory psychology

Theories: Self-referencing research Forsyth and Wibberly (1993), and Hartlep and Forsyth (2000), instructed psychology students in the use of self-referencing in encoding written material, and found that in comparison to students left to utilise their own study method, immediate and delayed recall of text material was superior. Similarly, Foos (2001) compared students who completed a self-referenced exercise on life expectancy with those who did not, and found significantly better performance, on a later test relating to life expectancy, in the self-reference group, even though no prior performance difference existed.

Implications for teaching Memory research leads to a number of recommendations for psychology teaching, including: • Teach the most important information at the beginning of a class to take advantage of better learning. Use the rest of the class for students to practise, apply and reinforce. End the class with a summary to take advantage of better learning at the end; • Do not overload students with too much information before they have a chance to think about it or write it down; • Teach students to organise or chunk information, by utilising mnemonics, taking notes or making a summary; • Encourage students to connect new information with what is already known, through notes, discussions and in-class practice. Material that can be related to students’ life experiences and self-concept is particularly well-remembered; • Encourage students to write things down to free up working memory, especially when working on a complicated problem that requires working memory for reasoning; • Encourage students to improve their knowledge base – for instance, through increasing their vocabulary;

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• Teach for understanding, using methods that require students to go over material a number of times, form linkages between new and already well-known material, and organise it in various ways. Reward students who show that they want to learn for understanding (e.g., if they are on the right track), and stress that mistakes are part of learning. Consider teaching in more depth and less breadth; • Try to engage all of students’ senses when you teach a topic, and preferably have them do something rather than just see or hear. Many experiential and applied learning techniques (e.g., problem-based learning) foster such processing; • Give students practice recalling what they know; • Activate what students know about a topic before they read, by using advance organisers; • Think about how students will need to remember what they are learning – recognise facts, recall a list, compare and contrast? Their learning strategy should match how they will have to remember the information; • Try not to teach similar and confusing concepts too closely in time, in order to reduce retroactive inhibition, and teach the first concept thoroughly before the next is introduced and/or use different methods to teach similar concepts; • Keep necessary administrative tasks until the end of a class; and • Encourage students to distribute learning across numerous study sessions, separated by some good nights’ sleep.

Learning Subsumption theory Ausubel’s (1963, 1978; Ausubel, Novak, & Hanesian, 1978) theory is concerned with how individuals learn large amounts of meaningful material from verbal/textual presentations in an educational setting. He argued that most meaningful verbal learning occurs mainly in the course of expository teaching, reception learning. Reception learning subsumes new material to existing cognitive structure on a substantive, non-verbatim basis, which can take the form of deriving material from pre-existing structure and/or involving material that is an extension of what is already known. He distinguishes reception learning from rote learning (which does not involve meaningful material or subsumption) and discovery learning (where the learner must discover information through problem-solving, see page 44). Ausubel argued that learners should be provided with organised information, with instruction proceeding from the most general and inclusive idea towards details of specific instances. This, he believed, is most effectively done through expository teaching. According to Ausubel, forgetting occurs because certain details get integrated into schemata and lose their individual identity. Ausubel’s theory has commonalities with gestalt theory (see page 33) and schema theory (see page 34). While there are some similarities with constructivist theory (see page 44), Ausubel emphasises that subsumption involves reorganisation of existing cognitive structures, not the development of new structures. A major instructional mechanism proposed by Ausubel is the use of advance organisers – highly generic concepts presented before the lesson, presented at a higher level of abstraction, generality and inclusiveness, and designed to bring to mind relevant knowledge and to clarify the relationships between new and old learning. Organisers act as a subsuming bridge between new material and existing related ideas. In this way they are different from overviews and summaries, which simply emphasise key ideas and are presented at the same

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level of abstraction and generality as the rest of the material. Although there has been a fair amount of controversy over advance organisers, and a large number of studies have been conducted on the effects of advance organisers in learning, there seems to be agreement that they work well if students do not know about the new topic, if the information lends itself to a clear organisation, and if they are concrete, familiar and specific (see Ausubel, 1968, 1978). In addition, such methods designed to activate prior knowledge can be counterproductive if the prior knowledge is weak or lacking.

Implications for teaching Ausubel would recommend that educators: • Present the most general ideas of a subject first, then progressively differentiate them in terms of detail and specificity; and • Utilise instructional materials that attempt to integrate new material with previously presented information through comparisons and cross-referencing of new and old ideas.

Constructivism In the last two decades education, especially science education, has been greatly influenced by the constructivist approach to learning and teaching (Fensham, Gunstone, & White, 1994; Forman & Pufall, 1988). As outlined by Bruner (1960), constructivism is a general framework for instruction based upon the study of cognitive growth and learning. While there are a number of variants of constructivism, with slight variability in emphasis, most tend to be derived from the work of Vygotsky (1978) and to a lesser extent Piaget (1973). Constructivism reflects both theorists’ beliefs that through continual active experience and social interaction, we construct our own ideas about the world. Learners actively ‘construct’ knowledge and meaning from their interpretation of what is happening around them, based on their own experiences and understandings, through the processes of assimilation and accommodation (see page 15). Learning (sometimes known as generative learning) is regarded as an interpretative process that entails challenging and enriching one’s own thinking, integrating new ideas to pre-existing schemata. Learning is also intrinsically social, with cooperative work exposing students to others’ thinking processes and successful problem-solving techniques. In his more recent work, Bruner (1986, 1990) has expanded his theoretical framework to encompass the social and cultural aspects of learning. According to Bruner (1961), the best way of learning is discovery learning, the learning that takes place when students are not presented with subject matter in its final form but rather are required to organise it for themselves, in a top-down fashion. Such learning, according to Bruner, facilitates transfer and retention and increases problem-solving ability and motivation. The process of discovery, however, must be taught through experience and more direct instructional procedures, and there should be guided discovery through a process of active dialogue, as some things are hard to discover without appropriate scaffolding. Instructors should translate information to be learned into a format appropriate to the learner’s current state of understanding, with curriculum organised in a ‘spiral’ manner so that students build upon what they have already learned.

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Problem: Promoting diversified knowledge and critical thinking Context:

Educational psychology

Theories: Constructivism Tynjälä (1999) compared the same educational psychology course learned in a traditional learning environment (involving lectures and individual reading) and in a constructivist learning environment (involving group discussions, writing assignments and a compiled essay), and reported that students in the constructivist learning environment acquired more diversified knowledge. In comparison to the traditional group, who rarely mentioned these outcomes, they reported gaining an ability to apply knowledge, developing critical thinking skills, changed conceptions of the topics studying, and moving from epistemological dualism towards a more relativistic view. Similarly, Scheurman (1997) describes a lesson, taken from an undergraduate educational psychology course he teaches, which aims to foster critical thinking. Because of the conceptual connections between aspects of critical thinking and key principles of constructivist theory (as critical thinking requires the capacity to construct one’s own knowledge, in the process challenging entrenched assumptions about reality and knowledge), the lesson was designed with constructivist principles in mind, such as those recommended by Anderson, Blumenfeld, Pintrich, Clark, Marx and Peterson (1995), and used simulated authentic contexts and techniques such as small group, whole class and panel discussion, role play and case study work.

One important aspect of constructivist learning and teaching is an interest in students’ misconceptions of important concepts. Within psychology pedagogical research, there has been somewhat of a focus on statistical misconceptions that impede students’ acquisition of statistical concepts (Garfield & Ahlgren, 1988; Hawkins, Jolliffe, & Glickman, 1992; Shaughnessy, 1992). Such research shows that students can hold confusions and misconceptions about even seemingly straightforward mathematical concepts such as correlation (Batanero, Estepa, & Godino, 1997; Morris, 1997, 1999). Such misconceptions are prevalent, persistent and often resistant to traditional forms of instruction (Cumming & Thomason, 1995). Computer-assisted learning programmes have been developed to provide an alternative form of statistical instruction where, for example, linked multiple representations and simulations can be used to address students’ misconceptions in statistics (Cumming & Thomason, 1995; Thomason, Cumming, & Zangari, 1994). Similarly, Cerbin (2000a) investigated students’ prior knowledge, and found that this impeded new learning in his educational psychology classes. This information was then used to devise a problem-based learning intervention to encourage students to test and revise their ideas, and stimulate them to move beyond them when challenged to do so in class.

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Problem: Fostering understanding of psychological statistics Context:

Psychological statistics

Theories: Constructivist theory, theories of mathematical understanding Based on research into students’ misconceptions about statistical concepts (Batanero et al., 1997; Morris, 1997, 1999), Morris and colleagues (Jones et al., 1999; Morris, 1998, 2001; Morris & Scanlon, 2000; Morris, Scanlon, & Joiner, 2000) have designed and evaluated programmes to be utilised by psychology students, focusing on central tendency and correlation. For example, Morris and Scanlon (2000) report the findings from a qualitative study that investigated students’ learning collaboratively using a multimedia application called ‘ActiveStats’.

Situated learning One important constructivist educational model is termed situated learning (Brown et al., 1989; Lave, 1988). According to this approach, most learning is a function of the activity, context and culture in which it occurs, and is largely unintentional. This contrasts with most classroom learning activities, which involve abstract and out-of-context knowledge and deliberate learning. In situated learning, learners, through social interaction and collaboration, become involved in a community of practice, which embodies certain beliefs and behaviours to be acquired. As the learner moves from the periphery of this community to its centre, they become more engaged in the culture and hence assume the role of expert. Other researchers have further developed the theory of situated learning. For example, Brown et al. (1989; Collins, Brown, & Newman, 1989) emphasise the idea of cognitive apprenticeship, where the learner is an apprentice in much the same sense as novices who are apprenticed to experts to learn new trades and skills. In the cognitive sphere, the experts are parents, siblings, peers and educators. Educators serve as a combination of model, guide, tutor, mentor and coach, fostering educational growth, rather than directly teaching the learner. Cognitive apprenticeship advocates the use of a number of specific techniques designed to clarify the role of educator and learner (apprentice). Modelling involves educators showing learners how something is done, not so much for learners to simply copy the expert’s performance (see social learning theory, page 51), but to help them develop conceptual models of a task, requiring educators to make steps and procedures involved in the task highly explicit and evident. Coaching involves guiding specific aspects of the student’s performance. Scaffolding (or mediated learning) involves providing support so that students can accomplish tasks that would otherwise be too difficult for them. Procedures that can be used in scaffolding include fading (gradual withdrawal of scaffolds as they become less necessary, derived from operant conditioning theory, see page 27); articulation (encouraging learners to put their conclusions, descriptions and principles into words); reflection; and exploration, the generalisation of learning. Three principles guide the sequencing of material in cognitive apprenticeship: global before local, referring to the idea that learners should be provided with an overall view of what is to be learned before they begin to work on specifics, enabling advance organisation; material should be presented in order of increasing complexity; and knowledge and skills acquired should be applied to an ever-increasing diversity of situations.

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Cooperative learning As already noted, cooperative learning is a major constructivist learning technique. While a large number of educators claim to use cooperative learning, fewer experiences are truly cooperative, where students can work together in a group small enough that everyone can participate on a collective task. The relationship among group members is one of positive interdependence, although individual responsibility for sharing, cooperating and learning is assigned. Vygotsky (1978) suggests a reason that cooperative learning is effective and important – because learning is highly dependent on social interaction. It is also dependent on language, and cooperative learning fosters the development and exercise of language skills. In addition, cooperative learning may foster student motivation, and processing and elaboration of information to be learnt (see page 39) (Bennett, Howe, & Truswell, 2002). Evidence suggests that cooperative learning techniques lead to superior academic achievement, high motivation, participation, enhancement of social skills, reduction in prejudice and improvement in self-esteem and attitudes towards education (Clibbens, 2000; Johnson et al., 1981; Kremer, 1997; Qin, Johnson, & Johnson; 1995; Rysavy & Sales, 1991). These positive effects may be partly due to the greater curriculum structure required for cooperative learning, to the language and social skills fostered, and/or to the feeling of common group membership. A number of different cooperative learning techniques have been developed. One wellestablished one is the jigsaw classroom (Aronson, Blaney, Stephan, Sikes, & Snapp, 1978), in which different students across the class are given different parts of a task to complete. Students with the same part complete it together, then collaborate with other students doing different parts of the task to finish the entire task. Perkins and Saris (2001) utilised the jigsaw classroom technique within an undergraduate statistics course, with students given different parts of a problem worksheet. Students reported that the technique helped them understand a statistical procedure, use class time efficiently and increased the variety of learning experiences available in the course, while Carroll (1986) found an improvement in student academic performance. Grossman (2002) used case studies within a jigsaw classroom framework to teach students in general or abnormal psychology courses about treatments for depression, and discusses other uses of cooperative learning focusing on case studies. Another well-known technique is Slavin’s (1995) Student Team Achievement Division (STAD), in which students are assigned to four-member learning teams that are mixed in performance level and/or other group memberships. The educator presents a lesson, and then students work within their teams to make sure all team members have mastered the material. Finally, students take individual quizzes on the material, at which time they may not assist one another. STAD is most appropriate for teaching well-defined objectives with single right answers, but can easily be adapted for use with less well-defined objectives by incorporating more open-ended assessments such as essays or performances. Lanzon (2002) describes her use of STAD with educational psychology students, to increase their understanding and application of group dynamics, which successfully increased at post-test. Several decades of empirical research have demonstrated conclusively that collaborative learning is an effective teaching device in higher education (e.g., Johnson, Johnson, & Smith, 1991), provided that two essential conditions are met. First, some kind of recognition or small reward must be provided to groups that do well so that group members can see that it is in their interest to help their groupmates learn. Second, there must be individual accountability for performance. The effectiveness of cooperative learning can be increased if group members are taught communication and helping skills and/or metacognitive learning strategies. 47

In addition to boosting achievement, cooperative learning methods have positive effects on such outcomes as improved intergroup relations, self-esteem and attitudes to study (Slavin, 1995). However, despite the evidence, there is still an over-reliance on traditional methods that emphasise individual learning. Reasons for this gap include the difficulty of translating the principles of collaborative learning into actual practice, and the fact that it can introduce more difficulties than solutions when done poorly (Bryant, 1978; Giordano & Hammer, 1999). Meyers (1997) summarised the components of successive collaborative learning tasks in a review of 68 empirical articles. He delineated three critical domains – task structure, student evaluation and group structure – and offered general guidance for incorporating collaborative learning tasks into courses. Meyers recommended that: • The structure of CL tasks should be amenable to small group work; • CL tasks should avoid the trap of social loafing (e.g., by using conjunctive tasks that require joint participation and maximise interdependence); • A variety of evaluative criteria should be used, assessed at both group and individual level; and • Group structure should promote individual participation. Problem: Fostering diversity, critical thinking and involvement, learning Context:

General psychology, social psychology,

Theories: Cooperative learning principles, social identity theory A large number of studies describe how cooperative learning principles have been utilised in psychology teaching, including George (1994), in multicultural classrooms; Grossman (1994, 2002), as a technique to foster critical thinking; Finkel (1999), to enhance student involvement and comprehension; and Watters (1996), as a way to foster reasoned discussion and conflict resolution. For example, Pychyl, Clarke and Abarbanel (1999) used the web to facilitate collaborative group work in a class of psychology postgraduate students, who used personal web sites for their seminar work. The web environment appeared to facilitate group work by providing clear demarcations of individual members’ contributions; a structure for group members’ participation; easy access to group members’ contributions; individual work space; and commensurable resources for each group member. Carlsmith and Cooper (2002) attempted to put Meyers’ (1997) principles into practice in a course on persuasion, designing it from the beginning to integrate the benefits of cooperative learning while minimising the difficulties and drawbacks. In their subject, small groups designed, implemented and evaluated a persuasive behaviour change campaign, with each campaign based on principles of social psychology. In addition, social identity theory (Hogg & Abrams, 1988) was used as the basis for techniques used to create feelings of cohesion among members of the group. Student self-reports indicated that the course format was significantly more popular than were traditional formats, and that students worked significantly harder for and learned more from the cooperative learning components than the traditional lecture- and text-based components of the subject.

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Implications for teaching A number of recommendations for psychology educators follow from constructivism, situated learning and cooperative learning (Anderson et al., 1995): • Seek to understand students’ levels of functioning, and provide educational material at an optimal level of difficulty; • Investigate students’ conceptions of key concepts, in order to determine misconceptions that may need to be challenged and changed; • Provide multiple representations of key ideas across learning situations; • Use learning situations that provide enough complexity to seem authentic; • Foster learner-learner interaction, such as through collaborative learning and public interaction; • Elicit students’ beliefs through comparison with alternative views; • Provide a supportive, learner-driven learning environment, one in which students can create their own ideas, both individually and collaboratively; • Move from a hierarchic classroom structure to an egalitarian cooperative one, where students’ ideas and interests drive the learning process, and you serve as a guide to rather than the source of knowledge, helping students to take the initiative in their own selfdirected explorations; and • Try to stay as flexible as possible in the classroom, sometimes giving guidance and training in a particular task or content area, but more often moving around the classroom, assisting individuals and groups.

Gagné’s information-processing model of learning Gagné (1985; Gagné, Briggs, & Wager, 1992; Gagné & Driscoll, 1988) devised an information-processing model of learning based on the notion that there are different types or levels of learning, each of which requires different types of internal and external conditions and therefore different instruction. According to Gagné, there are five major categories of learning (verbal information, intellectual skills, cognitive strategies, motor skills and attitudes), but the focus of his theory is on intellectual skills. Gagné suggests that learning tasks for intellectual skills can be organised in a hierarchy according to complexity: stimulus recognition, response generation, procedure following, use of terminology, discriminations, concept formation, rule application and problem-solving. Because higher-order skills and concepts depend upon subordinate capabilities, instruction based on this model always begins by analysing what is to be learned and arranging content into a hierarchy of tasks and sequence of instruction – a process called task analysis. Educators facilitate students’ progress through the different tasks, using scaffolding and other techniques. Gagné’s theory has been applied to the design of instruction in virtually every context, particularly in relation to instructional technology in teaching (Gagné, 1987).

Implications for teaching Gagné’s theory implies that psychology educators should: • Analyse what is to be learned and break this down into a sequence of tasks, with later tasks dependent upon successful achievement of earlier ones; and • Then facilitate students’ working through these different tasks by using direct instruction, scaffolding and other techniques.

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Transfer of learning Spontaneous transfer of learning and skills is rarely found in psychology research (Newstead, 1990; Singley & Anderson, 1989), even when the problem is essentially the same but phrased differently. Research on expert/novice differences also shows that expertise in one field does not transfer to other fields (Glaser & Chi, 1988). Instead, experts, due to their increased experience in their field, have broader and better organised knowledge of the field and its problems and a broader repertoire of appropriate problem-solving techniques, and know when and how to use these techniques effectively and speedily. Because spontaneous transfer is rare, Newstead (1990) points out that active steps need to be taken to ensure transfer, and makes a number of suggestions based on the literature. The more knowledge or expertise a person has in a subject or skill, and the greater the range and number of contexts in which this expertise was acquired, the more likely is the skill to transfer to a novel situation. Transfer is also easier when the subject matter and context in which it is to be applied is very similar to the original context (Perkins & Salomon, 1988), and for more general knowledge (McKeough, Lupart, & Marini, 1995; Phye, 1992). Transfer is also more likely when students are effective learners and do not have a competing mental model or schema, and are metacognitively aware (McKeogh et al., 1995; Newstead, 1990). Research shows that self-contained thinking skills packages tend not to lead to improved thinking abilities, perhaps because they do not encourage metacognitive awareness or skills generalisation, or understanding of the principles and cognitive processes underlying a skill (McMillan, 1987). Training in transferable skills is therefore most effective in the context of real practice in a specific field. Newstead (1990) suggests that transferable skills training should be an integral part of the psychology curriculum, and should be integrated with relevant theory. Skills training should also be made explicit, and if possible skills should be explicitly assessed.

Implications for teaching Research into transfer of knowledge and skills (Brown et al., 1989; Newstead, 1990) leads to a number of recommendations for teaching practice: • Do not assume that a student who is good (or poor) in one subject will be good (or poor) in another, or that a student who learns a skill in one class or subject will be able to apply it to another subject; • Use learning activities that present diverse examples, multiple representations of content and multiple perspectives – for example, case-based instruction, which emphasises knowledge construction and not its transmission; • Use instructional materials that avoid oversimplifying the content domain and supporting context-dependent knowledge; and highly interconnected rather than compartmentalised knowledge sources; • Make skills training explicit: make students aware of the skills they will be and are acquiring; • Make sure problems are always in context; • Teach skills in multiple contexts, and enable and encourage students to practise their skills in a variety of contexts; • Model skill use and transfer, in line with social learning theory (Bandura, 1977; see page 51); • Give students feedback on their performance on desired skills;

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• Teach new facts through patterns or principles, rather than by rote. Using analogous examples or tasks can also be effective, though students must understand the topic(s) on which analogies are based, and are likely to need to be cued about their relevance; • Teach for understanding, as having a deeper understanding of a topic helps students transfer. Help students organise information learnt and integrate it with what they already know; • Teach students to solve problems by applying their understanding; and • Help students have more realistic ideas about learning, helping them realise that mistakes are part of learning, and that learning is about understanding and not just memorising facts.

Social learning approaches Bandura’s (1977, 1986) social learning theory (also known as social cognitive theory) posits that observational learning (or imitation) is a central process in determining behaviour. Social learning through imitation reflects the effects of actual or anticipated direct or vicarious reinforcement, the observer’s awareness of the connection between behaviour and outcomes, and the observer’s ability to anticipate the consequences of behaviour. Essentially, social learning theory sees human behaviour as a continuous reciprocal interaction between cognitive, behavioural and environmental influences. Learning through imitation requires paying attention to the model’s behaviour, retention of it, reproducing it, and being motivated to learn it. Imitation can have a modelling effect (lead to the acquisition of new behaviours), an inhibitory-disinhibitory effect (inhibit or disinhibit deviant responses, usually due to observation of the model being punished or rewarded for the behaviour), or an eliciting effect (fostering behaviour that is not identical to that of the model but related to it, and neither novel nor deviant). In social learning, the educator can control many of the factors important for teaching, and foster attention, retention, reproduction and motivation. An example of this in the psychology context is found in Wheeler et al. (1999).

Problem: Student fear of the laboratory rat Context:

Introductory psychology

Theory:

Social learning theory

Barber (1994) used a participant modelling technique in the classroom to reduce students’ fear of a laboratory rat. In participant modelling, a clinical procedure used for treating phobias that is based on social learning theory, participants are exposed directly to a phobic object in the presence of a therapist (expert). In Barber’s study, students received a mild level of exposure (holding the rat’s transparent transport box), and saw peer volunteers handling the animal. Pre- and post-testing showed that student fear (as measured by a validated fear questionnaire) was significantly reduced after exposure, with the greatest reduction for the peer volunteers.

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Implications for teaching Social learning theory leads to a number of recommendations for teaching practice: • Be aware of the fact that students are more likely to adopt a modelled behaviour if the model is similar to the student and has admired status. As in many contexts academics are similar to their students and are accorded higher status, it is important to realise that your non-desired behaviour may also be modelled; • Make the positive outcomes of various learning behaviours explicit, as students are more likely to adopt a modelled behaviour if it results in outcomes they value; • Encourage students to analyse and describe behaviour they wish to emulate, because coding modelled behaviour into words, labels or images results in better retention than simply observing it; and • Have students visualise themselves doing the behaviour before actually doing it, as the highest level of observational learning is achieved by first organising and rehearsing the modelled behaviour symbolically and then enacting it overtly.

Motivation Motivation in HE is an issue for both students and staff, though the focus has tended to be on student motivation. As with learning, there are many different approaches to motivation, including behavioural approaches, content theories (theories, such as Maslow’s hierarchy of needs, that focus on what motivates one) and process theories (ones, such as Vroom’s expectancy theory, that focus on the dynamics of motivation).

Intrinsic and extrinsic motivation Within education, the emphasis in motivation research has been on fostering intrinsicallymotivated study behaviour – that is, behaviour that is performed simply for the sake of the pleasure inherent in the activity itself, occurring in the absence of external rewards or reinforcements, and characterised by the experience of interest, enjoyment and curiosity (Deci, 1975). Such intrinsic motivation has been empirically linked to a variety of important, positive educational outcomes (Patrick, Hisley, & Kempler, 2000). Research suggests that a number of educational variables can promote intrinsic motivation to learn (Patrick et al., 2000): self-determination (through the provision of greater choice and a focus on personally meaningful material), promotion of perceived competence through both positive feedback and optimal levels of challenge, interpersonal relatedness and perceived interpersonal cues regarding the motivation of others towards an activity (e.g., the perception that the educator is intrinsically motivated, perhaps because they are enthusiastic in their teaching). Focusing on the latter variable, Patrick et al. (2000) surveyed introductory and intermediate level psychology students enrolled in a variety of modules and found that perceived educator enthusiasm was the most powerful unique predictor of students’ intrinsic motivation and feelings of vitality within the classroom. Autonomy support and knowledge of subject also emerged as predictors of intrinsic motivation. However, motivation to learn in general, and motivation to study particular subjects, may differ and be based on different factors, such as the nature of the task to be done in the classroom. Jacobs and Newstead (2000) studied the nature and development of student motivation among psychology students, in a number of studies. The findings suggested that there are two types of students: those motivated by the discipline itself and those motivated by the

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acquisition of more general skills and experiences. The perceived importance of many aspects of the degree declined over the three years of the degree, seeming especially low in the second year, but some aspects, notably research methodology, and some skills and experiences showed marked increases in the final year. The authors conclude that current theories of educational motivation need to be extended to account for the difference between subject-related and generic motives to learn. In addition, much of what is to be learned in education is not inherently interesting or useful to students in the short-term, so extrinsic motivators (incentives) such as praise, marks, recognition and prizes may be needed. While there is some evidence that reinforcing people for behaviours that they would have done without reward, where rewards are provided for engaging in an activity regardless of standard of performance, can undermine long-term intrinsic motivation, for most tasks there is no basis for concern that use of extrinsic reinforcers will undermine intrinsic motivation (Cameron & Pierce, 1994). In fact, rewards more often increase intrinsic motivation, especially when they are contingent on the quality of performance and not just on mere participation, when the rewards are seen as recognition of competence, when the task is not very interesting, or when the rewards are social rather than material (Cameron & Pierce, 1994). Nonetheless, educators should attempt to make everything they teach as interesting as possible, and may be able to phase out extrinsic rewards as students come to enjoy and succeed at the activity (Hetrick, 1999). Problem: Low levels of motivation to learn in students Context:

Psychology students in general, introductory psychology students

Theories: Research into intrinsic motivation In an experimental study occurring outside the classroom situation, Patrick et al. (2000, Study 2) manipulated level of educator enthusiasm to determine its effects on introductory psychology student motivation. Results revealed that students who received an enthusiastically delivered lecture (as opposed to an unenthusiastically delivered one) subsequently reported greater intrinsic motivation regarding the lecture material and higher levels of vitality. There was also a trend, though not statistically significant, towards students’ being more likely to read lecture-related material on their own following an enthusiastically delivered lecture. Patrick et al. note, however, that in a real teaching context having the expectation that students will be motivated to learn can increase educator enthusiasm. Based on research showing that the nature of the task to be done impacts on student motivation, Hemenover, Caster and Mizumoto (1999) suggest that the ambiguity and lack of control inherent in the process of writing psychological reports and essays produces low motivation, which may in turn result in many students completing a paper at the last minute. As a result, students may not adequately process and reflect on what they have learned, resulting in less beneficial educational experiences. They suggest that progressive writing techniques may assist in student motivation. Students in their introductory psychology class were provided with a written tutorial that explained a sixstep writing process, and provided feedback on their progress at each step. Course evaluations indicated that students believed that the progressive writing approach helped them write a high quality paper, and student performance was good, with 44% of students earning more than 90% of the points available. However, student motivation was lower than was expected.

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Maslow’s hierarchy of needs Of all the content theories of motivation, those based on ‘need’ have been particular influential. Maslow (1943, 1970), in his hierarchy of needs, identified a number of different types of need. He argued that a satisfied need is no longer a motivator, and suggested that lower-order needs (deficiency needs) must be satisfied before higher-order needs (growth needs) can motivate behaviour. Maslow’s need levels are often shown as a pyramid, going from (at the lowest level) physiological needs, safety needs, belongingness and love needs, and esteem needs (deficiency needs); to the need to know and understand, aesthetic needs, and finally selfactualisation needs, realising one’s full potential, which can take many forms and varies between individuals. Maslow’s model assumes that higher-order needs are less likely to be satisfied than lower-order needs, with Maslow estimating that fewer than 1% of adults achieving self-actualisation. Maslow’s model implies that if students’ basic needs are not met (e.g., for food, sleep), learning will suffer. However, the most important deficiency needs may be those for love and self-esteem. Students who do not feel they are loved and capable are unlikely to have a strong motivation to achieve the higher-level growth objectives such as the search for knowledge and understanding for their own sake, or the creativity and openness to new ideas that are characteristic of self-actualising individuals. Educators who can therefore put students at ease and make them feel accepted and respected as individuals are more likely to help them become eager to learn for the sake of learning and willing to risk being creative and open.

Herzberg’s two-factor theory Unlike Maslow’s theoretical approach, Herzberg’s (1966) two-factor (or motivation-hygiene) theory was based on empirical research with engineers and accountants, and has had a major impact on job structuring in organisations. Herzberg found that while certain factors were associated with job satisfaction (motivators), others were linked with dissatisfaction if absent or poor (hygiene factors). They were not, however, simple mirror images of each other; motivators were linked with the job content, were intrinsic to the work (e.g., achievement, recognition, the work itself, responsibility and advancement), while hygiene factors were linked with the work environment, the job context (salary, supervision, interpersonal relations, policy and administration and working conditions). Removing hygiene factors that are creating dissatisfaction does not and indeed cannot create job satisfaction because hygiene factors are incapable of doing so. Herzberg suggested that the redesign of jobs to increase motivation and performance should concentrate on motivators. While Herzberg’s theory has met with a number of criticisms (see Robertson, Smith, & Cooper, 1992), Herzberg’s model has been influential, with the job enrichment movement strongly influenced by it. This movement has fostered strategies such as job rotation, job enlargement (increasing the range of tasks done by a worker), and job enrichment (job enlargement accompanied by greater autonomy, responsibility and job control), with Hackman and Oldham (1976, 1980) developing a well-known model of job redesign that explicitly refers to Herzberg’s work. While the job redesign approach is reasonably common within educational management (see Evans, 1998), it has only recently been applied to the area of student motivation (see next page).

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Problem: Increasing student motivation and interest Context:

General psychology students

Theories: Hackman and Oldham’s model of job characteristics and redesign Catanzaro (1997) suggested that Hackman and Oldham’s model could be usefully applied to the psychology teaching context, to provide a framework for enriching course design to increase student motivation. In order to test this, Bloom et al. (2000) administered to students the revised Job Diagnostic Survey (Hackman & Oldham, 1975; Idaszak & Drasgow, 1987), which was developed on the basis of Hackman and Oldham’s model of job redesign (1976, 1980), and found that the degree to which students perceived course material to affect the lives of others was the most salient predictor of course motivation, satisfaction, performance, absenteeism, interest and desire to withdraw. However, feedback received by students, perceived autonomy and the variety of skills developed and used by students also significantly predicted some of these outcome measures. Bloom et al. suggest that if educators try to foster these four dimensions in their teaching practice, they may significantly enhance students’ classroom experiences.

Expectancy theory One of the most influential process theories of motivation is Vroom’s (1964, 1974) expectancy theory, which is based on the assumption that people are motivated by what they regard as the likely impact of their actions. Individuals rationally (though not necessarily consciously) examine the prospects for different rewards that might arise from different courses of action, and decide to act in the way that is most likely to be successful and produce the greatest reward for them personally. People therefore are most likely to be motivated when they think they will receive rewards if they perform well; they feel they will be fairly rewarded by comparison with others around them; the attraction of the reward is high; and they feel confident of achieving a high level of performance. A similar theory is Atkinson’s (1964) expectancy-valence model, where motivation = perceived probability of success x incentive value of success (the value placed on success). Atkinson points out that under certain circumstances an overly high probability of success can reduce motivation; if someone is very able it may be so easy for them to succeed that they need not do their best. Atkinson argues that success in an easy task is not as valued as is success in a difficult task, therefore motivation should be at a maximum at moderate levels of probability of success. Confirming this theory, research shows that a person’s motivation increases as task difficulty increases up to a point at which the person decides that success is very unlikely or that the goal is not worth the effort (Brehm & Self, 1989).

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Self-determination theory Deci and Ryan’s self-determination theory (SDT; see Deci, Eghrari, Patrick, & Leone, 1994; Deci & Ryan, 1985, 2000; Ryan & Deci, 2000) is a well-established and comprehensive theory of motivation. Deci and Ryan postulated three innate psychological needs: competence, autonomy, and relatedness. Social contexts that facilitate satisfaction of these needs (by providing optimal challenge, informational feedback, interpersonal involvement and autonomy support) promote both intrinsic motivation and self-determined forms of extrinsic motivation. Intrinsic motivation and self-determined extrinsic motivation are positively associated with high quality learning and personal adjustment (Deci, Vallerand, Pelletier, & Ryan, 1991). SDT makes a distinction between self-determined (or autonomous) and controlled types of extrinsic motivation, and the impact that this distinction has on the quality of learning experiences. Controlled extrinsic motivation depends either on explicit or implicit rewards or punishment, or on people’s internalised beliefs about what is expected of them, and leads to behaviour that complies with pressures, as it is externally regulated. Such extrinsic motivation detracts from a feeling of self-determination and leads to a decrease in intrinsic motivation, and learning under such controlling conditions is likely to be rote, short-lived and poorly integrated into long-term values and skills (Reeve, 2002). By contrast, autonomous extrinsic motivation can lead to and not undermine intrinsic motivation, as it is self-determined, personally endorsed, reflects what people find interesting and important, and leads to behaviour with a sense of volition, agency and choice. Whether educators are controlling or autonomy supportive is influenced by a number of factors, such as their beliefs about students’ levels of motivation, and whether they are pressured or controlled by administrators or the system in general. However, studies show that educators can be taught to be more autonomy supportive, with the result that students increase their levels of selfdetermination and achievement (Reeve, 2002). Deci et al. (1991) summarise contextual factors that support student autonomy, such as providing a meaningful rationale, acknowledging students’ feelings and conveying choice. Project-based learning, for example, allows students numerous choices around what form their finished product will take (Williams, Saizow, & Ryan, 1999). Problem: Fostering student motivation Context:

Educational psychology

Theories: Motivational theory Tuckman (1996a) describes a series of studies assessing the effects of various strategies designed to foster motivation in students in his educational psychology course. In these studies, conducted in different class cohorts between 1988 and 1996, Tuckman compared experimental groups that received different interventions or were required to use different strategies. Intervention strategies, which were based on Tuckman’s own prior research into student motivation, included induced student strategies (goal-setting and planning), teaching strategies (participant modelling and text processing), and what he calls strategic classroom parameters (incentives and grading method). Over this time, student cognitive engagement (defined as the amount of time spent studying or completing assignments) increased, primarily among students lacking self-efficacy. Student achievement in course exams also improved. Based on these results, Tuckman proposes a model for enhancing student learning and motivation that includes student activities and behaviours requiring self-regulation.

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Attribution theory, locus of control and self-efficacy Attribution theory (Graham, 1991; Weiner, 1992, 1994) seeks to understand how people explain the causes of their own and others’ successes and failure (important recurring themes in education). According to Weiner (1994), most explanations for success and failure have three characteristics: whether the cause is internal or external, stable or unstable and controllable or not. Attribution theory deals primarily with four explanations for success and failure in achievement situations: ability (internal and stable), effort (internal and unstable), task difficulty (external and stable) and luck (external and unstable). A central assumption of attribution theory is that people attempt to maintain a positive self-image (Thompson, Davidson, & Barber, 1995), so are likely to attribute their success to their own efforts or abilities but their failures to factors over which they have no control. However, maintaining such attributions may be difficult to maintain, so students may move from an external unstable attribution of luck to one that is more stable, such as claiming that the course is too difficult. Students may even reduce their level of effort so that they can maintain the idea that they can succeed if they really wanted to (Jagacinski & Nicholls, 1990). A central concept in attribution theory is locus of control (Rotter, 1954), a personality trait that concerns whether people attribute responsibility for their achievement to internal factors (internal locus of control) or external factors (external locus of control). Closely related to the more global internal locus of control, but specific to particular task domains, is self-efficacy (Bandura, 1997), a person’s self-perceived level of competence and capacity to succeed in an area. Self-efficacy and academic motivation are strongly related, with self-efficacy found to be the second most important predictor of a student’s academic achievement after ability (Pajares, 1996; Schunk, 1991). Unsurprisingly, those with high self-efficacy in a particular domain can be expected to work hard, provided they want to succeed, while the belief that one will fail can lead to poor motivation and therefore be a self-fulfilling prophecy. However, achievement has a strong effect on locus of control and self-efficacy (Weiner, 1992), which can make it difficult to study the effects of these variables on achievement. Strategic training can foster both achievement and self-efficacy in a domain; for example, Prieto and colleagues (Prieto & Altmaier, 1994; Prieto & Meyers, 1999) have found that, amongst psychology postgraduate teaching assistants, formal training and supervision in relation to teaching practice has a positive, statically significant effect on students’ sense of self-efficacy toward teaching.

Goal orientation Dweck and colleagues (Dweck, 1986; Dweck & Elliott, 1983; Dweck & Leggett, 1988) propose that learners possess either performance goals or mastery (also known as learning) goals, which guide their activities, thoughts, feelings and performances (Hidi & Harackiewicz, 2000). Goal orientations are based on students’ implicit theories of intelligence, with students with performance goals implicitly believing that intelligence (or ability) is static and inflexible, fundamentally unchangeable, and those with mastery goals believing it is fundamentally malleable. Students with performance goals primarily seek to gain positive judgements of their competence and avoid negative judgments, and therefore focus on getting good marks, take easy courses and avoid challenging situations. When they run into problems they tend to fall into a pattern of helplessness. By contrast, those with mastery goals see the purpose of

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education as gaining competence in the skills being taught, use metacognitive or selfregulated learning strategies, and are more likely to take difficult courses and seek challenges. When they face problems they tend to seek assistance to improve their learning, and their motivation and performance may actually increase. While most students do not fall neatly into one goal orientation or the other, generally educators want to increase students’ mastery goals and diminish performance goals. However, performance goals can have positive effects in some situations for some students, according to Hidi and Harackiewicz (2000), so such an orientation to learning should not be viewed as necessarily limiting for all adult learners. Research suggests that educators should try to convince students that the purpose of academic work is learning rather than obtaining good marks, emphasising the interest, value and practical importance of the material studied and deemphasising marks and other rewards. In particular, use of highly competitive grading or incentive systems should be avoided, as those who perceive their ability to be low may well give up in advance (Ames, 1992). Fortunately, studies indicate that the use of learning tasks that are challenging, meaningful and related to real-life are more likely to lead to mastery goals than are other tasks (Ames, 1992).

Implications for teaching Research into motivation leads to the following recommendations for teaching practice: • Attempt to create a learning context that actively supports students’ growing interests and needs and does not undermine their intrinsic motivation; • Enhance student motivation by using a combination of intrinsically interesting tasks, responsibility delegated to them, opportunities for recognisable achievement and personal growth, and recognition and advancement; • Try to teach in an enthusiastic style; • Develop educational materials that fit students’ interests and real-world knowledge, and challenge them; • Provide clear feedback on performance, whether formal or informal; and • Use assessment techniques that measure both understanding and knowledge, while not fostering high levels of competition.

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The social context Whilst many psychological theories of relevance to teaching tend to focus on the individual and factors influencing their individual cognitions and behaviours, it is important to recall that education is fundamentally a social process, as sociocultural theorists of education explicitly acknowledge (see page 15).

Group processes Group work is often encouraged and utilised in psychology teaching (Bennett et al., 2002), in order to enhance student involvement, learning and comprehension, and considered a key transferable skill that fosters student employability. In addition, students are encouraged to work in groups because this can result in gains in productivity due to the fact that in comparison to individuals the group as a whole has more knowledge and ideas and a greater capacity to evaluate opinions and detect errors and problems. However, this productivity gain can be balanced out by process losses – inefficiencies and problems caused by the fact that a group of people are involved. Such problems can include low levels of group cohesiveness, poor communication within groups, poor decision-making, and social loafing (uneven participation by group members), each of which will be addressed in the following subsections of this report.

Group development and structure While small groups and teams are frequently used in HE, creating group cohesiveness within such teams, particularly where membership is not self-selected, can be problematic. While group cohesiveness is not necessary for effective performance, it can foster group motivation and reduce social loafing (Michaelsen, Fink, & Knight, 1997), as well as make group participation more pleasurable. Group cohesiveness is influenced by a number of factors, including salience of group membership, strength of identification with the group, whether other ingroup members are seen to represent epitomise norms, dependence of members upon the group, group achievement, and external threat (Hogg, 1992).

Problem: Poor cohesiveness within cooperative groups Context:

General psychology

Theories: Social identity theory Carlsmith and Cooper (1992) utilised social identity theory research to create cohesion within small cooperative groups in the classroom, encouraging groups to generate unique group names, meet in separate areas and in social settings, and sit together during class lectures and discussions. Research into small group and team development has come up with a number of models of small group development, which generally agree that the route to group cohesion may be both traumatic and problematic, reflecting the intricacy of the issues involved. In Tuckman’s (1965) well-known model of group development, for example, groups go through four stages: • Forming (characterised by uncertainty and anxiety); • Storming (conflict and internal dissent due to individual differences);

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• Norming (developing cohesion and satisfaction as group members, and establishing new group goals, norms, roles and leadership); and • Performing (focusing on task completion, with interpersonal difficulties resolved. Tuckman and Jensen (1977) added a further stage, adjourning, where the group is likely to disband because the task has been completed or group members are leaving, precipitating reflection and preparation for change. Tuckman’s model appears to be verified by research (Tuckman & Jensen, 1977) and seems to explain issues associated with many problematic groups that fail to work effectively. Once a group has been established, individuals take on group or team roles. On the basis of observations of team working at a (male-dominated) management college, Belbin (1981, 1993) developed a well-known and -used model of group/team role, which builds on the idea of role and personality matching in team building. Belbin argues that people have an inherent ‘selfperception’ which determines their intuitive way of acting in group situations, and specifies a number of different ‘team roles’, each of which relates to the particular psychological and social attributes of team members. Belbin found that a range of distinct ‘team roles’ can be identified, falling into ‘action-oriented’ roles, ‘people-oriented’ roles and ‘cerebral’ roles. Individual roles can be predicted through psychometric testing, with leaders tending to prefer or adopt one or two particular team roles. Combining team roles in particular ways (e.g., if individuals become more aware of their best roles and potential strengths or if individuals work to team strengths rather than allow their weaknesses to interfere) tends to produce more effective teams. Belbin’s observations indicated that the most successful teams were those with members who had a complementary range of skills and abilities, plus the flexibility to adapt roles and behaviour to changing circumstances.

Communication within groups In relation to communication within groups, Leavitt’s (1951) work points to the leader’s strategic role in intragroup communication: the nature of the group or network effectively controls how communication works. In contrast to centralised networks (e.g., a ‘chain’ network, a unidirectional flow of communication from one person to the next, or a ‘star’ network, where all communication goes through a central person), which depend upon individual links or performance, in decentralised networks (e.g., a ‘circle’ network, where there is sequential but bi-directional communication, or ‘all-channel’ networks, where everyone is in communication with everyone else), information flows more freely between all group members. As a consequence, for simple tasks star and all-channel networks perform well, and circle networks less well. All-channel networks again perform best in complex task situations. Chain networks may benefit the individuals at the head of the chain, but are generally of limited value to the group and are not good at fostering motivation. This research suggests that communication within groups is fostered when everyone is in communication with each other, for example through an email list, with all interactions circulated to all members. With the advent of such communication and information technologies, researchers’ interest has turned to computer-mediated communication (CMC). Unlike face-to-face communication, CMC is relatively anonymous due to the many social context cues filtered out. Research shows that such online anonymity has benefits for teaching and learning, including increased equity and higher participation rates (Berge & Collins, 1995). However, CMC may be associated not only with higher levels of self-disclosure but of antisocial behaviour, due to the absence of nonverbal cues, well-established etiquette and face-to-face norms. This is particularly the case in large internet lists, where it is easier to remain anonymous (Berge & Collins, 1995).

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Problem: Increasing participation and involvement in the class community Context: Personality identity and community in cyberspace course Theories: Computer-mediated communication research Chester and Gwynne (1998) utilised CMC in an online psychology subject focusing on personal identity and community in cyberspace, in a context that they hoped would promote collaborative learning, by making it necessary for the completion of a number of assessment tasks. They found that CMC increased the proportion of intercultural interactions and participation of those who would normally rarely participate in class. Students in general reported higher participation rates and greater involvement in the class community. The process of CMC itself, and its implications for communication, identity and community, was the focus of the class, fostering critical self-reflexivity in students.

Group norms and conformity Associated with every group are group norms, expected behaviours and even cognitions, and the expectation that group members will conform to those norms. As social identity theory (Hogg & Abrams, 1988) explores, if one sees oneself as part of a group and values that group, then ingroup identification will lead one to take on the group’s norms regarding both one’s own behaviour and that of members of other groups. Going against a group’s norms is a challenge to the identity of the group and its members, and can therefore lead to extreme behaviour such as exclusion of the individual or forced conformity. In many cases conformity with group norms is beneficial, if the group’s norms are positive (e.g., that group members should focus on the task at hand and not be distracted by the desire to socialise), but in some cases conformity may lead to lower quality outcomes. For example, when the group norm is not to argue about things but to seek unanimity, and there is a dominant group member or tutor, this may lead to groupthink (Janis, 1972, 1982), a phenomenon that can and has led to very poor decisions. In groupthink not all alternatives are carefully considered, but instead the will of the dominant individual tends to be adopted, and the group tends to engage in stereotypical thinking and rationalisation of poor decisions. Even when a group’s norms are not detrimental to quality argument, influence processes operating within groups tend to produce group polarisation – the group’s opinions tend to shift in the direction initially favoured by group members before discussion (Myers & Lamm, 1975). Within a problem-based learning group, for example, this could lead to the group settling on a solution too early, producing a poorer solution than one generated from a more thorough discussion. However, when groups are more heterogeneous they tend to offer more creative solutions to problems than do homogeneous groups (McLeod, Lobel, & Cox, 1996), perhaps because heterogeneity of group members reduces the tendency towards conformity. Conformity to group norms, such as occurs in group polarisation, is affected by a range of elements including group size, unanimity of the majority, and group structure, with conformity often increasing as group size grows. In addition, conformity is greater in decentralised than in centralised networks. Asch’s classic 1950s experimental studies of conformity (e.g., Asch, 1951) indicate the potential for individual problems when a new member joins the team, as well as the importance of ensuring that appropriate norms are established by a group during the ‘storming’ and ‘norming’ stages of group development (see page 59).

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Social loafing It has long been established that as one adds more and more people to a group pulling on a rope, the total effort or output produced by the group rises, but the average exerted or produced by each group member declines, a phenomenon known as social loafing (Latané, Williams, & Harkins, 1979), with various theories such as losses in motivation, evaluation apprehension and coordination, and increased deindividuation, having been posited as responsible. Michaelsen et al. (1997) examine the research on social loafing in learning groups and identify several key variables that must be maximised in order to create a group environment that is conducive to broad-based member participation and learning: member identifiability; group discussion and interaction; immediate, unambiguous and meaningful feedback; and explicit rewards for high levels of group performance. In addition, social loafing is less likely to occur in more novel and challenging tasks and where ingroup identity and group cohesiveness are strong (Karau & Williams, 2001).

Implications for teaching Research into group processes leads to a number of recommendations for teaching practice: • Help students build cohesive groups and teams by encouraging them to develop a shared goal(s) and unity of purpose; develop complementary roles; foster individual and group accountability; provide help and social support to fellow group members; understand and appreciate each other’s roles; regularly communicate with all other team members; monitor, evaluate and adjust goals as needed; listen to others; and show respect; • Explain to students that teams often go through early stages of conflict, where things are unclear and relationships ambiguous, before they can progress towards more stable, integrated relationships and structures where norms and behaviour are understood by all team members; and • Reduce social loafing by fostering member identifiability but also strong group identity and cohesiveness; encouraging group discussion and interaction; providing useful and immediate feedback and rewards for excellent group performance; and providing groups with novel and challenging tasks.

Intergroup relations Stereotyping and prejudice As mentioned on the previous page, social identity theory (Hogg & Abrams, 1988) argues that when group members identify with a group, they internalise the norms and beliefs that are prototypical of that group, beliefs about and attitudes towards other groups (outgroup stereotypes and prejudice), and stereotypes of and preference for the ingroup. These stereotypes and feelings generally reflect the nature of real social relations between groups – that is, whether groups are of differing status, compete with each other, and so on. As Matlin (1991) discusses, when one’s group identity is made salient (e.g., when class discussion turns to gender differences in housework), these stereotypes and prejudices can impact upon behaviour towards members of one’s own and other groups, with a number of implications for the HE context. However, stereotypes also impact upon expectations regarding how members of the ingroup and outgroups should behave. Such expectancy effects can be very powerful within the educational context, particularly when held by educators, with strong evidence emerging that

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educator expectancies can serve as self-fulfilling prophecies (Rosenthal & Jacobson, 1992), operating not only through discriminatory educator behaviour but also through the impact of that on student self-concept, self-efficacy and motivation (Bandura, 1997). Even when educator behaviour is in no way discriminatory, student performance can be impacted upon by the knowledge that such discrimination is possible and occurs in the wider society. Steele (1997, 1998; Steele & Aronson, 1995) identifies what he calls stereotype threat, the experience of being in a situation where one recognises that a negative outgroup stereotype could apply to oneself. His research shows that, in situations where one’s performance and related outcomes are very important, this stereotype threat can be distracting and upsetting, and impacts upon performance on high stake standardised tests. In addition, stereotype threat can affect behaviours as varied as participating in class, seeking help from staff, and contact with students in other groups. If it becomes a chronic feature of the educational environment, it can lead to disidentification with that environment, with the pain of stereotype threat relieved by losing identification with the part of life where the pain occurs. This necessarily includes a loss of motivation to succeed in that part of life, which can further reduce performance. In addition, stereotype threat most impairs students who most identify with achievement, often those who are also the most skilled, motivated and confident – the academic vanguard of the group. Essentially, a person has to care about a domain in order to be disturbed by the prospect of being stereotyped in it; students who do not identify with education do not experience any impact on performance due to stereotype threat.

Intergroup contact However, the university educational context can have a number of positive effects on intergroup relations. Importantly, contact with members of other student groups can reduce prejudice and stereotyping (e.g., Biernat, 1990; Fichten, Taglakis, & Amsel, 1989; Kay, Jensen-Osinski, Beidler, & Aronson, 1983), provided that such contact is equal status, cooperative, supported by authorities and stereotype disconfirming (Pettigrew, 1991). On the basis of analysis of a large US cross-institutional data set, Gurin (1999) concludes that diversity experiences during university have impressive effects on the extent to which graduates live racially or ethnically integrated lives in the post-university world. Students who experience the most diversity in classroom settings and in informal interactions with peers show the most: growth in intellectual engagement, motivation, intellectual and academic skills; engagement with active thinking processes, various forms of citizenship, and people from different races/cultures; and were the most likely to acknowledge that group differences are compatible with the interests of the broader community (Astin, 1993; King & Shuford, 1996). Such findings are also consistent with those obtained by Newcomb (Alwin, Cohen, & Newcomb, 1991; Newcomb, 1943; Newcomb, Koenig, Flacks, & Warwick, 1967), whose classic longitudinal investigation into how student attitudes and norms changed upon entering college (and were maintained after college) revealed the strong social influence of peers, as well as how the transition to the more complex social structure of the university environment challenges individuals, fostering deep thinking and cognitive growth. Even where students may not encounter a very diverse student body, participation in subjects such as the psychology of racism course described by Khan (1999) can have a positive effect on student attitudes if taught with sensitivity (see Khan for a number of suggestions as to how best to do this). As Kowalski (2000) points out, the study of diversity conveys information about individual differences, psychological processes and scientific biases, and has practical implications for students’ current and future behaviour.

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Implications for teaching Research into intergroup relations leads to a number of recommendations for psychology educators: • Be aware of stereotypes of different groups of students within your particular educational context; • Make contact between groups as equal status, pleasant, stereotype disconfirming and cooperative as possible, and make it clear that such positive contact is supported by teaching staff and other authorities; and • Consider the impact of group norms upon student behaviour.

Persuasion and attitude change The research on persuasion and attitude change has many implications for psychology teaching. Ultimately, as Fives and Alexander (2001) point out, educators want to persuade their students towards learning; persuasion, like teaching, involves convincing others to look differently or more deeply at some concept or subject. A well-crafted message in the form of classroom discourse or text becomes a mechanism for fostering discussion and reflection (Hynd, 2001). Murphy (2001) argues that the perception of teaching as persuasion: • Rejects the idea that there can be simple of transmission of knowledge from educator to student and the assumption that all students will accept whatever information is introduced into the learning environment fully or in part; • Accepts learning as a change in students’ knowledge, beliefs and interests; • Acknowledges and values the ideas and feelings that learners bring to the classroom environment; • Recognises the power of messages in shaping understanding; • Holds that there is no singular view or understanding in relation to complex concepts, and that these competing views are worthy of exploration; • Assumes that deep-seated changes in students’ understandings come from reaching into the social/cultural, motivational, as well as cognitive realms; and • Is responsive to the informational demands placed on students in today’s post-industrial world. As with most areas of psychology, there are a variety of theories of persuasion and attitude change, some of which will now be explored.

Cognitive dissonance theory According to cognitive dissonance theory (Festinger, 1957), individuals have a tendency to seek consistency among their cognitions (e.g., attitudes, beliefs), and between their cognitions and behaviours. For example, people tend to prefer that their actions are consistent with their beliefs and attitudes. When an inconsistency occurs, cognitive dissonance, a negative experience, is the result. The strength of the dissonance is affected by the number of dissonant cognitions, and by the importance attached to each one. Because dissonance is seen as an intrinsically negative state, the dissonance is resolved in one of a number of ways: by reducing the importance of the dissonant cognitions; adding more consonant cognitions that outweigh the dissonant ones; changing behaviour; or changing cognitions. In a classic study of cognitive dissonance with particular implications for teaching, Festinger and Carlsmith (1959) showed that if too much justification is given for the performance of an

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unpleasant or otherwise cognitively-inconsistent behaviour (in that study, lying to a confederate), individuals may resolve any cognitive dissonance experienced not by changing their attitude but by justifying their behaviour in terms of the reward (the over-justification effect). This finding is not predicted by other theories of persuasion based on behavioural theory (e.g., Hovland, Janis, & Kelley, 1953), which would predict attitude change in the direction of the reinforced behaviour (see page 27). However, it is consistent with much of the research into intrinsic motivation (see page 53).

The elaboration likelihood model In their well-known and well-supported elaboration likelihood model of persuasion (ELM), Petty and Cacioppo (1986) propose that there are two forms or routes of persuasion. In central route processing, people elaborate upon the message arguments, process them more deeply and tie them to existing knowledge. Learning and persuasion through the central route is more durable and impactful and more likely to influence subsequent behaviour (though if the processed message is rejected it may result in change in the undesired direction, what is known as the boomerang effect). In peripheral route processing, by comparison, individuals do not process the message deeply, but instead use cues from the message (e.g., the length of the article) or the author, or other heuristics, to make decisions about the importance or value of the message and whether it is therefore accepted. Research in both the attitude change and learning literatures confirms that both learners’ characteristics (e.g., background experience) and aspects of the message (e.g., the author’s perceived purpose and credibility, or the argument structure) play important roles in the persuasion process. In terms of learner characteristics, central route processing of a message is more likely if the learner has: • The motivation to process the message, generally because it is relevant. For example, Murphy (1998, cited in Murphy, 2001) found that students’ pre-existing knowledge, beliefs and interest in a particular topic or text played a fundamental role in what those students came to learn, while material that has been related to the self is best remembered (Forsyth & Wibberley, 1993; Hartlep & Forsyth, 2000); • The ability to process the message, which requires both the ability to comprehend it and not being too distracted or cognitively overloaded to process it. For example, Dole and Sinatra (1998) report that those with greater comprehension skills are more apt to use central route processing. Repetition of the message can also foster comprehension of it; • Weak pre-existing beliefs or attitudes, as strong pre-existing beliefs may bias the depth and nature of processing of the message (e.g., Chinn & Brewer, 1993; Fishbein & Ajzen, 1975; Guzzetti & Hynd, 1998; Lord, Ross, & Lepper, 1979); • Accessible and relevant pre-existing beliefs (e.g., Wood & Kallgren, 1988, found that those more capable at retrieving relevant beliefs were more likely to process the message); and • Some relevant knowledge, but not too much, as this may bias or reduce processing, what is known as biased assimilation (Petty & Cacioppo, 1986). In relation to message characteristics, the route of persuasion is influenced by: • The strength of the message, with central route processing more likely when arguments are causal or explanatory in nature (Ford & Smith, 1991); • Other aspects of the message (e.g., its length, its understandability, its capacity to evoke emotion, its interest, whether it is one- or two-sided, the number of arguments presented, etc). These can serve either as peripheral cues and therefore foster peripheral route processing, or provoke central route processing, depending upon the context and learner characteristics; and

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• The expertise and credibility of the message communicator, which can again either foster peripheral or central route processing, depending upon the context. Consistent with this literature about the effects of message consistency with one’s pre-existing opinion, Budesheim and Lundquist (1999) investigated the effects of in-class debates on students’ attitudes toward the issues they debated, in three different psychology subjects. Results indicated that arguing a position consistent with one’s opinion did produce biased assimilation, but that arguing for a position inconsistent with one’s opinion reduced this tendency.

Implications for teaching Research into persuasion leads to a number of recommendations for teaching, including: • Encourage students to voluntarily engage in study behaviours about which they have a negative attitude (e.g., revising texts or solving problems), in order to foster cognitive dissonance and thereby attitude change; • Do not provide too many incentives for students to engage in unpleasant behaviours, as this may deter students from changing their beliefs to become more positive towards such work; and • In order to foster deep processing of study material, activate students’ relevant beliefs and knowledge before providing the message; maximise the comprehensibility of the message and the strength of the arguments it contains; emphasise the credibility of the source of the information; and increase the relevance of the material to the student.

Leadership The psychological research into leadership has a number of implications for the practice of teaching psychology. In many ways the lecturer or tutor can be seen as the ‘leader’ of the class of students, managing their classrooms, and meeting five distinguishing characteristics of leadership (Adair, 1983): giving direction, offering inspiration, building teamwork, setting an example, and gaining acceptance of their own leadership. However, educators in HE may also seek to foster leadership within students (particularly postgraduates), who may be or become leaders in their own areas of endeavour. Theories of leadership fall into three main types: trait, style, and contingency theories. Trait theories focus on the personality and other characteristics of leaders, and suggest that leadership cannot be taught, but that one is ‘born’ a leader. More profitable in terms of fostering leadership are style theories of leadership, which focus on how the way in which leaders approach their roles in given situations fosters success or failure. Lewin, Lippit and White (1939), for example, after examining the leadership styles of youth leaders, came up with a threefold typology: authoritarian leaders, who create a sense of group dependence on the leader, with work only done when the leader is present; laissez-faire leaders, who foster little work whether they are present or absent; and democratic leaders, who achieve group cohesion and harmonious working relations whether they are present or not. Typologies of educator styles paralleling Lewin et al.’s leadership styles have also been developed. For example, McKeachie, Lin, Moffett and Daugherty (1978) contrast directive and facilitative styles of teaching, while Edwards (1993) differentiates between autocratic (essentially authoritarian), permissive (laissez-faire) and democratic teaching styles.

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Unsurprisingly, these authors, as well as others (e.g., Rohrkemper, 1984), find that a democratic/facilitative style of teaching is most effective in facilitating learning and motivating students. While some early studies on leadership style tended to assume such styles were immutable, more recent research (including the educational studies in the previous paragraph) show the usefulness of tailoring one’s style to the situation. For example, Hersey and Blanchard’s (1977) situational leadership theory distinguishes between attention to the task to be achieved and the relationship with ‘followers’ (e.g., students), and identifies four resulting leadership styles: delegating (low relationship and low task focus); supporting (high relationship and low task focus); coaching (high task and high relationship focus); and directing (high task and low relationship focus). Hersey and Blanchard suggest that the ‘maturity’ level of followers – defined as the capacity to set high but attainable goals, willingness and ability to take responsibility, and education and/or experience of an individual or group, which can vary across tasks and over time – influences the degree of emphasis which the leader needs to place on task or relationship behaviour at any given time. According to Blanchard and Zigarmi (1991), different leadership styles are more appropriate with followers of different levels of maturity (operationalised as competence and commitment): • With followers of low competence but high commitment, directing is more appropriate; • With followers with some competence and low commitment, coaching is recommended; • With followers of high competence and variable commitment, supporting is best; and • With followers of high competence and high commitment, delegating is recommended. Contingency theories such as Fiedler’s (1971, 1976) theory argue that successful leadership is contingent upon the situation as well as upon the people involved, recognising the complexity of the relationships between these factors. According to Fiedler, leadership effectiveness is influenced by the extent to which the task is structured, the leader’s power, and the nature of the relationship between the leader and followers. Fiedler found that a structuring or task-focused leadership style was especially effective where the situation was either strongly favourable or unfavourable to the leader; when only moderately favourable, supportive or relationship-focused styles worked best. Handy (1993) extended Fiedler’s approach by arguing that Fiedler’s factors all depend to some degree on a fourth factor, the environment, made up of the organisational setting of the leader, their group, and the importance of the task.

Implications for teaching To summarise, research into theories of leadership lead to a number of recommendations for teaching practice: • Recognise that the appropriateness of a particular leadership behaviour will depend upon the context, which can vary over time; • Pay attention to different aspects of the context, reflect on how student behaviour may best fit the demands of the context, and attempt to be flexible and responsive to the context; and • Consider changing your leadership style as an educator as students mature and develop in competence and commitment; fostering autonomy may become increasingly important as their competence increases.

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Barriers to and facilitators of learning Although students may be highly able and motivated to learn at university and college, in many cases their levels of achievement within HE may be negatively impacted upon by various unanticipated or underestimated psychological factors, such as stress or anxiety. Some of these factors are addressed in the following subsection of the report, along with other variables that psychological research suggests may serve as facilitators of student performance.

Arousal and emotion A large body of research shows that physiological arousal, often associated with high levels of emotion, can impact upon learning and performance. One of the most important findings in relation to arousal is known as the Yerkes-Dodson law (Yerkes & Dodson, 1908), which predicts an inverted U-shaped relationship between arousal and performance. Across a broad range of performance settings it has been shown that both low and high levels of arousal produce minimum performance, whereas a moderate level of arousal results in maximum performance in a task – some mid-level of arousal provides the motivation to perform. Too little arousal has a frustrating effect on the learner, while too much has a hyperactive effect. There is an optimal level of arousal for each individual at any given time and depending upon the task. The optimal level of arousal is lower for more difficult or demanding tasks (learners need to concentrate on the material), and higher for tasks requiring endurance and persistence (learners need more motivation). If the level of arousal drops below the optimal level, the person will seek stimulation (engage in exploratory behaviour) (Berlyne, 1960). When arousal is associated with strong emotion, as in the case of emotional events such as crises and traumas, the relationship between learning and arousal becomes linear, with emotional events (and particularly negative ones) better remembered than non-emotional events (Blakemore & Frith, 2000), probably because this type of learning is important for survival. Within the educational context, this suggests that educators should attempt to maximise the enjoyment students obtain from learning activities, to increase their memorability.

Anxiety Moving onto negative emotions, anxiety has received considerable research attention. It is usually triggered by a situation that involves a decision or judgement; tests and examinations are common precursors of anxiety in educational settings (Everson, Tobias, Hartman, & Gourgey, 1993). While every student feels some anxiety at some time, for certain students anxiety seriously inhibits learning or performance. The main source of anxiety in education is the fear of failure and, with it, the loss of self-esteem. Unsurprisingly, low achievers are particularly likely to suffer from it, but it is not restricted to them. Anxiety has been shown to impair performance in a wide range of cognitive functions including attention, memory, concept formation and problem-solving (e.g., Sieber, O’Neil, & Tobias, 1977; Spielberger, 1966). Anxious students may suffer from less thorough acquisition of the information to be examined; a lack of basic domain-specific skills; interference in the retrieval of prior learning; difficulty using or transferring knowledge they possess; difficulty demonstrating their knowledge on tests; being self-conscious in performance settings, 68

distracting attention from the task at hand; or some combination of these. However, the impact of anxiety interacts with task difficulty, with anxiety resulting in poorer performance in complex tasks but at times improving performance on very simple tasks. This interaction has been explained by drive reduction theory (Hull, 1940), which posits that arousal increases the strength of responding, but competing responses are activated in complex tasks. Different sorts of anxiety can operate and impact differentially on academic performance. A distinction is generally made between state anxiety (increased arousal due to environmental factors) and trait anxiety (an individual’s characteristic way of reacting to arousal, correlated with self-esteem and defensiveness), with a person’s total level of anxiety a function of both types. In addition, anxiety can be specific to different domains (Everson et al., 1993), such as test anxiety, mathematics anxiety and statistics anxiety (Dillon, 1982). High test anxiety predicts poor academic performance (Zeidner, 1998), as well as lower academic self-esteem. A number of scales measuring different aspects of test anxiety have been developed, such as the Test Anxiety Inventory (used in Musch & Broder, 1999) and the Revised Test Anxiety Scale (McIlroy, Bunting, & Adamson, 2000). Musch and Broder suggest that the relative contribution of test anxiety and academic skill may be different for different domains and specific subject matters under consideration. Studies of test anxiety in psychology students confirm that test anxiety is an important predictor of performance in that domain. Smith, Arnkoff and Wright (1990), for example, found that both test anxiety and academic skills were associated with final course mark, with test anxiety relatively more important than other variables in their analysis, while McIlroy et al. (2000) found that cognitive aspects of test anxiety (worry, and test irrelevant thoughts) were the most substantial negative predictors of examination performance. As in other studies, personality factors known to be related to academic performance, such as self-efficacy and academic locus of control, also emerged as systematically related to test anxiety. Many psychology students also experience statistics anxiety and/or mathematics anxiety. Zeidner (1991) investigated statistics anxiety and mathematics anxiety in social science students (including psychology ones) and found that, as with mathematics anxiety, two factors underlay statistics anxiety scores: statistics test anxiety and content anxiety. Statistics anxiety correlated negatively with high school scores in mathematics as well as with perceptions of maths abilities. The data provided support for the idea that aversive prior experiences with mathematics, prior poor achievement in maths and a low sense of maths self-efficacy are meaningful antecedents of statistics anxiety. The test anxiety literature suggests a number of possible treatments for the problem, and favours a multimodal approach in its treatment (Hembree, 1988; Zeidner, 1998). Many of these are aimed at changing students’ attitudes about their personal competence, aiming to increase the expectation of success. Where test-anxious students suffer from retrieval problems due to worry and test-irrelevant thoughts, cognitive therapy and relaxation techniques such as relaxation therapy, systematic desensitisation, thought stopping, meditation and biofeedback may be useful. For those with problems in all stages of information-processing, academic and study skills training may be useful, such as in time management. It has also been found that interventions designed to improve self-efficacy and academic locus of control have helped both to reduce test anxiety and improve exam performance. Highly anxious students also tend to learn better with more structured instructional approaches, where student interaction is not expected or required, and can benefit from increased time for assignments and tests and more formative feedback. In addition, creating a classroom climate that is accepting, comfortable and non-competitive helps. 69

Stress Within the HE context, stress can be experienced by both educators and students. As many have pointed out, stress of itself is neither good nor bad – its impact is dependent on the environment, the person and the person-environment interface. Medical and neuropsychological research evidence suggests that individuals need a certain level of stress to function effectively, and that such optimal levels of stress can foster learning, creativity and innovation (Blakemore & Frith, 2000). The amount of stress an individual can withstand, however, appears to be highly dependent on individuals themselves, their personalities, the context within which they operate and how they perceive stressful situations/life stressors. Research suggests that stress can be seen to arise from the balance between one’s perceived demands and perceived personal resources, with an imbalance leading to a perception of stress. Personal coping strategies can help one deal with the resulting imbalance, including such strategies as getting to know one’s own personal limits and capabilities, consciously developing personal skills and resources to meet any demands one chooses to take on (rather than have imposed on one); and becoming actively aware of relevant life stages, life events and non-work pressures facing one so that one does not overly stretch one’s mental and physical coping skills.

Problem: Emotional impact of postgraduate clinical psychology training Context:

Clinical and counselling psychology

Theories: Stress research O’Halloran and O’Halloran (2001) apply the stress research in relation to graduate level psychology courses, focusing on the importance of anticipating and addressing the secondary traumatic stress (STS) such students experience in coursework relating to trauma and violence (Stamm, 1995). Because level of therapeutic experience mediates STS, it is probable that students new to the field of clinical and counselling psychology are particularly likely to be distressed in classes on trauma (Seegmiller, 1995). The authors use Herman’s (1997) model for treating survivors of trauma (which states that to progress to recovery, survivors must move through the stages of establishing their own safety; remembrance of and mourning over experiences and losses; and reconnection with themselves and others) as a framework for recommendations for ameliorating STS in the classroom. They also suggest biobehavioural, affective-cognitive, relational and spiritual strategies for self-care, which can be used outside of the classroom by both students and lecturers.

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Psychotherapy With the publication of Goleman’s recent books on emotional intelligence (Goleman, 1995, 1998) has come a resurgence of interest within HE on developing emotional competence or intelligence in students. While such an interest raises questions for some educators about the nature of the boundary between education and psychotherapy, Gregory (2002) argues that the boundary is by no means rigid if one adopts a humanistic perspective, and defines psychotherapy as a non-clinical, growth-oriented activity focusing on personal development. Murphy (2000) argues that both professions are considered helping ones, aimed at enhancing the quality of life; both require the participant’s active engagement to be effective; and both occur in a social communicative context characterised by varying levels of information exchange and emotional/behavioural interaction. On the basis of these similarities, he suggests that university teaching can be enhanced by the educator’s knowledge and application of what research shows to work in therapy. Bassin (1974) describes an early example of this strategy, in which the principles and structures of the therapeutic community were adapted to the classroom, which was viewed as a microcosm of an anomic and lonely civilisation. To deal with this, therapeutic community techniques were structured into the course design, such as goal-setting and contract negotiation, rotating of leadership roles, nameplates, the use of an ombudsman, feedback and evaluation. According to recent research on what works in therapy, successful change occurs primarily as a result of four interrelated factors (Asay & Lambert, 1999): client factors (personal resources, strengths, beliefs); relationship factors (therapists’ empathy, acceptance, warmth); hope factors (clients’ and therapists’ expectations for change); and model/technique factors (therapists’ theoretical orientation and intervention techniques and how suited these are to the client). These factors are interrelated in that the enhancement of one factor strengthens the others. In education, these are paralleled by student factors (what the student brings to the learning context, including their unique life experiences); relationship factors (the educators’ genuine interest, acceptance and support for the student); hope (students’ and educators’ expectations for success and failure); and technique factors (educators’ teaching techniques and philosophy and how suitable these are for the client). On the basis of these parallels, Murphy (2000) suggests a number of instructional techniques which can enhance university teaching, including encouraging students to explore how their life experiences can contribute to their effectiveness in their discipline; making genuine and ongoing efforts to assess students’ response to instruction; and where appropriate actively collaborating with students on instructional decisions.

Resilience Paralleling the new focus within psychology as a whole on positive psychology (Seligman, 1999), and within clinical psychology on psychological resilience, in recent years educational researchers have investigated educational resilience, defined as the heightened likelihood of educational success despite personal vulnerabilities and adversities brought about by environmental conditions and experiences (Wang, Haertel, & Walberg, 1994). This research has generally focused on primary and secondary school students, but has more recently begun to be utilised with university students. For example, Morales (2000) explored protective

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factors in the lives of a number of academically resilient university students, and present the concept of a ‘resilience cycle’ and its practical implications. Based on the results of a large number of reviews and meta-analyses, Wang, Haertel and Walberg (1993) identify a range of learner characteristics and features of the home, classroom and community contexts that may mitigate against negative life circumstances while facilitating development and educational resilience. These include classroom practices such as educator actions and expectations, effective instructional methods and curriculum, and policies and climate. Problem: Fostering engagement in course content Context:

Abnormal psychology

Theories: Resilience research Duffy’s (2000) vision of a new approach to teaching grew out of her expertise as a practising psychologist. Rather than focusing on the problems that people face, Duffy organised her abnormal psychology course around the topic of resilience. She reports that this focus on resilience was not only less overwhelming than a focus on problems, but was more hopeful and hope-giving, and, according to Duffy, engaged students more effectively in the course content. It also had strong policy implications, which she emphasised in her course. In terms of assessment, Duffy attempted to recognise the diversity in her class, opening assessment up to different forms of intelligence and ways of knowing, and focusing on engendering competence rather than on extinguishing it. As a consequence she utilised a variety of different assessment techniques. One such was a critical incident group project, where a small group of students analysed a critical incident from the service learning (learning out in the community, in ‘real life’) of one of its members. In addition, students who were not working in a community setting were asked to create a programme that would engender resilience on a particular problem in some identified age group, which could involve trips to community groups and settings as well as more traditional literature searches. In order to foster resilience in her own students, Duffy also required students to map out their use of time for the 24 hours of every day in a week, explaining the task in terms of the need to create a context for success in the course by allocating sufficient time to study – if students set themselves up for failure and then fail and feel badly about themselves, this does not foster resilience.

Implications for teaching The research into barriers and facilitators of learning leads to a number of recommendations for psychology teaching, including: • Try to ensure that learning activities are not extremely arousing or stressful, to reduce student discomfort and the negative impact of such processes on learning. However, make sure activities are sufficiently interesting to produce a moderate level of arousal; • Where learning activities are intrinsically stressful (e.g., postgraduate clinical psychology training), give students the opportunity, in class time and outside it (e.g., by using communication and information technologies), for debriefing, social support and one-onone supervision and counselling; • Make classroom climates as accepting, comfortable and non-competitive as possible. Try to demonstrate genuine interest in and support for the students as individuals, and attempt to foster student autonomy;

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• Design class activities to facilitate the improvement of academic self-efficacy and locus of control, by allowing students opportunities to succeed and achieve, and providing unambiguous feedback to ensure that they are clear about their good performance; • In statistics and other subjects where students suffer from anxiety, consider the use of more structured educational approaches, increased time for assignments and tests, and more formative feedback; and • Encourage students with high levels of test and other forms of anxiety, and/or high levels of stress, to seek assistance in dealing with these through cognitive therapy and relaxation techniques, and academic and study skills training focusing on time and stress management and coping skills.

Assessing student learning The importance of assessment has been a common theme throughout this report. The vast research literature on psychometrics (psychological measurement) and assessment has many implications for the practice of psychology teaching (Newstead, 1992b, 1996). Psychometric theory provides a general collection of techniques for evaluating the development and use, in assessment, of psychological and educational tests. In classical test theory (Lord & Novick, 1968), a relatively simple model for mental testing which has a strong emphasis on reliabilility, the test score is a combination of a true score and measurement error. This measurement error can be defined in several ways depending on the way one would like to generalise to other testing situations. Generalisability theory (e.g., Cronbach, Linn, Brennan, & Haertel, 1997) focuses on this problem, giving a framework in which the various aspects of observed test scores can be dealt with, allowing the decomposition of scores into components representing the impact of systematic factors, such as raters or test conditions, on scores. In item response theory (Birnbaum, 1968; Lord, 1980), the unit of analysis is the item rather than the test. In IRT models the variance of measurement errors is a function of the level or ability of the respondent, an important characteristic which is somewhat neglected by classical test theory (Hambleton & Jones, 1993). Other important theoretical approaches are multidimensional item response theory, structural equation modelling, and scaling theory (see Murphy & Davidshofer, 2001). However, despite the psychological expertise that has been built up over the years, psychologists are patchy in applying their expertise to assessing the performance of their own students. In relation to item and test construction, for example, the theoretical literature is more often applied. For example, in test banks for introductory psychology textbooks, Mentzer (1982) unearthed many multiple-choice items in which length of response cued students to the correct response choice, while Scialfa, Legare, Wenger and Dingley (2001) found inconsistent item difficulty and discriminability across chapter topics. Research-based recommendations relating to good practice in item and test construction are provided in Berk (1998), Scialfa et al. (2001), Stirling (1996) and Stalder (2001). However, the very assessment technique chosen, regardless of how well an individual example of it is constructed, may not meet the most basic principles of assessment – reliability, validity, fairness, standardisation, and unfakeability (Newstead, 2002). As Newstead (1992b) points out, the most common assessment technique used by psychology academics is still the examination, and research evidence suggests that some psychology examinations may be inadequate in relation to reliability of markers (Caryl, 1999; Dracup,

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1997; Laming, 1990; Newstead & Dennis, 1994), lack of agreed criteria against which test performance can be compared, poor predictive validity of degree and other examinations (Kornbrot, 1989), freedom from bias caused by knowledge of the student or other factors (Hartley, 1992; Newstead & Dennis, 1990), and lack of standardisation (at least across departments; Connolly & Smith, 1986; Larrington & Lindsay, 2002; Smith, 1990). In addition, tests and examinations can often reinforce more surface approaches to learning rather than deeper understandings (Connor-Greene, 2000; Jones, 1988; Newstead & Findlay, 1997). Although there has been a move in recent years away from assessing students through formal examinations towards assessing them with coursework, and especially coursework essays, coursework may not be a wholly adequate substitute for examinations. Evidence suggests that coursework encourages surface approaches to learning (Newstead, 2002), as well as student cheating (Newstead, Franklyn-Stokes, & Armstead, 1996). Marker consistency and bias may also be problematic (Bradley, 1984, 1994; Dennis & Newstead, 1994; Dennis, Newstead, & Wright, 1996; Johnson, 1985; Newstead & Dennis, 1990).

Problem: Promoting student learning Context:

Abnormal psychology, women and psychology

Theory:

Assessment

Connor-Greene (2000) discusses the fact that while many teaching methods have been modified to encourage higher-level thinking, approaches to testing often remain unchanged, reinforcing memorising rather than critical thinking. She describes the use of daily essay quizzes to encourage thorough preparation for class and higher-level thinking. Students in her women and psychology subject received daily quizzes, while students in abnormal psychology had four scheduled tests over the course of the semester. Teaching evaluations supported the perceived value of the daily testing method in enhancing student learning. However, the predictable tests resulted in greater last-minute preparation and student perceptions of less learning.

Given all these difficulties, Newstead (2002) concludes that in general assessment has a negative effect on students, rather than being the driver of conceptual understanding and a deep approach to learning. However, given the need to assess students, he suggests investigating the advantages and disadvantages of differing types of assessment before deciding which one to use in any particular subject.

Implications for teaching Based on research into assessment and measurement, it is recommended that psychology educators: • Consider both the reliability and validity of assessment measures, when developing and selecting them; • Be aware of the literature relating to good test item construction; and • Wherever possible, use assessment measures that foster a deep approach to learning within students (e.g., that require active learning, and critical thinking).

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Conclusion The present research report explores how psychology research, theory and knowledge can be and has been applied to teaching practice in psychology, in the hope that this will lead to improved psychology teaching and learning, through mechanisms such as new course structures, classroom activities, assessments, forms of feedback, and web-based activities. However, simply because an innovation is research-informed does not guarantee that it will have a positive or indeed any impact. As with all educational change, research-informed innovations should be evaluated in terms of their impact on student learning, staff teaching, and departmental resourcing, both in the short-term and the long-term (e.g., after the subject concludes, and students move on to other subjects). Evaluation should also seek and document unintended consequences of the innovation – as the project case studies (see http://ltsnpsy.york.ac.uk/LTSNPsych/r2p.htm) show, these can have quite a major impact on the overall success of the innovation. Action research can provide a useful, theoreticallygrounded methodology for such evaluations, as well as for pedagogical research in psychology in general – see Norton (2001b), and her LTSN Psychology website area (http://ltsnpsy.york.ac.uk/LTSNPsych/Specialist/sp005.htm) for guidance on this. To conclude, we hope readers of this report have been encouraged to consider applying their own psychology disciplinary knowledge to their psychology teaching practice, if they are not already doing so. It is also hoped that this report may lead to replication and extension of some of the studies described in this document, to determine to what extent methodologies and results can be generalised beyond the original study context. Such replicability is a key strength of psychology research in general, and one that should be fostered in psychology pedagogical research. We would urge anyone engaging in such research-informed innovations to share their experiences with other members of the UK (and international) psychology community by posting a brief report on their work, and its outcomes, on the online database of practice associated with this project (http://ltsnpsy.york.ac.uk/LTSNPsych/r2p.htm). We hope this database will not only assist the academics concerned, but foster a sense of intellectual excitement about the field. Keep checking the database for more inspiration!

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References Adair, J. (1983). Effective leadership. London: Pan. Alexander, P. A. (1992). Domain knowledge: Evolving themes and emerging concerns. Educational Psychologist, 27, 33-51. Alwin, D. F., Cohen, R. L., & Newcomb, T. L. (1991). Political attitudes over the life span. Madison: University of Wisconsin Press. Amabile, T. M. (1996). Creativity in context. Boulder, CO: Westview Press. Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84, 261-271. Anderson, J. A., & Adams, M. (1992). Acknowledging the learning styles of diverse student populations: Implications for instructional design. New Directions for Teaching and Learning, 49, 19-34. Anderson, L. M., Blumenfeld, P., Pintrich, P. R., Clark, C. M., Marx, R. W., & Peterson, P. (1995). Educational psychology for teachers: Reforming our courses, rethinking our roles. Educational Psychologist, 30, 143-157. Anthony, W. (1983). The development of extraversion and ability: Analysis of data from a large-scale longitudinal study of children tested at 10-11 and 15-18 years. British Journal of Educational Psychology, 53, 374-379. Arnold, J., Newstead, S. E., Donaldson, M. L., Reid, F. J., & Dennis, I. (1987). Skills development in undergraduate psychology courses. Bulletin of the British Psychological Society, 40, 469-472. Aronson, E., Blaney, N., Stephan, C., Sikes, J., & Snapp, M. (1978). The jigsaw classroom. Beverly Hills, CA: Sage. Asay, T. P., & Lambert, M. J. (1999). The empirical case for common factors in therapy: Quantitative findings. In M. A. Hubble, B. L. Duncan, & S. D. Miller (Eds.), The heart and soul of change: What works in therapy (pp. 33-56). Washington, DC: American Psychological Association. Asch, S. E. (1946). Forming impressions of personality. Journal of Abnormal and Social Psychology, 41, 1230-1240. Asch, S. E. (1951). Effects of group pressure upon the modification and distortion of judgements. In H. Geutzknow (Ed.), Groups, leadership and men (pp. 177-190). New York: Carnegie. Astin, A. W. (1993). Diversity and multiculturalism on campus: How are students affected? Change, 25, 44-49. Atkinson, J. W. (1964). An introduction to motivation. Princeton, NJ: Van Nostrand. Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its component processes. In K. Spence & J. Spence (Eds.), The psychology of learning and motivation (Vol. 2, pp. 89-195). New York: Academic Press. Ausubel, D. P. (1963). The psychology of meaningful verbal learning. New York: Grune and Stratton. Ausubel, D. P. (1978). In defense of advance organizers: A reply to the critics. Review of Educational Research, 48, 251-257. Ausubel, D. P., Novak, J. D., & Hanesian, H. (1978). Educational psychology: A cognitive view (2nd ed.). New York: Holt, Rinehart and Winston. Baddeley, A. (1998). Human memory: Theory and practice (rev. ed.). Boston: Allyn and Bacon. Baillie, A., Porter, N., & Corrie, S. (1996). Encouraging a deep approach to the undergraduate psychology curriculum: An example and some lessons from a third-year course. Psychology Teaching Review, 5, 14-24. 76

Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice Hall. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman. Barber, N. (1994). Reducing fear of the laboratory rat: A participant modelling approach. Teaching of Psychology, 21, 228-230. Barrie, S. C., Buntine, M. A., Jamie, I., & Kable, S. H. (2001). APCELL: Developing better ways of teaching in the laboratory. In A. Fernandez (Ed.), Proceedings of Research and Development into University Science Teaching and Learning Workshop, April 20, 2001, The University of Sydney (pp. 23-28). Sydney: Uniserve Science, University of Sydney. Retrieved August 29, 2002, from http://science.uniserve.edu.au/pubs/procs/wshop6/ rdws002.pdf Bass, R. (1999). The scholarship of teaching: What’s the problem? Inventio, 1(1). Retrieved August 29, 2002, from http://www.doiiit.gmu.edu/Archives/feb98/randybass.htm Basseches, M. (1984). Dialectical thinking and adult development. Norwood, NJ: Ablex. Bassin, A. (1974). The therapeutic community teaching concept in behavioural science education. Teaching of Psychology, 1, 64-68. Batanero, C., Estepa, A., & Godino, J. D. (1997). Evolution of students’ understanding of statistical association in a computer-based teaching environment. In J. B. Garfield & G. Burrill (Eds.), Research on the role of technology in teaching and learning statistics: Proceedings of the 1996 IASE Round Table Conference (pp. 191-205). Voorburg, The Netherlands: International Statistical Institute. Baumann, J. (1988). Direct instruction reconsidered. Journal of Reading Behavior, 31, 712718. Belbin, R. M. (1981). Management teams: Why they succeed or fail. Oxford: Heinemann. Belbin, R. M. (1993). Team roles at work. Oxford: Butterworth Heinemann. Belenky, M. F., Clinchy, B. M., Goldberger, N. R., & Tarule, J. M. (1986). Women’s ways of knowing: The development of self, voice and mind. New York: Basic Books. Bennett, C., Howe, C., & Truswell, E. (2002). Small group teaching and learning in psychology: A review of research in small-group teaching and suggestions for good practice (Report and Evaluation Series no. 1). York: LTSN Psychology, University of York. Berge, Z. L., & Collins, M. P. (Eds.). (1995). Computer mediated communication and the online classroom: Vol. 2. Higher education. Cresskill, NJ: Hampton Press. Berk, R. A. (1998). A humorous account of 10 multiple-choice test-item flaws that clue testwise students. Journal on Excellence in College Teaching, 9, 93-117. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/contents/article.php?article=170 Berlyne, D. (1960). Conflict, arousal, and curiosity. New York: McGraw Hill. Bernstein, D. (2002). Peer review of teaching: Course portfolio. Retrieved August 29, 2002, from http://kml2.carnegiefoundation.org/html/gallery/example_specific.php?id=18 Biernat, M. (1990). Stereotypes on campus: How contact and liking influence perceptions of group distinctiveness. Journal of Applied Social Psychology, 20, 1485-1513. Biggs, J. B. (1985). The role of metalearning in study processes. British Journal of Educational Psychology, 55, 185-212. Biggs, J. B. (1987). Student approaches to learning and studying. Melbourne: Australian Council for Educational Research. Biggs, J. B. (1989). Approaches to learning in two cultures. In V. Bickley (Ed.), Teaching and learning styles within and across cultures: Implications for language pedagogy (pp. 421-436). Hong Kong: Institute of Language in Education, Education Department.

77

Biggs, J. B., & Telfer, R. (1987). The process of learning (2nd ed.). Sydney: Prentice Hall. Birchmeier, Z., & Bakker, A. I. (2002, November). The effects of active learning techniques on college student motivation. Paper presented at the 22nd Annual Lilly Conference on College Teaching, Miami, OH. Retrieved November 18, 2002, from http://www.units.muohio.edu/lillycon/contributedabsta-c.shtml#birchmeier Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee’s ability. In F. M. Lord & M. R. Novick (Eds.), Statistical theories of mental test scores (pp. 397424). Reading, MA: Addison-Wesley. Bjork, E. L., & Bjork, R. A. (Eds.). (1996). Memory. San Diego, CA: Academic Press. Bjork, R. A. (1979). Information-processing analysis of college teaching. Educational Psychologist, 14, 15-23. Blackwell, R., Channel, J., & Wilson, J. (2001). Teaching circles: A way forward for part time teaching staff? International Journal for Academic Development, 6, 40-53. Blackwell, R., & Preece, D. (2001). Changing higher education. International Journal of Management Education, 3, 4-14. Blakemore, S.-J., & Frith, U. (2000). The implications of recent developments in neuroscience for research on teaching and learning. Paper presented at the Second Programme Conference of the Education and Social Research Council Teaching and Learning Research Programme, Birmingham. Retrieved November 18, 2002, from http://www.tlrp.org/pub/acadpub/Blakemore2000.pdf Blanchard, K., & Zigarmi, D. (1991). Leadership and the one minute manager. London: Willow Books. Bloom, A. J., Yorges, S. L., & Ruhl, A. J. (2000). Enhancing student motivation: Extensions from job enrichment theory and practice. Teaching of Psychology, 27, 135-137. Bloom, B. (1968). Learning for mastery. Evaluation Comment, 1, 1-5. Bloom, B. (1971). Mastery learning: Theory and practice. New York: Holt, Rinehart and Winston. Bobrow, D. G., & Collins, A. (Eds.). (1975). Representation and understanding: Studies in cognitive science. New York: Academic Press. Bradley, C. (1984). Sex bias in the evaluation of students. British Journal of Social Psychology, 23, 147-163. Bradley, C. (1994). Evidence of sex bias knocked out by blunt instrument? A comment on Hartley (1992). Psychology Teaching Review, 3, 19-23. Bransford, J. D. (1979). Human cognition: Learning, understanding, and remembering. Belmont, CA: Wadsworth. Bransford, J. D., & Johnson, M. K. (1972). Contextual prerequisites for understanding: Some investigations of comprehension and recall. Journal of Verbal Learning and Verbal Behavior, 11, 717-726. Bransford, J. D., Sherwood, R., Vye, N. J., & Rieser, J. (1986). Teaching thinking and problem solving: Research foundations. American Psychologist, 41, 1078-1089. Brehm, J. W., & Self, E. A. (1989). The intensity of motivation. Annual Review of Psychology, 40, 109-131. Broadbent, D. E. (1975). Cognitive psychology and education. British Journal of Educational Psychology, 45, 162-176. Brookfield, S. D. (1986). Understanding and facilitating adult learning. San Francisco, CA: Jossey-Bass. Brothen, T., Wambach, C., & Hansen, G. (2002). Accommodating students with disabilities: PSI as an example of universal instructional design. Teaching of Psychology, 29, 239240.

78

Brown, A. L., & Campione, J. C. (1996). Psychological theory and the design of innovative learning environments: On procedures, principles and systems. In L. Schauble & R. Glaser (Eds.), Innovations in learning: New environments for education (pp. 289-325). Mahwah, NJ: Erlbaum. Brown, G. (1997). Teaching psychology: A vade mecum. Psychology Teaching Review, 6, 112-126. Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18, 32-42. Bruner, J. (1960). The process of education. Cambridge, MA: Harvard University Press. Bruner, J. (1961). The act of discovery. Harvard Educational Review, 31, 21-32. Bruner, J. (1986). Actual minds, possible worlds. Cambridge, MA: Harvard University Press. Bruner, J. (1990). Acts of meaning. Cambridge, MA: Harvard University Press. Bryant, B. K. (1978). Cooperative goal structure and collaborative teaching. Teaching of Psychology, 29, 182-185. Budesheim, T. L., & Lundquist, A. R. (1999). Consider the opposite: Opening minds through in-class debates on course-related controversies. Teaching of Psychology, 26, 106-110. Buskist, W., Cush, D., & DeGrandpre, R. J. (1991). The life and times of PSI. Journal of Behavioral Education, 1, 215-234. Butler, A., Phillmann, K. B., & Smart, L. (2001). Active learning within a lecture: Assessing the impact of short, in-class writing exercises. Teaching of Psychology, 28, 257-259. Cabe, P. A., Walker, M. H., & Williams, M. (1999). Newspaper advice column letters as teaching cases for developmental psychology. Teaching of Psychology, 26, 128-130. Cacioppo, J. T., Petty, R. E., Feinstein, J. A., & Jarvis, W. B. G. (1996). Dispositional differences in cognitive motivation: The life and times of individuals varying in need for cognition. Psychological Bulletin, 199, 197-233. Cameron, J., & Pierce, W. D. (1994). Reinforcement, reward, and intrinsic motivation: A metaanalysis. Review of Educational Research, 64, 363-423. Carlsmith, K. M., & Cooper, J. (2002). A persuasive example of collaborative learning. Teaching of Psychology, 29, 132-135. Carney, R. N., & Levin, J. R. (1998). Coming to terms with the keyword method in introductory psychology: A “neuromnemonic” example. Teaching of Psychology, 25, 132-134. Carney, R. N., Levin, J. R., & Levin, M. E. (1994). Enhancing the psychology of memory by enhancing memory of psychology. Teaching of Psychology, 21, 171-174. Carroll, D. W. (1986). Use of the jigsaw technique in laboratory and discussion classes. Teaching of Psychology, 13, 208-210. Carroll, J. B. (1963). A model of school learning. Educators College Record, 64, 723-733. Caryl, P. G. (1999). Psychology examiners re-examined: A five-year perspective. Studies in Higher Education, 24, 61-74. Catanzaro, D. (1997). Course enrichment and the job characteristics model. Teaching of Psychology, 24, 85-87. Cerbin, W. (1996). Inventing a new genre: The course portfolio at the University of WisconsinLa Crosse. In P. Hutchings (Ed.), Making teaching community property: A menu for peer collaboration and peer review (pp. 52-56). Washington, DC: American Association for Higher Education. Cerbin, W. (1998). Problem-based learning in an educational psychology course. Retrieved August 29, 2002, from http://kml2.carnegiefoundation.org/html/gallery/ example_specific.php?id=8

79

Cerbin, W. (2000a). Investigating student learning in a problem-based psychology course. In P. Hutchings (Ed.), Opening lines: Approaches to the scholarship of teaching and learning (pp. 11-21). Menlo Park, CA: Carnegie Foundation for the Advancement of Teaching. Cerbin, W. (2000b). Using PBL to teach for understanding of disciplinary knowledge. Journal on Excellence in College Teaching, 11(2), 191-202. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/contents/article.php?article=226 Chester, A., & Gwynne, G. (1998). Online teaching: Encouraging collaboration through anonymity. Journal of Computer-Mediated Communication, 4(2), 1-9. Retrieved August 29, 2002, from http://www.ascusc.org/jcmc/vol4/issue2/chester.html Chinn, C. A., & Brewer, W. F. (1993). The role of anomalous data in knowledge acquisition: A theoretical framework and implications for science instruction. Review of Educational Research, 63, 1-49. Clark, J. M., & Paivio, A. (1991). Dual coding theory and education. Educational Psychology Review, 3, 149-210. Clibbens, J. (2000). Group discussion workshops in advanced undergraduate teaching: An evaluation. Psychology Teaching Review, 9, 11-15. Coate, K., Barnett, R., & Williams, G. (2001). Relationships between teaching and research in higher education in England. Higher Education Quarterly, 55, 158-174. Collingridge, D. S. (1999). Suggestions on teaching international students: Advice for psychology instructors. Teaching of Psychology, 26, 126-128. Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 453-494). Hillsdale, NJ: Erlbaum. Collins, A. M., & Loftus, E. F. (1975). A spreading-activation theory of semantic processing. Psychological Review, 82, 407-428. Connolly, K. J., & Smith, P. K. (1986). What makes a “good” degree: Variations between different departments. Bulletin of the British Psychological Society, 39, 48-51. Connor-Greene, P. A. (2000). Assessing and promoting student learning: Blurring the line between teaching and testing. Teaching of Psychology, 27, 84-88. Conway, M. A., Cohen, G., & Stanhope, N. (1992). Why is it that university grades do not predict very-long-term retention? Journal of Experimental Psychology: General, 121, 382-384. Cook, L. K., & Mayer, R. E. (1988). Teaching students about the structure of scientific text. Journal of Educational Psychology, 80, 448-456. Craik, F. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behavior, 11, 671-684. Craik, F. I. M., & Tulving, E. (1975). Depth of processing and the retention of words in episodic memory. Journal of Experimental Psychology, 104, 268-294. Cromley, J. (2000). Learning to think, learning to learn: What the science of thinking and learning has to offer adult education. Washington, DC: National Institute for Literacy. Retrieved August 29, 2002, from http://www.nifl.gov/nifl/fellowship/cromley_report.pdf Cronbach, L. J., Linn, R. L., Brennan, R. L., & Haertel, E. H. (1997). Generalizability analysis for performance assessment of student achievement or school effectiveness. Educational and Psychological Measurement, 57, 373-399. Cross, K. P. (1998). What do we know about students’ learning and how do we know it? Paper presented at the American Association for Higher Education 1998 National Conference. Retrieved August 29, 2002, from http://www.aahe.org/nche/ cross_lecture.htm

80

Cumming, G., & Thomason, N. (1995). Designing software for cognitive change: StatPlay and understanding statistics. In J. D. Tinsley & T. J. van Weerts (Eds.), World Conference on Computers in Education VI. WCCE 95, Liberating the learner (pp. 753-765). London: Chapman and Hall. Curry, L. (1987). Integrating concepts of cognitive or learning style: A review with attention to psychometric standards. Ottawa: Canadian College of Health Service Executives. Curry, L. (1990). A critique of the research on learning styles. Educational Leadership, 48, 50-52. Davidson, J. E., & Sternberg, R. J. (1998). Smart problem solving: How metacognition helps. In D. J. Hacker, J. Dunlosky & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 47-68). Mahwah, NJ: Erlbaum. Davis, M., & Hult, R. E. (1997). Effects of writing summaries as a generative learning activity during note taking. Teaching of Psychology, 24, 47-49. Deci, E. L. (1975). Intrinsic motivation. New York: Plenum. Deci, E. L., Eghrari, H., Patrick, B. C., & Leone, D. R. (1994). Facilitating internalization: The self-determination theory perspective. Journal of Personality, 62, 119-142. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum. Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227-268. Deci, E. L., Vallerand, R., Pelletier, L., & Ryan, R. (1991). Motivation and education: The selfdetermination perspective. Educational Psychologist, 26, 325-346. Dempster, F. N. (1988). The spacing effect: A case study in the failure to apply the results of psychological research. American Psychologist, 43, 627-634. Dempster, F. N. (1989). Spacing effects and their implications for theory and practice. Educational Psychology Review, 1, 309-330. DeNeve, K. M., & Heppner, M. J. (1997). Role play simulations: The assessment of an active learning technique and comparisons with traditional lectures. Innovative Higher Education, 21, 231-246. Dennis, I., & Newstead, S. E. (1994). The strange case of the disappearing sex bias. Assessment and Evaluation in Higher Education, 19, 49-56. Dennis, I., Newstead, S. E., & Wright, D. E. (1996). A new approach to exploring biases in educational assessment. British Journal of Psychology, 87, 515-534. Dewey, J. (1938). Experience and education. New York: Macmillan. Dillon, K. M. (1982). Statisticophobia. Teaching of Psychology, 9, 117. Dole, J. A., & Sinatra, G. M. (1998). Reconceptualizing change in the cognitive construction of knowledge. Educational Psychologist, 33, 109-128. Dolinksky, B. (2001). An active learning approach to teaching statistics. Teaching of Psychology, 28, 55-56. Doolittle, P. (1997). Vygotsky’s zone of proximal development as a theoretical foundation for cooperative learning. Journal on Excellence in College Teaching, 8(1), 83-103. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-topdf.php?article=137 Dracup, C. (1997). The reliability of marking on a psychology degree. British Journal of Psychology, 88, 691-708. Duffy, D. K. (2000). Resilient students, resilient communities. In P. Hutchings (Ed.), Opening lines: Approaches to the scholarship of teaching and learning (pp. 23-30). Menlo Park, CA: Carnegie Foundation for the Advancement of Teaching. Dunn, R. (1984). Learning styles: State of the science. Theory into Practice, 23, 10-19.

81

Dunn, R., Beaudry, J., & Klavas, A. (1989). Survey of research on learning styles. Educational Leadership, 46, 50-58. Dunn, R., Dunn, K., & Price, G. E. (1985). Learning Styles Inventory (LSI): An inventory for the identification of how individuals in Grades 3 through 12 prefer to learn. Lawrence, KS: Price Systems. Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41, 1040-1048. Dweck, C. S., & Elliott, E. S. (1983). Achievement motivation. In E. M. Hetherington (Ed.), Socialization, personality, and social development (pp. 643-691). New York: Wiley. Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273. Earley, C. (1989). Social loafing and collectivism: A comparison of the United States and the People’s Republic of China. Administrative Science Quarterly, 34, 565-581. Edwards, C. H. (1993). Classroom discipline and management. New York: Macmillan. Ellis, W. D. (1938). A source book of gestalt psychology. New York: Harcourt, Brace and World. Entwistle, N. (1972). Personality and academic achievement. British Journal of Educational Psychology, 42, 137-151. Entwistle, N. J., & Ramsden, P. (1983). Understanding student learning. London: Croom Helm. Entwistle, N. J., Tait, H., & McCune, V. (2000). Patterns of response to an approaches to studying inventory across contrasting groups and contexts. European Journal of Psychology of Education, 15, 33-48. Erwin, T. D., & Rieppi, R. (1999). Comparing multimedia and traditional approaches in undergraduate psychology classes. Teaching of Psychology, 26, 58-61. Evans, J. St.-B. T., Newstead, S. E., Allen, J. L., & Pollard, P. (1994). Debiasing by instruction: The case of belief bias. European Journal of Cognitive Psychology, 6, 263-285. Evans, L. (1998). Educator morale, job satisfaction and motivation. London: Chapman. Everson, H., Tobias, S., Hartman, H., & Gourgey, A. (1993). Test anxiety and the curriculum: The subject matters. Anxiety, Stress, and Coping, 6, 1-8. Eysenck, M., & Keane, M. (1995). Cognitive psychology. London: Erlbaum. Falchikov, N. (1995). Peer feedback marking : Developing peer assessment. Innovations in Education and Training International, 32, 175-187. Fenigstein, A., Scheier, M. F., & Buss, A. H. (1975). Public and private self-consciousness: Assessment and theory. Journal of Consulting and Clinical Psychology, 36, 1241-1250. Fensham, P., Gunstone, R., & White, R. (1994). The content of science: A constructivist approach to its teaching and learning. London: Falmer Press. Festinger, L. (1957). A theory of cognitive dissonance. Stanford, CA: Stanford University Press. Festinger, L., & Carlsmith, J. M. (1959). Cognitive consequences of forced compliance. Journal of Abnormal and Social Psychology, 58, 203-210. Fichten, C. S., Taglakis, V., & Amsel, R. (1989). Effects of cognitive modeling, affect, and contact on attitudes, thoughts, and feelings toward college students with physical disabilities. Journal of the Multihandicapped Person, 2, 119-137. Fiedler, F. (1971). Validation and extension of the contingency model of leadership effectiveness: A review of empirical findings. Psychological Bulletin, 76, 128-148. Fiedler, F. (1976). A theory of leadership effectiveness. New York: McGraw-Hill. Finke, R. A., Ward, T. B., & Smith, S. M. (1992). Creative cognition. Cambridge, MA: Bradford/MIT Press.

82

Finkel, D. (1999). Enhancing student involvement and comprehension through group and class discussions. Journal on Excellence in College Teaching, 10(3), 33-48. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-to-pdf.php?article=202 Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley. Fisher, C. B., & Kuther, T. L. (1997). Integrating research ethics into the introductory psychology course curriculum. Teaching of Psychology, 24, 172-175. Fives, H., & Alexander, P. A. (2001). Persuasion as a metaphor for teaching: A case in point. Theory into Practice, 40, 242-248. Fleming, V. M. (2002). Improving students’ exam performance by introducing study strategies and goal setting. Teaching of Psychology, 29, 115-119. Foos, P. W. (2001). A self-reference exercise for teaching life expectancy. Teaching of Psychology, 28, 199-201. Ford, L. A., & Smith, S. W. (1991). Memorability and persuasiveness of organ donation message strategies. American Behavioral Scientist, 34, 695-711. Forman, G., & Pufall, P. B. (Eds.). (1988). Constructivism in the computer age. Hillsdale, NJ: Erlbaum. Forsyth, D. R., & Wibberly, K. H. (1993). The self-reference effect: Demonstrating schematic processing in the classroom. Teaching of Psychology, 20, 237-238. Gagné, R. M. (1985). The conditions of learning (4th ed.). New York: Holt, Rinehart and Winston. Gagné, R. M. (1987). Instructional technology foundations. Hillsdale, NJ: Erlbaum. Gagné, R. M., Briggs, L. J., & Wager, W. W. (1992). Principles of instructional design (4th ed.). Fort Worth, TX: Harcourt Brace Jovanovich. Gagné, R. M., & Driscoll, M. (1988). Essentials of learning for instruction (2nd ed.). Englewood Cliffs, NJ: Prentice Hall. Gale, A. (1990a). Applying psychology to the psychology degree: Pass with first class honours, or miserable failure? The Psychologist: Bulletin of the British Psychological Society, 11, 483-488. Gale, A. (1990b). Psychology as God’s gift. In F. N. Watts (Ed.), The undergraduate curriculum in psychology (pp. 7-11) (Group of Teachers of Psychology Occasional Paper no. 9). Leicester: British Psychological Society. Galton, M. (2000, November). Integrating theory and practice: Teachers’ perspectives on educational research. Paper presented at the First Programme Conference of the Education and Social Research Council Teaching and Learning Research Programme, Leicester. Retrieved October 13, 2001, from http://www.tlrp.org/pub/ acadpub/galton2000.pdf Gardner, H. (1983). Frames of mind: The theory of multiple intelligences. New York: Basic Books. Gardner, H. (1993). Multiple intelligences: The theory in practice. New York: Basic Books. Gardner, H. (1998). Are there additional intelligences? The case for naturalist, spiritual, and existential intelligences. In J. Kane (Ed.), Education, information, and transformation (pp. 111-131). Upper Saddle River, NJ: Merrill-Prentice Hall. Garfield, J., & Ahlgren, A. (1988). Difficulties in learning basic concepts in probability and statistics: Implications for research. Journal for Research in Mathematics Education, 19, 44-63. George, P. G. (1994). The effectiveness of cooperative learning strategies in multicultural university classrooms. Journal on Excellence in College Teaching, 5(1), 21-30. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-to-pdf.php? article=56

83

Giordano, P. J., & Hammer, E. Y. (1999). In-class collaborative learning: Practical suggestions from the teaching trenches. Teaching of Psychology, 26, 42-44. Glanzer, M., & Cunitz, A. R. (1966). Two storage mechanisms in free recall. Journal of Verbal Learning and Verbal Behavior, 5, 531-560. Glaser, R., & Chi, M. T. H. (1988). Overview. In M. T. H. Chi, R. Glaser & M. Farr (Eds.), The nature of expertise (pp. xv-xxviii). Hillsdale, NJ: Erlbaum. Gloria, A. M., Rieckmann, T. R., & Rush, J. D. (2000). Issues and recommendations for teaching an ethnic/culture-based course. Teaching of Psychology, 27, 102-107. Goleman, D. (1995). Emotional intelligence: Why it can matter more than IQ. New York: Bantam. Goleman, D. (1998). Working with emotional intelligence. New York: Bantam. Graham, R. B. (1999). Unannounced quizzes raise test scores selectively for mid-range students. Teaching of Psychology, 26, 271-273. Graham, S. (1991). A review of attribution theory in achievement contexts. Educational Psychology Review, 3, 5-39. Gregory, J. (2002). Principles of experiential education. In P. Jarvis (Ed.), The theory and practice of teaching (pp. 94-107). London: Kogan Page. Grossman, R. W. (1994). Encouraging critical thinking using the case study method and cooperative learning techniques. Journal on Excellence in College Teaching, 5(1), 7-20. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-to-pdf.php? article=57 Grossman, R. (2002, November). Use of different kinds of case studies to enhance instruction. Abstract of paper presented at the 22nd Annual Lilly Conference on College Teaching, Miami, OH, November. Retrieved November 18, 2002, from http://www.units.muohio.edu/lillycon/contributedabstd-h.shtml#Grossman Guilford, J. P. (1950). Creativity. American Psychologist, 5, 444-454. Guilford, J. P. (1959). Three faces of intellect. American Psychologist, 14, 469-479. Gurin, P. (1999). Expert report of Patricia Gurin submitted to the Court in the cases of Gratz et al. v. Bollinger et al., Grutter et al. v. Bollinger et al. Retrieved August 28, 2002, from http://www.umich.edu/~urel/admissions/legal/expert/gurintoc.html Guskey, T., & Pigott, T. (1988). Research on group-based mastery learning programs: A meta-analysis. Journal of Educational Research, 81, 197-216. Hacker, D. J. (1998). Definitions and empirical foundations. In D. J. Hacker, J. Dunlosky & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 1-23). Mahwah, NJ: Erlbaum. Hackman, J. R., & Oldham, G. R. (1975). Development of the Job Diagnostic Survey. Journal of Applied Psychology, 60, 161-172. Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16, 250-279. Hackman, J. R., & Oldham, G. R. (1980). Work redesign. Reading, MA: Addison-Wesley. Hambleton, R. K., & Jones, R. W. (1993). Comparison of classical test theory and item response theory and their applications to test development. Educational Measurement: Issues and Practice, 12, 38-47. Handy, C. (1993). Understanding organizations (4th ed.). Harmondsworth: Penguin. Hartlep, K. L., & Forsyth, G. A. (2000). The effect of self-reference on learning and retention. Teaching of Psychology, 27, 269-271. Hartley, J. (1992). Sex bias, blind marking and assessing students. Psychology Teaching Review, 1, 66-75. Hattie, J., & Marsh, H. W. (1996). The relationship between research and teaching: A metaanalysis. Review of Educational Research, 66, 507-542.

84

Hawkins, A., Jolliffe, F., & Glickman, L. (1992). Teaching statistical concepts. London: Longman. Heckler, J. B., Fuqua, R. W., & Pennypacker, H. S. (1975). Errorless differentiation of academic responses by college students. Teaching of Psychology, 2, 103-107. Hembree, R. (1988). Correlates, causes, effects and treatment of test anxiety. Review of Educational Research, 58, 47-77. Hemenover, S. H., Caster, J. B., & Mizumoto, A. (1999). Combining the use of progressive writing techniques and popular movies in introductory psychology. Teaching of Psychology, 26, 196-198. Hendry, G. D., & King, R. C. (1994). On theory of learning and knowledge: Educational implications of advances in neuroscience. Science Education, 78, 223-253. Herman, J. L. (1997). Trauma and recovery: The aftermath of violence: From domestic abuse to political terror (rev. ed.). New York: Basic Books. Hersey, P., & Blanchard, K. H. (1977). Management of organizational behaviour: Utilizing human resources. London: Prentice Hall International. Herzberg, F. (1966). Work and the nature of man. Cleveland, OH: World. Hetrick, J. (1999). Starting where the students are. Research and Creative Activity, 12(1), 13. Retrieved August 29, 2002, from http://www.indiana.edu/~rcapub/v22n1/p13.html Hidi, S., & Harackiewicz, J. M. (2000). Motivating the academically unmotivated: A critical issue for the 21st century. Review of Educational Research, 70, 151-179. Hill, W. G., IV. (2000). Incorporating a cross-cultural perspective in the undergraduate psychology curriculum: An interview with David Matsumoto. Teaching of Psychology, 27, 71-75. Hinkle, S., Sherman, R. C., Mueller, D., Young, J. B., End, C., Campbell, J., et al. (2001, November). Advanced students teaching beginning students via the internet: Do the beginners like it; Do they learn anything? Paper presented at the 21st Annual Lilly Conference on College Teaching, Miami, OH. Retrieved August 29, 2002, from http://www.units.muohio.edu/lillycon/old/01conabstract.htm Hmelo-Silver, C. (2000). Knowledge recycling: Crisscrossing the landscape of educational psychology in a problem-based learning course for preservice educators. Journal on Excellence in College Teaching, 11(2), 41-56. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-to-pdf.php?article=217 Hogg, M. A. (1992). The social psychology of group cohesiveness. Hemel Hempstead: Harvester Wheatsheaf. Hogg, M. A., & Abrams, D. (1988). Social identifications: A social psychology of intergroup relations and group processes. London: Routledge. Holland, J. L. (1973). Making vocational choices: A theory of careers. Englewood Cliffs, NJ: Prentice Hall. Honey, P., & Mumford, A. (1988). Manual of learning styles. Maidenhead: Peter Honey. Hovland, C., Janis, I., & Kelley, H. (1953). Communication and persuasion. New Haven, CT: Yale University Press. Huber, M. T. (2002). Disciplinary styles in the scholarship of teaching: Reflections on The Carnegie Academy for the Scholarship of Teaching and Learning. In M. T. Huber & S. P. Morreale (Eds.), Disciplinary styles in the scholarship of teaching and learning: Exploring common ground (pp. 25-43). Washington, DC: American Association for Higher Education and the Carnegie Foundation for the Advancement of Teaching. Retrieved August 28, 2002, from http://www.aahe.org/pubs/Disciplinary_Styles_ Orientation.pdf

85

Hutchings, P., & Shulman, L. S. (1999). The scholarship of teaching: New elaborations, new developments. Change, 31(5), 10-15. Retrieved August 28, 2002, from http://www.carnegiefoundation.org/elibrary/docs/sotl1999.htm Hynd, C. (2001). Persuasion and its role in meeting educational goals. Theory into Practice, 40, 270-277. Idaszak, J. R., & Drasgow, F. (1987). A revision of the Job Diagnostic Survey: Elimination of a measurement artifact. Journal of Applied Psychology, 72, 69-74. Jacobs, P. A., & Newstead, S. E. (2000). The nature and development of student motivation. British Journal of Educational Psychology, 70, 243-254. Jacobs-Lawson, J. M., & Hershey, D. A. (2002). Concept maps as an assessment tool in psychology courses. Teaching of Psychology, 29, 25-29. Jagacinski, C. M., & Nicholls, J. G. (1990). Reducing effort to protect perceived ability: “They’d do it but I wouldn’t”. Journal of Educational Psychology, 82, 15-21. Janis, I. (1972). Victims of groupthink. Boston: Houghton Mifflin. Janis, I. (1982). Groupthink: Psychological studies of policy decisions and fiascos (2nd ed.). Boston: Houghton Mifflin. Jarvis, P. (2002). Practice-based and problem-based learning. In P. Jarvis (Ed.), The theory and practice of teaching (pp. 123-131). London: Kogan Page. Jensen, G. H. (1987). Learning styles. In J. A. Provost & S. Anchors (Eds.), Applications of the Myers-Briggs Type Indicator in higher education (pp. 181-206). Palo Alto, CA: Consulting Psychologists Press. Johnson, D. W., Johnson, R. T., & Smith, K. A. (1991). Active learning: Cooperation in the college classroom. Edina, MN: Interaction Book Company. Johnson, D. W., Maruyama, G., Johnson, R., Nelson, D., & Skon, L. (1981). The effects of cooperative, competitive, and individualistic goal structures on achievement: A metaanalysis. Psychological Bulletin, 89, 47-62. Johnson, E. G. (1985). An analysis of assessment procedures used in an introductory course in psychology. Assessment and Evaluation in Higher Education, 10, 63-70. Jones, A., Scanlon, E., Tosunoglu, C., Morris, E., Ross, S., Butcher, P., et al. (1999). Contexts for evaluating educational software. Interacting with Computers, 11, 499-516. Jones, L. V. (1988). Educational assessment as a promising area for psychometric research. Applied Measurement in Education, 1, 233-241. Jung, C. G. (1992). Psychological types (Vol. 6 of the Collected Works, R. F. C. Hull, Trans.). London: Routledge. (Original work published 1921) Just, M. A., & Carpenter, P. A. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99, 122-149. Karau, S. J., & Williams, K. D. (2001). Understanding individual motivation in groups: The collective effort model. In M. E. Turner (Ed.), Groups at work: Theory and research (pp. 113-141). Mahwah, NJ: Lawrence Erlbaum. Kay, E. J., Jensen-Osinski, B. H., Beidler, P. G., & Aronson, J. L. (1983). The graying of the college classroom. The Gerontologist, 23, 196-199. Keller, F. S. (1968). “Goodbye, Educator…” Journal of Applied Behavior Analysis, 1, 79-89. Keller, F. S. (1974). Ten years of personalized instruction. Teaching of Psychology, 1, 4-9. Keller, F. S. (1985). Lightning strikes twice. Teaching of Psychology, 12, 4-8. Kelley, H. H. (1950). The warm-cold variable in first impressions of persons. Journal of Personality, 18, 431-439. Kellum, K. K., Carr, J. E., & Dozier, C. L. (2001). Response-card instruction and student learning in a college classroom. Teaching of Psychology, 28, 101-104. Khan, S. R. (1999). Teaching an undergraduate course on the psychology of racism. Teaching of Psychology, 26, 28-33.

86

King, P. M., & Shuford, B. C. (1996). A multicultural view is a more cognitively complex view. American Behavioral Scientist, 40, 153-164. Knowles, M. (1984a). Andragogy in action. London: McGraw-Hill. Knowles, M. (1984b). The adult learner: A neglected species (3rd ed.). Houston, TX: Gulf. Kolb, D. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall. Kolb, D., Rubin, I., & McIntyre, J. (1971). Organizational psychology: An experiential approach. Hemel Hempstead: Prentice Hall. Kornbrot, D. (1987). Science and Psychology degree performance. Bulletin of the British Psychological Society, 40, 409-417. Kowalski, R. M. (2000). Including gender, race, and ethnicity in psychology content courses. Teaching of Psychology, 27, 18-24. Kreiner, D. S. (1997). Guided notes and interactive methods for teaching with videotapes. Teaching of Psychology, 24, 183-185. Kremer, J. (1997). Empowerment in the learning process: The case of student discussion groups. Psychology Teaching Review, 6, 77-84. Kulik, C.-L. C., Kulik, J., & Bangert-Downs, R. (1990). Effectiveness of mastery learning programs: A meta-analysis. Review of Educational Research, 60, 265-306. Kulik, C.-L. C., Kulik, J., & Cohen, P. A. (1980). Instructional technology and college teaching. Teaching of Psychology, 7, 199-205. Kulik, J., Kulik, C.-L. C., & Cohen, P. A. (1979). A meta-analysis of outcome studies of Keller’s personalized system of instruction. American Psychologist, 34, 307-318. Labouvie-Vief, G. (1980). Beyond formal operations: Uses and limits of pure logic in life-span development. Human Development, 23, 141-161. Laming, D. (1990). The reliability of a certain university examination compared with the precision of absolute judgements. Quarterly Journal of Experimental Psychology, 42A, 239-254. Lanzon, P. M. (2002, November). Application of Slavin’s Student Team Achievement Division model to the community college classroom. Paper presented at the 21st Annual Lilly Conference on College Teaching, Miami, OH. Retrieved August 29, 2002, from http://www.units.muohio.edu/lillycon/contributedabstj-r.shtml#Lanzon Larrington, C., & Lindsay, R. (2002). Equal among firsts: Reviewing quality in Psychology. Psychology Learning and Teaching, 2, 6-11. Latané, B., Williams, K., & Harkins, S. (1979). Many hands make light the work: The causes and consequences of social loafing. Journal of Personality and Social Psychology, 37, 822-832. Laurillard, D. (1993). Rethinking university teaching: A framework for the effective use of educational technology. London: Routledge. Lave, J. (1988). Cognition in practice: Mind, mathematics, and culture in everyday life. Cambridge: Cambridge University Press. Leavitt, H. T. (1951). Some effects of certain communicative patterns on group performance. Journal of Abnormal Psychology, 36, 38-50. Leonard, J. A., Mitchell, K. L., Meyers, S. A., & Love, J. D. (2002). Using case studies in introductory psychology. Teaching of Psychology, 29, 142-144. Levin, M. E., & Levin, J. R. (1990). Scientific mnemonomies: Methods for maximizing more than memory. American Educational Research Journal, 27, 301-321. Lewin, K., Lippit, R., & White, R. K. (1939). Patterns of aggressive behavior in experimentally created ‘social climates’. Journal of Social Psychology, 10, 271-299.

87

Light, L. C., McKeachie, W. J., & Lin, Y.-G. (2002). Self-scoring: A self-monitoring procedure. In R. A. Griggs (Ed.), Handbook for teaching introductory psychology: Vol. 3. With an emphasis on assessment (pp. 130-131). Mahwah, NJ: Erlbaum. Lockhart, R. S., & Craik, F. I. M. (1990). Levels of processing: A retrospective commentary on a framework for memory research. Canadian Journal of Psychology, 44, 87-112. Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37, 2098-2109. Lord, F. M. (1980). Applications of item response theory to practical testing problems. Hillsdale, NJ: Erlbaum. Lord, F. M., & Novick, M. R. (Eds.). (1968). Statistical theories of mental test scores. Reading, MA: Addison-Wesley. Macaranas, N. (1982). Fostering, experiencing and developing creativity – as a method of instruction in psychology. Creative Child and Adult Quarterly, 7, 15-29. Markee, N. (1997). Managing curricular innovation. Cambridge: Cambridge University Press. Marton, F., Dall’Alba, G., & Beaty, E. (1993). Conceptions of learning. International Journal of Educational Research, 19, 277-300. Marton, F., & Saljo, R. (1976). On qualitative differences in learning. I. Outcome and process. British Journal of Educational Psychology, 46, 4-11. Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 1, 370-396. Maslow, A. H. (1970). Motivation and personality (2nd ed.). New York: Harper and Row. Matlin, M. (1991). The social cognition approach to stereotypes and its application to teaching. Journal on Excellence in College Teaching, 2, 9-24. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-to-pdf.php?article=103 Mayer, R. E. (1979). Twenty years of research on advance organizers. Instructional Science, 8, 133-169. McDade, S. A. (1995). Case study pedagogy to advance critical thinking. Teaching Psychology, 22, 9-10. McGuinness, C. (1999). Research-led teaching: Meanings of “research-led teaching” within the Queen’s context. Unpublished paper, Queens University, Belfast. Retrieved October 23, 2002, from www.qub.ac.uk/geosci/documents/people/whalley/misc/ teaching/resled.html McIlroy, D., Bunting, B., & Adamson, G. (2000). An evaluation of the factor structure and predictive utility of a test anxiety scale with reference to students’ past performance and personality indices. British Journal of Educational Psychology, 70, 17-32. McKeachie, W. J., Lin, Y. G., Moffett, M. M., & Daugherty, M. (1978). Effective teaching: Facilitative versus directive style. Teaching of Psychology, 5, 193-194. McKeough, A., Lupart, J., & Marini, A. (Eds.). (1995). Teaching for transfer: Fostering generalization in learning. Mahwah, NJ: Erlbaum. McLaughlin, M. W., & Mitra, D. (2001). Theory-based change and change-based theory: Going deeper, going broader. Unpublished manuscript, University of Stanford. McLeod, P., Lobel, S. A., & Cox, T. H. (1996). Ethnic diversity and creativity in small groups. Small Group Research, 27, 827-847. McMillan, J. H. (1987). Enhancing college students’ critical thinking. Research in Higher Education, 26, 3-30. Melton, A. W. (1970). The situation with respect to the spacing of repetitions and memory. Journal of Verbal Learning and Verbal Behavior, 9, 596-606. Mentzer, T. L. (1982). Response biases in multiple-choice test item files. Educational and Psychological Measurement, 42, 437-448.

88

Meyers, S. A. (1997). Increasing student participation and productivity in small-group activities for psychology classes. Teaching of Psychology, 24, 105-115. Michaelsen, L. K., Fink, L. D., & Knight, A. (1997). Designing effective group activities: Lessons for classroom teaching and faculty development. In D. Dezure (Ed.), To improve the academy (Vol. 16, pp. 373-398). Fort Collins, CO: Professional and Organizational Development Network in Higher Education. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81-97. Miserandino, M. (1996). Teaching a personality course in Vienna. Teaching of Psychology, 23, 240-241. Montgomery, S. M., & Groat, L. N. (1998). Student learning styles and their implications for teaching (Occasional Paper no. 10). Ann Arbor: Centre for Research on Learning and Teaching, University of Michigan. Retrieved August 29, 2002, from http://www.crlt. umich.edu/occ10.html Morales, E. E. (2000). A contextual understanding of the process of educational resilience: High achieving Dominican American students and the “resilience cycle”. Innovative Higher Education, 25, 7-22. Morris, E. J. (1997). An investigation of students’ conceptions and procedural skills in the statistical topic correlation (CITE Report no. 230). Walton Hall: Centre for Information Technology in Education, Institute of Educational Technology, Open University. Morris, E. J. (1998, April). The development of a computer-assisted learning program designed to address students’ misconceptions in correlation. Paper presented at CiP98: Computers in Psychology Conference, York. Retrieved August 29, 2002, from http://ltsnpsy.york.ac.uk/LTSNCiPAbstracts/cip98.htm Morris, E. J. (1999). Another look at psychology students’ understanding of correlation (CITE Report no. 246). Walton Hall: Centre for Information Technology in Education, Institute of Educational Technology, Open University. Morris, E. J. (2001). The design and evaluation of ‘Link’: A computer-based learning system for correlation. British Journal of Educational Technology, 32, 39-52. Morris, E. J., & Scanlon, E. (2000, March). Active learning of statistics: A case study. Association for Learning Technology Journal, 8(1), 80-91. Morris, E. J., Scanlon, E., & Joiner, R. (2000). Evaluating multimedia resources for teaching statistics to psychology undergraduates. Abstract of paper presented at CiP2000: Computers in Psychology 2000 Conference, York. Retrieved August 29, 2002, from http://cti-psy.york.ac.uk/cip2000-online/papers/paper1.htm Murphy, J. J. (2000). Applying “what works” in psychotherapy to university teaching. Paper presented at the 20th Annual Lilly Conference on College Teaching, Miami, OH. Retrieved August 29, 2002, from http://www.units.muohio.edu/lillycon/old/ 00conabstract.htm#ap18 Murphy, K. R., & Davidshofer, C. O. (2001). Psychological testing: Principles and applications (5th ed.). Upper Saddle River, NJ: Prentice Hall. Murphy, P. K. (2001). Teaching as persuasion: A new metaphor for a new decade. Theory into Practice, 40, 224-227. Musch, J., & Broder, A. (1999). Test anxiety versus academic skills: A comparison of two alternative models for predicting performance in a statistics exam. British Journal of Educational Psychology, 69, 105-116. Myers, D. G., & Lamm, H. (1975). The polarizing effect of group discussion. American Scientist, 63, 297-303.

89

Myers, I. B. (1993). Introduction to Type (5th ed.). Palo Alto, CA: Consulting Psychologists Press. Myers, I. B., & McCaulley, M. H. (1985). Manual: A guide to the development and use of the Myers-Briggs Type Indicator. Palo Alto, CA: Consulting Psychologists Press. Newcomb, T. L. (1943). Personality and social change: Attitude formation in a student community. New York: Dryden Press. Newcomb, T. L., Koenig, K. E., Flacks, R., & Warwick, D. P. (1967). Persistence and change: Bennington College and its students after 25 years. New York: John Wiley. Newstead, S. E. (1990). Teaching transferable skills. In F. N. Watts (Ed.), The undergraduate curriculum in psychology (pp. 17-23) (Group of Teachers of Psychology Occasional Paper no. 9). Leicester: British Psychological Society. Newstead, S. E. (1992a). A study of two “quick-and-easy” methods of assessing individual differences in student learning. British Journal of Educational Psychology, 62, 299-312. Newstead, S. E. (1992b). The use of examinations in the assessment of psychology students. Psychology Teaching Review, 1, 22-33. Newstead, S. E. (1996). The psychology of student assessment. The Psychologist: Bulletin of the British Psychological Society, 9, 543-547. Newstead, S. E. (2002). Examining the examiners: Why are we so bad at assessing students? Psychology Learning and Teaching, 2, 70-75. Newstead, S. E., & Dennis, I. (1990). Blind marking and sex bias in student assessment. Assessment and Evaluation in Higher Education, 15, 132-139. Newstead, S. E., & Dennis, I. (1994). Examiners examined: The reliability of exam marking in psychology. The Psychologist: Bulletin of the British Psychological Society, 7, 216-219. Newstead, S. E., & Findlay, K. (1997). Some problems with using examination performance as a measure of teaching ability. Psychology Teaching Review, 6, 14-21. Newstead, S. E., Franklyn-Stokes, B. A., & Armstead, P. (1996). Individual differences in student cheating. Journal of Educational Psychology, 88, 229-241. Norman, G. R., & Schmidt, H. G. (1992). The psychological basis of problem-based learning: A review of the evidence. Academic Medicine, 67, 557-565. Norton, L. (2001a). Encouraging students to take a deep approach to learning: Tutor pack. Retrieved October 24, 2002, from http://ltsnpsy.york.ac.uk/LTSNPsych/Specialist/ Norton/Introduction.htm Norton, L. (2001b). Researching your teaching. Psychology Learning and Teaching, 1, 21-27. Norton, L. S., & Crowley, C. M. (1995). Can students be helped to learn how to learn? An evaluation of an approaches to learning programme for first year degree students. Higher Education, 29, 307-328. Norton, L. S., & Dickins, T. E. (1995). Do approaches to learning courses improve students’ learning strategies? In G. Gibbs (Ed.), Improving student learning through assessment and evaluation (pp. 455-469). Oxford: Oxford Centre for Staff Development, Oxford Brookes University. Norton, L. S., Scantlebury, E., & Dickins, T. E. (1999). Helping undergraduates to become more effective learners: An evaluation of two learning interventions. Innovations in Education and Training International, 3, 273-284. Norton, L. S., Tilley, A. J., Newstead, S. E., & Franklyn-Stokes, A. (2001). The pressures of assessment in undergraduate courses and their effect on student behaviours. Assessment and Evaluation in Higher Education, 26, 268-284. Nummedal, S. G., Benson, J. B., & Chew, S. L. (2002). Disciplinary styles in the scholarship of teaching and learning: A view from psychology. In M. T. Huber & S. P. Morreale (Eds.), Disciplinary styles in the scholarship of teaching and learning: Exploring common ground (pp. 163-179). Washington, DC: The American Association for Higher Education and the Carnegie Foundation for the Advancement of Teaching. 90

O’Halloran, M. S., & O’Halloran, T. (2001). Secondary traumatic stress in the classroom: Ameliorating stress in graduate students. Teaching of Psychology, 28, 92-96. Paivio, A. (1971). Imagery and verbal processes. New York: Holt, Rinehart and Winston. Pajares, F. (1996). Self-efficacy beliefs in academic settings. Review of Educational Research, 66, 543-578. Pask, G. (1976). Styles and strategies of learning. British Journal of Educational Psychology, 46, 128-148. Patrick, B. C., Hisley, J., & Kempler, T. (2000). “What’s everybody so excited about?”: The effects of educator enthusiasm on student intrinsic motivation and vitality. Journal of Experimental Education, 68, 217-236. Perkins, D. N., & Salomon, G. (1988). Teaching for transfer. Educational Leadership, 46, 2-32. Perkins, D. N., & Salomon, G. (1989). Are cognitive skills context-bound? Educational Researcher, 18, 16-25. Perkins, D. V. (1991). A case-study assignment to teach theoretical perspectives in abnormal psychology. Teaching of Psychology, 18, 97-99. Perkins, D. V., & Saris, R. N. (2001). A “jigsaw classroom” technique for undergraduate statistics courses. Teaching of Psychology, 28, 111-113. Perry, N. W., Huss, M. T., McAuliff, B. D., & Galas, J. M. (1996). An active-learning approach to teaching the undergraduate psychology and law course. Teaching of Psychology, 23, 76-81. Perry, W. G., Jr. (1970). Forms of intellectual and ethical development in the college years: A scheme. New York: Holt, Rinehart and Winston. Pettigrew, T. F. (1991). Normative theory in intergroup relations: Explaining both harmony and conflict. Psychology and Developing Societies, 3, 3-16. Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion: Central and peripheral routes to attitude change. New York: Springer-Verlag. Phye, G. D. (1992). Strategic transfer: A tool for academic problem solving. Educational Psychology Review, 4, 393-421. Piaget, J. (1972). Intellectual development from adolescence to adulthood. Human Development, 15, 1-12. Piaget, J. (1973). To understand is to invent. New York: Grossman. Pike, C. (2002) Exploring the conceptual space of LEGO: Teaching and learning the psychology of creativity. Psychology Learning and Teaching, 2, 87-94 Pintrich, P. R. (1990). Implications of psychological research on student learning and teaching for educator education. In W. R. Houston (Ed.), Handbook of research on educator education (pp. 826-857). New York: Macmillan. Podeschi, R. (1990). Teaching their own: Minority challenges to mainstream institutions. New Directions for Adult and Continuing Education, 48, 55-65. Polanyi, M. (1958). Personal knowledge: Towards a post-critical philosophy. London: Routledge and Kegan Paul. Polanyi, M. (1967). The tacit dimension. London: Routledge and Kegan Paul. Prieto, L. R., & Altmaier, E. M. (1994). The relationship of prior training and previous teaching experience to self-efficacy among graduate teaching assistants. Research in Higher Education, 35, 481-497. Prieto, L. R., & Meyers, S. A. (1999). Effects of training and supervision on the self-efficacy of psychology graduate teaching assistants. Teaching of Psychology, 26, 264-266. Provost, J. A., & Anchors, S. (Eds.). (1987). Applications of the Myers-Briggs Type Indicator in higher education. Palo Alto, CA: Consulting Psychologists Press.

91

Pychyl, T. A., Clarke, D., & Abarbanel, T. (1999). Computer-mediated group projects: Facilitating collaborative learning with the World Wide Web. Teaching of Psychology, 26, 138-141. Qin, Z., Johnson, D. W., & Johnson, R. T. (1995). Cooperative versus competitive efforts and problem solving. Review of Educational Research, 65, 129-143. Radford, J. (1992). The undergraduate curriculum in psychology. The Psychologist: Bulletin of the British Psychological Society, 5, 273-276. Ramsden, P. (1985). Student learning research: Retrospect and prospect. Higher Education Research and Development, 5, 51-70. Rayner, S., & Riding, R. (1997). Towards a categorisation of cognitive styles and learning styles. Educational Psychology, 17, 5-27. Reboy, L. M., & Semb, G. B. (1991). PSI and critical thinking: Compatibility or irreconcilable differences? Teaching of Psychology, 18, 212-214. Reeve, J. (2002). Self-determination theory applied to educational settings. In E. L. Deci & R. M. Ryan (Eds.), Handbook of self-determination research (pp. 193-203). Rochester, NY: University of Rochester Press. Reisberg, D. (2001). Cognition: Exploring the science of the mind (2nd ed.). London: Norton. Renkl, A., Atkinson, R. K., & Maier, U. H. (2000). From studying examples to solving problems: Fading worked-out solution steps helps learning. In L. R. Gleitman & A. K. Joshi (Eds.), Proceedings of the 22nd Annual Conference of the Cognitive Science Society (pp. 393-398). Mahwah, NJ: Erlbaum. Richardson, J. T. E. (1992a). A critical evaluation of the short form of the Approaches to Studying Inventory. Psychology Teaching Review, 1, 34-45. Richardson, J. T. E. (1992b). Cognitive psychology and student learning. Psychology Teaching Review, 1, 2-9. Robertson, I. T., Smith, M., & Cooper, D. (1992). Motivation: Strategies, theory and practice. London: Institute of Personnel Management. Rogers, C. R. (1969). Freedom to learn (1st ed.). Columbus, OH: Merrill. Rogers, C. R., & Freiberg, H. J. (1994). Freedom to learn (3rd ed.). Columbus, OH: Merrill/Macmillan. Rohrkemper, M. M. (1984). How teaching for understanding changes the rules in the classroom. Educational Leadership, 51, 19-21. Rosenthal, R., & Jacobson, L. (1992). Pygmalion in the classroom: Teacher expectation and pupils’ intellectual development. New York: Irvington. Ross, L., Lepper, M. R., & Hubbard, M. (1975). Perseverance in self-perception and social perception: Biased attributional processes in the debriefing paradigm. Journal of Personality and Social Psychology, 32, 880-892. Rotter, J. (1954). Social learning and clinical psychology. Englewood Cliffs, NJ: Prentice Hall. Rumelhart, D. E., McClelland, J. L. and the PDP Research Group (Eds.). (1986). Parallel distributed processing: Explorations in the microstructure of cognition (Vols 1 and 2). Cambridge, MA: MIT Press. Ruscio, J. (2001). Administering quizzes at random to increase students’ reading. Teaching of Psychology, 28, 204-206. Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68-78. Rysavy, S. D. M., & Sales, G. C. (1991). Cooperative learning in computer-based instruction. Educational Technology Research and Development, 39, 70-79. Saljo, R. (1979). Learning about learning. Higher Education, 8, 443-451. Savery, J. R., & Duffy, T. A. (1995). Problem-based learning: An instructional model and its constructivist framework. Educational Technology, 35, 31-38.

92

Schacter, D. L., Norman, K. A., & Koutstaal, W. (1998). The cognitive neuroscience of constructive memory. Annual Review of Psychology, 49, 289-318. Schank, R. C., & Abelson, R. P. (1977). Scripts, plans, goals, and understanding: An inquiry into human knowledge structures. Hillsdale, NJ: Erlbaum. Scheurman, G. (1997). Using principles of constructivism to promote reflective judgment: A model lesson. Journal on Excellence in College Teaching, 8(2), 63-86. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-to-pdf.php?article=143 Schunk, D. H. (1991). Self-efficacy and academic motivation. Educational Psychologist, 26, 207-231. Scialfa, C., Legare, C., Wenger, L., & Dingley, L. (2001). Difficulty and discriminability of introductory psychology test items. Teaching of Psychology, 28, 11-15. Seegmiller, B. R. (1995). Teaching an undergraduate course on intrafamily abuse across the life span. Teaching of Psychology, 22, 108-112. Seligman, M. E. P. (1999). Teaching positive psychology. APA Monitor, 30, 42. Shatz, M. A. (2000). Teaching psychology in Hong Kong: Pedagogical challenges, instructional solutions, and lessons learned. Teaching of Psychology, 27, 140-141. Shaughnessy, J. M. (1992). Research in probability and statistics: Reflections and directions. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning: A project of the National Council of Educators of Mathematics (pp. 465-494). New York: Macmillan. Sheldon, J. P. (1999). A secondary agenda in classroom activities: Having students confront their biases and assumptions. Teaching of Psychology, 26, 209-211. Sherman, R. C. (1998). Using the World Wide Web to teach applications of social psychology to everyday life. Teaching of Psychology, 25, 212-216. Shostrom, E. L. (1963). Manual for the Personal Orientation Inventory. San Diego, CA: Educational and Industrial Testing Service. Shostrom, E. L. (1964). An inventory for the measurement of self-actualization. Educational and Psychological Measurement, 24, 207-218. Sieber, J., O’Neil, H. F., & Tobias, S. (1977). Anxiety, learning and instruction. Hillsdale, NJ: Erlbaum. Singley, M. K., & Anderson, J. R. (1989). The transfer of cognitive skill. Cambridge, MA: Harvard University Press. Skinner, B. F. (1953). Science and human behavior. New York: Macmillan. Skinner, B. F. (1954). The science of learning and the art of teaching. Harvard Educational Review, 24, 86-97. Skinner, B. F. (1968). The technology of teaching. New York: Appleton-Century-Crofts. Slavin, R. E. (1987). Mastery learning reconsidered. Review of Educational Research, 57, 175-214. Slavin, R. E. (1995). Cooperative learning: Theory, research, and practice (2nd ed.). Boston: Allyn and Bacon. Slowey, M. (Ed.). (1995). Implementing change from within universities and colleges: Ten personal accounts. London: Kogan Page. Smith, E. W. L., & McIntosh, W. D. (2001). Offering a course in humanistic and transpersonal psychology in a traditional psychology department. Teaching of Psychology, 28, 64-66. Smith, P. K. (1990). The distribution of psychology degree classes in the UK. The Psychologist: Bulletin of the British Psychological Society, 3, 147-152. Smith, R. J., Arnkoff, D. B., & Wright, T. L. (1990). Test anxiety and academic competence: A comparison of alternative models. Journal of Counseling Psychology, 37, 313-321. Smith, S. M., & Woody, P. C. (2000). Interactive effect of multimedia instruction and learning styles. Teaching of Psychology, 17, 220-223.

93

Snyder, M. (1974). Self monitoring of expressive behavior. Journal of Personality and Social Psychology, 30, 526-537. Snyder, M., & Kendzierski, D. (1982). Choosing social situation: Investigating the origin of correspondence between attitudes and behavior. Journal of Personality, 50, 280-295. Snyder, M., & Swann, W., Jr. (1976). When actions reflect attitudes: The politics of impression management. Journal of Personality and Social Psychology, 34, 1034-1042. Solomon, P. R. (1979). The two-point system: A method for encouraging students to read assigned material before class. Teaching of Psychology, 6, 77-80. Sommer, R., & Sommer, B. A. (1991). Teaching psychology in Estonia, USSR. Teaching of Psychology, 18, 105-107. Spielberger, C. (1966). Anxiety and behavior. New York: Academic Press. Stalder, D. R. (2001). The use of discrimination indexes in constructing course exams: A question of assumptions. Teaching of Psychology, 28, 278-280. Stamm, B. H. (Ed.) (1995). Secondary traumatic stress: Self-care issues for clinicians, researchers, and educators. Lutherville, MD: Sidran. Steele, C. M. (1997). A threat in the air: How stereotypes shape intellectual identity and performance. American Psychologist, 52, 613-619. Steele, C. M. (1998). Stereotyping and its threat are real. American Psychologist, 53, 680681. Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69, 797-811. Sternberg, R. J. (1985). Beyond IQ. New York: Cambridge University Press. Sternberg, R. J. (1988). The nature of creativity. New York: Cambridge University Press. Sternberg, R. J. (1996). Successful intelligence: How practical and creative intelligence determine success in life. New York: Simon and Schuster. Sternberg, R. J. (1999). A propulsion model of types of creative contributions. Review of General Psychology, 3, 83-100. Sternberg, R. J., Ferrari, M., Clinkenbeard, P., & Grigorenko, E. L. (1996). Identification, instruction and assessment of gifted children: A construct validation of a triarchic model. Gifted Child Quarterly, 40, 129-137. Sternberg, R. J., Grigorenko, E. L., Ferrari, M., & Clinkenbeard, P. (1999). A triarchic analysis of an aptitude-treatment interaction. European Journal of Psychological Assessment, 15, 3-13. Sternberg, R. J., & Lubart, T. I. (1995). Defying the crowd: Cultivating creativity in a culture of conformity. New York: Free Press. Sternberg, R. J., Torff, B., & Grigorenko, E. L. (1998). Teaching triarchically improves school achievement. Journal of Educational Psychology, 90, 374-384. Stirling, J. (1996). The use of multiple choice tests in the teaching and assessment of undergraduate psychology degree courses. Psychology Teaching Review, 5, 83-89. Symons, C. S., & Johnson, B. T. (1997). The self-reference effect in memory: A metaanalysis. Psychological Bulletin, 121, 371-394. Thomason, N., Cumming, G., & Zangari, M. (1994). Understanding central concepts of statistics and experimental design in the social sciences. In K. Beattie, C. McNaught & S. Wills (Eds.), Interactive multimedia in university education: Designing for change in teaching and learning (pp. 59-81). Amsterdam: Elsevier Science. Thompson, T., Davidson, J. A., & Barber, J. G. (1995). Self-worth protection in achievement motivation: Performance effects and attributional behavior. Journal of Educational Psychology, 87, 598-610. Thorndike, E. L. (1906). The principles of teaching, based on psychology. New York: Seiler.

94

Thorndike, E. L. (1932). The fundamentals of learning. New York: Educators College Press. Thorne, B. M. (2000). Extra credit exercise: A painless pop quiz. Teaching of Psychology, 27, 204-205. Tomlinson, P. (1992). Psychology and education: What went wrong – or did it? The Psychologist: Bulletin of the British Psychological Society, 5, 104-116. Tuckman, B. W. (1965). Development sequences in small groups. Psychological Bulletin, 63, 384-399. Tuckman, B. W. (1996a). Strategies for enhancing teaching and learning in an undergraduate course. Journal on Excellence in College Teaching, 7(3), 111-128. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-to-pdf.php?article=125 Tuckman, B. W. (1996b). The relative effectiveness of incentive motivation and prescribed learning strategy in improving college students’ course performance. Journal of Experimental Education, 64, 197-210. Tuckman, B. W., & Jensen, N. (1977). Stages of small group development revisited. Group and Organizational Studies, 2, 419-427. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124-1131. Tynjälä, P. (1999). Towards expert knowledge? A comparison between a constructivist and a traditional learning environment in the university. International Journal of Educational Research, 31, 357-442. Underwood, G. (1974). Moray vs. the rest: The effect of extended shadowing practice. Quarterly Journal of Experimental Psychology, 26, 368-372. VanGundy, A. B. (1987). Creative problem solving. New York: Quorum. VanVoorhis, C. R. W. (2002). Stat jingles: To sing or not to sing. Teaching of Psychology, 29, 249-250. Vernon, D. T. A., & Blake, R. L. (1993). Does problem-based learning work? A meta-analysis of evaluative research. Academic Medicine, 68, 550-563. Vroom, V. (1964). Work and motivation. New York: Wiley. Vroom, V. (1974). A new look at managerial decision-making. Organizational Behaviour, 5, 66-68. Vygotsky, L. S. (1962). Thought and language. Cambridge, MA: MIT Press. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press. Waehler, C. A., Kopera-Frye, K., Wiscott, R., & Yahney, E. O. (1999). Implementing an instructional model to enhance student responsibility in college classrooms. Journal on Excellence in College Teaching, 10(1), 47-62. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-to-pdf.php?article=185 Wang, M. C., Haertel, G. D., & Walberg, H. J. (1993). Toward a knowledge base for school learning. Review of Educational Research, 63, 249-294. Wang, M. C., Haertel, G. D., & Walberg, H. J. (1994). Educational resilience in inner cities. In M. C. Wang & E. W. Gordon (Eds.), Educational resilience in inner-city America: Challenges and prospects (pp. 45-72). Hillsdale, NJ: Erlbaum. Ware, R. (2001, November). Application of Jungian Type theory to teaching. Paper presented at the 21st Annual Lilly Conference on College Teaching, Miami, OH. Retrieved August 29, 2002, from http://www.units.muohio.edu/lillycon/old/01conabstract.htm Waterman, A. S. (1981). Individualism and interdependence. American Psychologist, 36, 762773. Watters, B. L. (1996). Teaching peace through structured controversy. Journal on Excellence in College Teaching, 7(1), 107-125. Retrieved August 29, 2002, from http://ject.lib. muohio.edu/articles/pdf-to-pdf.php?article=123

95

Watts, F. N. (1990). Comment. In F. N. Watts (Ed.), The undergraduate curriculum in psychology (pp. 35-36) (Group of Teachers of Psychology Occasional Paper no. 9). Leicester: British Psychological Society. Weiner, B. (1992). Human motivation: Metaphors, theories, and research. Newbury Park, CA: Sage. Weiner, B. (1994). Integrating social and personal theories of achievement striving. Review of Educational Research, 64, 557-573. Wertheimer, M. (1982). Productive thinking (enlarged ed.). Chicago: University of Chicago Press. Wheeler, E. A., Ayers, J. F., Fracasso, M. P., Galupo, M. P., & Rabin, J. S. (1999). Approaches to modeling diversity in the college classroom: Challenges and strategies. Journal on Excellence in College Teaching, 10(2), 79-93. Retrieved August 29, 2002, from http://ject.lib.muohio.edu/articles/pdf-to-pdf.php?article=194 Williams, G. C., Saizow, R. B., & Ryan, R. M. (1999). The importance of self-determination theory for medical education. Academic Medicine, 74, 992-995. Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker, J. Dunlosky & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277-304). Mahwah, NJ: Erlbaum. Witkin, H. (1962). Psychological differentiation: Studies of development. New York: Wiley. Witte, R. H. (1998). Use of an interactive case study to examine school learning problems. Teaching of Psychology, 25, 224-226. Wolfe, C. R., Crider, L., Mayer, L., McBride, M., & Sherman, R. (1998). Toward a Miami University model for internet intensive higher education. Journal on Excellence in College Teaching, 9(1), 29-51. Retrieved August 29, 2002, from http://ject.lib.muohio. edu/articles/pdf-to-pdf.php?article=148 Wolfe, R., & Johnson, S. (1995). Personality as a predictor of college performance. Educational and Psychological Measurement, 55, 177-185. Wood, W., & Kallgren, C. A. (1988). Communicator attributes and persuasion: Recipients’ access to attitude-relevant information in memory. Personality and Social Psychology Bulletin, 14, 172-182. Yerkes, R. M., & Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habitformation. Journal of Comparative Neurology and Psychology, 18, 459-482. Zeidner, M. (1991). Statistics and mathematics anxiety in social science students: Some interesting parallels. British Journal of Educational Psychology, 61, 319-328. Zeidner, M. (1998). Test anxiety: The state of the art. London: Plenum Press.

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