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into modern computer science teaching practice. In this paper we examine the application of the threshold concept theory to the whole of our field of education, ...
2013 Learning and Teaching in Computing and Engineering

Computer Science Education: the First Threshold Concept Nickolas J. G. Falkner, Rebecca Vivian and Katrina Falkner School of Computer Science The University of Adelaide Adelaide, South Australia, 5005 Email: {nickolas.falkner,rebecca.vivian,katrina.falkner}@adelaide.edu.au other group of learners. In the case of teachers, they must be ready to teach and should have a vision of a particular type of learning, an understanding of how to achieve this, the motivation to undertake the work required to achieve this new approach and then, finally, have the opportunity to put the new approach into practice [4]. To quote Shulman and Shulman [4], “[The teacher] is disposed to think of teaching as a process other than telling, and of learning as a process other than repeating or restating.” The final aspect that binds together the transformation required in pursuit of a new understanding of learning and teaching is the requirement to be capable of reflecting upon the process. If we revisit Terence’s quote, then nothing human is foreign, providing that we are willing to put considerable effort in thinking about how we can integrate new approaches into our current practice. Where the motivation does not exist to invest this effort, innovation will not be adopted, new techniques will not spread and learning (about learning) will stop [3]. There are many obstacles to adopting a new teaching practice, from the relatively new focus on teaching as scholarship, to any impediments to the model above: if there is insufficient vision, little understanding, low motivation or no opportunity to practise, then it is unsurprising that reflecting on the experience will result in an overwhelmingly negative impression. Rather than address structural or leadership issues, such as the influence of heads of faculty on pedagogical direction or availability of teaching resources, this paper will address the issues that can prevent individuals from perceiving that a key concept in learning and teaching is worthwhile or that may limit the extent to which it can be adopted. We will identify certain concepts, including that of the value to teachers of Computer Science Educational Research (CSER) itself, as being challenging to accept but transformative once incorporated. First, we will introduce the terminology of threshold concepts to explain a set of concepts that provide an unusual level of challenge to learners, including a review of the existing work in educational research that appears to remain challenging to the wider CS community. We will then discuss our investigation of the research literature, where we track those educational research ideas that, while challenging, have been adopted more widely. This leads to our modelling of the information sources for practising faculty in Computer Science, to explain how the competition between industry

Abstract—When presented with results and evidence that clearly show how teaching and learning can be improved, it is not uncommon for such ideas to be rejected because of personal experience, inter-disciplinary suspicion or because the information seems to completely counter all previously accepted wisdom. Such behaviour in students could be classified as a reaction to alien and counter-intuitive knowledge, as described in the works of Meyer and Land on threshold concepts. Since the threshold concept is, itself, a product of educational research, we would expect to have difficulty in explaining this concept to our colleagues. This is one possible explanation for the relatively slow penetration of computer science specific educational theory into modern computer science teaching practice. In this paper we examine the application of the threshold concept theory to the whole of our field of education, using the literature to find examples of how troublesome knowledge does, or does not, spread throughout the academic community. We track the adoption and display of knowledge of key concepts in Computer Science educational research, in order to identify common patterns in adoption and, by providing models to explain the flow of information across our discipline, provide an early indication of the role that threshold concepts (as a barrier to understanding) are playing in the community.

I. I NTRODUCTION “Homo sum, humani a me nihil alienum puto (I am a [human], nothing human is foreign to me)” [1] wrote Terence in 163BC but, while a majestic sentiment, we are constantly confronted by how many foreign ideas and concepts there are in our lives. One of the more familiar ideas is that we can somehow divide the world into teachers and learners, as if the two are categorically separate groups and that there is some immutable and innate set of characteristics that defines one as a teacher, replete with the sufficiency of knowledge required for the successful delivery of the discipline. This supposition is obviously unsupportable when we regard the developments in the discipline of teaching over time. Teaching is no longer telling [2] and a successful teacher must be able to learn about teaching, from their own experiences as well as the major influence of other people. Innovation in learning and teaching requires us to consider teachers as being able to learn, and we have to consider how we then present new, challenging and innovative ideas in a way that encourages learning [3]. When we investigate how we motivate teachers as learners, it is not enough to present peers and colleagues with a set of new materials or approaches and expect overnight acceptance; we must approach the teaching community as we would any 978-0-7695-4960-6/13 $26.00 © 2013 IEEE DOI 10.1109/LaTiCE.2013.32

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and academic information sources can explain why certain practices have been adopted, yet the supporting theory has not. Finally, we discuss the role of messengers and their importance in bringing new and innovative practices to the attention of the wider CS community and identifying some key factors in the successful adoption of challenging, or even threatening, new concepts in learning and teaching.

despite research support for the far greater efficacy of different approaches. For example, the benefits of social constructivism, including the zone of proximal development [11], are well known and extensively studied [7], [12], [13], yet the practice of group work may be employed without any knowledge of the underlying theory that would drive the detailed nature of such collaboration - or without requiring that group work even be collaboration. Group work, or team-based programming, is far more likely to reflect the practices of industry in achieving a programming task, instead of having been assembled in order to facilitate knowledge construction. Rather than placing such avoidance at the feet of malign influence, if we accept that threshold concepts can have an influence upon all types of learners, then we may consider the lack of adoption of research and evidence-based approaches in terms of:

II. T HRESHOLD C ONCEPTS In the educational field, Meyer and Land have identified threshold concepts [5] as a set of concepts that are transformative once understood but troublesome and alien before they are comprehended. The existence of these, often counterintuitive, concepts give the lie to Terence’s quote as it appears that certain concepts will be extremely foreign and hard to communicate or comprehend until we understand them. The major impact of these challenging concepts is on the ability of learners to form correct mental models [6], [7] and, regardless of whether we look at this in terms of a constructivist approach or any other theory of learning, threshold concepts are points where learners will have difficulty learning. To further define threshold concepts, from [5], they are also: 1) integrative, in that they identify a previously unknown way of linking concepts together, 2) irreversible, in that once truly learnt, this new way of thinking becomes part of the learner, and 3) area markers, in that they identify the boundary of a part (or all) of a set of concepts. An entire discipline may have a boundary, upon which may be placed a single threshold concept, the mastery of which indicates mastery of that discipline. Thus, one of the greatest obstacles to a learner having the requisite vision or motivation to pursue a new area of knowledge can be their rejection of a counterintuitive but transformative concept. For example, before accepting the potential benefits and enthusiastically adopting innovative learning and teaching ideas and practices, people who are learning in the area of CSER must first accept that the field is of benefit. Given the apprenticeship model that is the default system for developing new academic educators in higher education, this is a more challenging acceptance than it may first appear.

1) Misconceptions: The mental model of the teacher does not include an accurate depiction of the educational value or suitability of the techniques being employed. 2) Area isolation: The teacher does not have an integrated view of the discipline and thus sees no connection between actions taken in one place and those in another. 3) Lack of awareness: Key elements of community information are not reaching the teachers, or are not being accepted by the teachers. We will describe these as messenger failures and refer back to this shortly. Self motivation is of questionable value when we are dealing with misconceptions in an isolated community and reflection, without internal mechanisms at the correct stage of development or a supportive community, is not going to able to correct the misconceptions. Teachers are supposed to be experts in learning and, where teaching is taught and the scholarship is both concrete and expected, we can see mechanisms to provide enough guidance to reduce misconceptions and provide a sound basis for vision, motivation and practice. The tertiary Computer Science sector does not have a widespread tradition of scholarship in teaching, although this is slowly changing, and in many cases the traditional model that Dewey described predominates. Is this an intrinsic flaw in the discipline or a facet of its nature as a threshold concept? Yes, it is challenging to accept that everyone who taught you was potentially uninformed, or could have done better, but challenge alone does not define a threshold concept. Therefore, let us examine the area more closely. Scholarship in Computer Science learning and teaching illuminates one’s teaching practice. Discovering tools, theories and methodologies that can explain the actions of our students is of great importance to the educator and transforms the way that one thinks about learning and teaching. The lecturer is as much a learner as her or his students. Unconnected issues and events become connected. Causal relationships may be drawn between employing one set of activities or materials over another. But transformative and highly illuminative mechanisms often come at a substantial cost, especially when they are placed in direct confrontation with established and traditional teaching modes. When additional effort is required, the learner

A. Threshold Concepts in Educational Research Reading across the fields of education, educational psychology and Computer Science education research, it rapidly becomes apparent that some ideas have been described repeatedly over decades, but have gained little traction within CS. Dewey’s disgust at the prison-like school classroom was recorded in 1938, yet one can walk onto any campus in the world and find the same “cells”, arrayed in ranks. The majority of course design and implementation shows little influence of any of the research conducted in the last 20 years [8] , let alone the cognitive development stages of Piaget [9], the reliance upon authority found in Perry [10] or even the existence of threshold concepts themselves. The lecture is still the dominant communication form in many higher education institutions,

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of the discipline and learners who can function as discipline practitioners. From any discipline perspective of Computer Science, it is not enough to be able to program, what we (and our industry) wish to see is evidence that our learners will be able to think and act as Computer Scientists. The natural extension of this idea is that people who wish to learn about learning and teaching in CS will also face the same problem and it is essential that we regard the educator as a learner in this context, because we can then identify the additional support and resources required for certain key concepts, where adoption and acceptance have very high rewards. In identifying the impact of CSER as a threshold concept, we discuss key research concepts in CSER and trace their adoption within the community, showing where some ideas have been accepted and yet others, of equal value and similar mode, have failed. We have reviewed the literature to identify the spread and level of comprehension for key theories in CSER, concentrating on the introduction of the concepts of constructivism [6] and threshold concepts [5]. To frame this study, we must first accept that it is less than 10 years since the original publication of Meyer and Land’s original paper [5] and, as we will show in the literature review, despite a large amount of publication and work on Computer Science threshold concepts, the evolution of curricula is slow and, as a result, lack of penetration of these particular concepts may not indicate anything significant. However, armed with Meyer and Land’s identification of the concept of threshold concepts, we examine another core area of research that is of great theoretical and practical use to CS, the inter-twined concepts of team work, collaboration and social constructivism.

must be motivated and have a vision of where this effort will lead. It is essential that participants understand why they have to change, support that change and have a clear understanding of how they can bring about that change. This is potentially challenging to the point of threatening, as well as requiring more effort during the period of change and we believe that this explains why there is a great deal of resistance from those members of the community who have not yet embraced the scholarship of learning and teaching. Resistance to acceptance in the field may stem from effects that would be carefully addressed in our students (such as their ongoing problems with threshold concepts) but that are not addressed when dealing with teachers. Teachers are presented with the alien and the unsettling and, because do not recognise their dual nature as learners, we risk not providing the appropriate scaffolding to facilitate the acceptance of alien and troubling information. Thus, we regard educational research as a good example of a threshold concept and the way that we teach it to others must take into account its troublesome nature. Meyer and Land’s initial work in Threshold Concepts [5], [14] provided the core characteristics of the concepts as well as raising the importance of the mastery of threshold concepts on the development of an identity within the discipline and, while the concept is being troublesome, the occupancy of a liminal state. The liminal state is a transitional state that a learner occupies from the time they start to learn a concept, until they fully master it and identifies that state where a learner may suffer from oscillation, fragile knowledge [15] or be prone to resorting to mimicry as the conceptual and cognitive difficulties in mastering the new concept overwhelms them [16]. Oscillation is the movement backwards and forwards in terms of developing and understanding components of the concept, and is frustrating to both learner and educator as the learner appears to be ‘getting it’ then moves backwards. An obvious misinterpretation of this is that the learner has “stopped trying” or is either “lazy” or “stupid”, when in fact this reflects the intrinsic cognitive difficulty in the underling concept. Fragile knowledge is where the learner has some notions of how to solve problems but cannot construct a clean solution, which may allow excellent participation in certain activities and assessments but not others. Finally, mimicry is the reproduction of what has been seen, without true understanding, and may also pass for comprehension of the concept in an unintentionally deceptive manner. It is easy to construe the load on the learner during this liminal phase as being characterised by frustration, with the investment of effort without perceived reward and an equally large cognitive load in establishing precisely which level of knowledge has been constructed or received. Learners with fragile knowledge, at the low ebb of the oscillation, resorting to handing in cargocult solutions because they are overwhelmed by the demands of these concepts are, quite understandably, extremely vulnerable and in great need of assistance. Threshold concepts identify key stages in learning how a discipline practitioner thinks [14] and this provides a strict separation between learners who can employ the techniques

B. Threshold Concepts in Computer Science As with most disciplines, we have an educational research framework to describe how we teach and learn within the discipline, and a discipline research framework that describes how we extend and develop the discipline itself. If CSER is itself a threshold concept then, by definition, the concept of the threshold concept is itself a threshold concept. This is not syntactic juggling, as the impact of this statement is that a learner could encounter a challenging and alien concept, yet not have the vocabulary to identify what is bothering them, nor could the teacher appreciate why a particular area is causing problems for her or his students. With the introduction of threshold concept theory, there has been an increasing acceptance within the educational research community that many ongoing problems in the learning and teaching of Computer Science are caused by these challenging concepts. However, as we will show through our exploration of the literature, the spread of the ideas is relatively slow and heavily localised in the educational research community. The ongoing challenge of teaching computer programming (among other concepts) often leaves educators wondering why students are not learning and how we can address the stumbling blocks, especially in first year programming classes, and threshold concepts provide one explanation for why these particular blocks cause problems. Threshold concepts were

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concept theory in a way that can help teacher and learner. Does the threshold concept mechanism apply to itself? Is it a limiting factor on the communication and acceptance of itself as a new way to think about learning difficulties? When a community does not have one clear vision of their practices or accepted theory, then internal discussion may be affected (depending upon the degree of civility within the community) but discussions with external communities may result in confusion, if too many disparate views are expressed, and rejection, because the firm and consistent foundation that is required to convince other people is lacking. Given that our learners (who are teachers learning about learning) need a clear vision and enough information to be able to practice, any educational theory that is not sufficiently well supported is highly unlikely to make it into the practitioner community and it is even more likely that a challenging concept will be rejected more quickly, as there is no motivation to cross the threshold. We will further illustrate the disconnect between the flow of theoretical knowledge and educational practice through an examination of the use of constructivist theory and team work in undergraduate education.

contextualised in early work that linked the characteristics of threshold concepts to constructivist theory, mental models and the importance of student misconceptions [7]. Threshold concepts, aligned with the core concepts of the discipline in their role as area boundary markers, provide an organising principle for the curriculum. This provides a clear statement of organising element as a transformative achievement. The authors of this paper contrasted this with other organisational strategies, such as that based on Fundamental Ideas in Mathematics, where the criteria are: horizontal (observable in multiple ways or areas), vertical (taught at every level, with varying sophistication), relevant over time, and has an everyday sense and can be explained in ordinary language, after Schwill [17]. Schwill’s organisation has many advantages in terms of its explicable simplicity but, if threshold concepts exist and apply to discussions of Computer Science as well as the subject itself, then the final requirement (formally “the criterion of sense”) may well be one that we cannot meet. If certain ideas are so troublesome and require so much effort to overcome, their everyday sense or layperson’s language may not exist in a reachable form. The issues that arise from teaching programming have been studied in numerous ways [18], [19] and these previous studies identified a large group of students who had difficulty with writing programs, following the execution of programs, or, even before any writing had taken place, designing programs. The studies clearly indicated the presence of mimicry and fragile knowledge, indicators of the liminal state. Building upon this work and incorporating threshold concepts resulted in approaches such as anchor graphs, derived from threshold concepts and cognitive load to assist in course construction and assessment formation [20]. Philosophical works on whether threshold concepts existed in Computer Science and (if so) whether they were useful were answered with “Yes” and “Yes” [21] but these works also draw on earlier constructivist thinking on troublesome knowledge, especially that which is conceptually different or foreign [12]. Threshold concepts have become part of the dialogue of the educational research community in Computer Science and a number of studies have attempted to provide the pragmatic application into teaching programming, designing curricula and even choosing programming languages [22]. Works also include simple and practical discussions of getting students “unstuck” [23] and managing the potentially frustrating liminal state [16]. Despite having such a weighty title, threshold concepts may be seemingly simple and everyday, such as state, the setting of variables in the program [24]. This illustrates why understanding that such concepts exist, and that the transformative effect may elevate the learner to a point where the mundanity of the threshold concept when viewed from the other side, makes it difficult to communicate the core idea to a learner who has not yet begun to learn this concept or is in the liminal state. Combine this with the known problems of oscillation and the pressure of traditional deadline-based assessment mechanisms to deliver something, it is unsurprising that we strive for a pragmatic application of the threshold

C. Constructivism and Ben-Ari Constructivism is a theory of learning claiming that learners actively construct their knowledge rather than acting in a passive, absorbing role when exposed to lectures and educational texts [6]. Social constructivism requires the presence of others to aid in the construction, where radical constructivism focuses on the knowledge developed by the learner within themselves. As an example of a learning structure that can assist in knowledge construction, team work is at the heart of the vast majority of successful software engineering projects and almost all teaching of computer science will require students to work in teams at some stage. Where justified pedagogically, we draw upon social constructivism, the zone of proximal development [11] and notions of cognitive apprenticeship in order to provide a good social environment in which to construct knowledge. While the work of Vygotsky is the most obvious reference for social constructivism and the zone of proximal development, there is no guarantee that a work (even a research work) that discusses team work or student collaboration will cite Vygotsky directly. However, this assumes that the goal is that of Vygotsky (a theoretical perspective) rather than that of the industry writers who seek to achieve a project inside reasonable timeframes and predictable levels of quality. Team work, a single type of activity, may have different supporting arguments and we risk confusion if we do not identify what we seek to achieve. As illustrated in many of the papers mentioned previously, one of the most common access points for Computer Scientists to refer to constructivism is Ben-Ari’s 1998 work, helpfully entitled “Constructivism in computer science education” [6]. This is not the universally accepted reference, however, and, especially where the authors have a more extensive background in the educational or psychological disciplines ([25] for

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reduction of scaffolding, or because of the benefits of social constructivism, and we would not be surprised if the majority nods turned quickly to furrowed brows. We have a rich history of educational research and a rich vein of practice to draw upon but we wish to know what determines whether practice and understanding flow from one area to another. We have seen, with Ben-Ari, that the term “constructivism” has now entered certain lexicons where Vygotsky’s efforts did not. To understand this, we must briefly review the attractiveness of ideas. Why is the original author not the architect of change as it sweeps through our discipline?

example) or wish to specifically refer to social constructivism, Vygotsky is referenced directly. There are two key points in the citation of the work of BenAri, neither of which are criticisms of the original work. The first is that while Ben-Ari describes constructivism in terms of both social and radical, he does not cite Vyogtsky directly – the monograph referenced as [1] in his paper consists of many chapters and is a relatively exhaustive exploration of the area in the closely aligned field of Mathematics education, including references to the key works of Vygotsky. The second point is that Ben-Ari’s analysis of earlier studies clearly identifies characteristics such as “fragile knowledge”, “oscillation” and the problem with misconceptions leading towards other issues, clearly identifying the importance of establishing the correct mental model. (Thus, BenAri effectively identified the liminal state, without that terminology, some 7 years prior to the Meyer and Land paper.) An incorrect mental model will lead to nothing happening or the wrong thing happening. Computer programming languages are notoriously inflexible and errors in mental models can lead to problems of barriers (requirements that limit degree of expressiveness) and traps (logical errors caused by misunderstandings encouraged by the language) [22] that can prevent learners from achieving their goals. We conducted a search for works that included references to Ben-Ari and were clearly in the Computing Educational field and relevant, as provided by the Association for Computational Machinery’s Portal website, the IEEE’s IeeeXplore website and the Google Scholar portal, identifying those with any further citations behind their initial publication. We selected 52 papers, based on citation count and degree of relevance, and conducted a manual analysis to allow us to categorise them in the way that they employed the Ben-Ari reference. The Ben-Ari paper was cited in three key ways: as the person who introduced constructivism to Computer Science Education (historical), as the source of constructivism in Computer Science (reference) and for a discussion of students entering the class without a model of computer or programming (effectively ignoring constructivism). What emerged from our analysis is that, at some key points, Ben-Ari’s paper formed a bridge between the educational and psychological underpinnings of constructivism, and the computer science education community. Despite some misuse and misinterpretation of the original Ben-Ari paper, the acceptance of constructivism via Ben-Ari has been used to drive a number of initiatives including collaborative work, pair programming, addressing curriculum shortfalls and understanding why our students might have variations and deficiencies in their mental models. Yet the connection between theory and practice is still weak. Were we to ask if students should form programming teams for large, authentic industrystyle assignments, we would receive the answer “yes”. If we asked if programming courses should increase in conceptual difficulty over the years, introducing more and more teambased activities as we gradually removed tutoring and handholding for the students, we would expect to receive nods of agreement. However, ask if these were justified in terms of the

D. Adoption of Ideas Theories of models of cultural information transfer originated from the notion of the meme [26] and are, in loose terms, a way of explaining how ideas propagate. When dealing with the research underpinnings of any discipline, we do not usually refer to the attractiveness or suitability of an idea when we address a success or failure of propagation. However, the language of the threshold concept allows us now to separate concepts within an area into, effectively, mundane (not a threshold concept) and troublesome (the key identifier of the threshold concept). Whatever our theory of learning, troublesome concepts will slow the rate at which learning occurs and slow progress may lead to the learner disengaging and leaving. Social constructivism [11] provides one important way to overcome these problems but this requires that educators be sufficiently well informed regarding social constructivism to employ it correctly. Putting students together into a group is not guaranteed to facilitate collaborative work, unless the learning experience is correctly designed. To design this correctly requires the educator to understand the theory. To understand the theory, the educator has to have been exposed to the idea and to have accepted the idea. Once again, if the idea itself is challenging and a difficult concept to master, then the ability to overcome threshold concepts in our learners has an upper limit established by the ability of the educator to overcome the threshold concept that is threshold concepts! The reason that we cannot depend upon accidental adoption of sound theory is, firstly, that the liminal state and its associated frustration may reduce the effort invested unless careful scaffolding is provided but, secondly, because the roles of participants in the adoption of a successfully propagated idea depends upon the participants, the idea and the context in which it is focused [27]. In Computer Science, we also suffer from having many sources of information: the theoretical and mathematical community, the educational community, the psychology community, the Computer Science educational community and our industry links as well. Given that ideas and theory can be provided from all of these and then, in turn, demanded for accreditation of our students by any of these, it is possible to have a theory/practice divide and a great deal of variation in the nature, depth and selectivity of the citation of work to support research and practice.

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indirect connection. Through the accreditation process and the requirement to produce graduates who will be able to find gainful employment, the Industry requirements are a strong source of feedback to the practising CS educator. However, we are aware that there is a great deal of theory that is developed both inside and out of Computer Science and this can also be fed into the academic educational practitioners. Psychological research can reach the practising teaching community via industry, through the role of the evangelising populism of psychology in the form of video presentations (such as TedX), books and training courses, or through the influence of mainstream television. While few people in industry may be aware of neo-Piagetian theory, a large number will be aware of the debate over intrinsic and extrinsic motivating factors through the work of Kohn [29] and Pink [30]. Analysis of concepts from educational research and their application into Computer Science educational theory and teaching practice shows the two-speed system that is already in operation. While collaborative work, as Contributing Student Pedagogy (CSP) [13], cognitive apprenticeship [31] or (simply) social constructivism, is important, requirements are far more frequently specified as “work in teams”. When disastrously combined with poorly articulated limitations of team/individual contribution separations for summative activities, this absence of theoretical underpinning (and the usual linking of formative activities to this type of constructivist learning) suddenly becomes very apparent. Even the nature of research studies may be questioned, as certain disciplines would not necessarily recognise phenomenographic or grounded theory investigations due to a lack of familiarity. When the community cannot necessarily agree upon what constitutes a valid research study, it is hardly surprising that the value of the studies themselves may become contentious. If industry believes that graduates should be capable of team work, then assigning capstone teamwork projects will meet this requirement but this is not an educational requirement, this is a practice requirement. If assessment activities are constructed to allow for extensive collaboration on the principles of social constructivism, but are all formative in nature, then this theoretically-based teaching improvement may not be recognised as team work by industry. Both activities revolve around students working together and, aligned in terminology and intent, we can achieve both aims successfully with a single activity. Alignment is a difficult business and if we start introducing theoretical concepts that are essentially threshold in nature, then we must approach this exactly as we would when introducing threshold concepts to students. We must accept that this will be challenging. We must accept that careful scaffolding and cognitive load management has to be employed. Ultimately, we must accept that this idea might be rejected unequivocally until it is embraced as a breakthrough.

Mentors, Peers and Self (Apprenticeship and reflection)

Folk Pedagogy

Superstition Accident

Computer Science Educators

Studies Talks Conferences

Publication Peer Review Conferences

Accreditation Requirements Industry Practices

Computer Science Education Research

Educational Psychology

Fig. 1.

Computing Industry

Reflection Internal company review Standards Re-invention

Populists and Evangelists

Information Flow to Computer Science Teaching Practitioners

III. I NFORMATION F LOW IN C OMPUTER S CIENCE Ideas on how to teach and practice Computer Science enter the academy from numerous sources. There is no shortage in the variety of beliefs held by academics as to what constitutes “good” teaching practice [28], but it is rarer that we ask “why” someone holds a certain belief. There is also no one definitive type of teacher in Computer Science, we include those who conduct research, those who stay abreast of current scholarship and those who purely practice teaching in our midst. While research and scholarship are not the only way to gain knowledge, and we will discuss apprenticeship models shortly, the scholarship of the published works of a discipline are the way in which academics share their knowledge, so it is unsurprising to see it as a core contributor to the successful sharing of educational knowledge. Where academics are trained as educators, or have an educational background, their teaching may be informed by both their scholarship and the research in the discipline, as well as the seminal papers of educational research. Where academics have focused on discipline-derived research areas, their teaching may be more likely to have taken the form of an apprenticeship in combination with their reflection on their own experiences as a student - as we would expect from [4]. Where academics have come from industry, they are more likely to practice educational techniques that are the techniques of the practice. From Shulman’s model, with reflection at the core of the vision, motivation, understanding, practice model, the learning context will cause a great deal of variation in what constitutes valid motivation, an inspiring vision, recognised understanding and worthwhile practice. The flow of information into the teaching practitioners of the discipline of Computer Science may be captured as Figure 1. While some information may travel from the CS Educational research area into industry, this is a weak and generally

A. Messengers The Ben-Ari Constructivism paper occupies a special role in the Computer Science Education community as it appears to have brought constructivism into the dialogue of the main-

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formed is that everything up until now has potentially been wrong, as have our predecessors. Industry requirements are unlikely to step on traditional toes as, if the dialogue is with a higher educational facility, tradition is expected. The liminal state is frustrating for students but they are designated as learners by their titles. Educators going through the liminal state may feel embarrassed, stressed or even worthless. Educators at the tertiary level are expected to demonstrate mastery in their field [2], [3] and, by association, very few academics would consider themselves to be “bad” lecturers, regardless of student feedback or course outcomes. Educators need to retain their belief in both themselves and their ability to organise and change their environment [32] and they must believe in their own self-efficacy. This belief has a direct impact on the individual’s goal setting, and hence their vision, their motivation and their influence on their situations. If we continue to (correctly) regard the teacher as a learner, and computer science education as something to learn about, then the educator’s learning context is one of high stress and one that is at comparatively high risk of leading to low feelings of selfesteem and self-efficacy if mismanaged. As in Ben-Ari’s paper, where the student is unlikely to have a valid mental model for computation [6], an educator who has never been trained for teaching or exposed to educational research is unlikely to have the mental models to innately develop sound teaching practice, especially where counter-intuitive. They may not have any idea that their vision is lacking and, when challenged by ideas that seem counterintuitive and unnecessary, it is little surprise that they would reject them. Therefore, their teaching practice is potentially not integrated and they have neither the vocabulary nor the context to understand why change is being proposed. It is not an overstatement to say that it is easy to see how such a request for change could be seen as a statement of incompetence or an attack.

stream. While readily discussed in the Higher Educational community, the citations make it clear that the Ben-Ari paper acted in a way that allowed the concept to be more easily adopted within Computer Science. Papers prior to Meyer and Land make it clear that the problem of the threshold concept was known, but we did not have a convenient and consistent way to address the issue as a whole. (This is one of the many reasons that threshold concepts are threshold concepts, because they integrate an entire suite of apparently separate problems.) Meyer and Land, Ben-Ari and similar worlds act as messengers, in that they take a message from one place (educational research in the case of Ben-Ari, and as a semantic container in the case of Meyer and Land) and make it available to another community, using the language and models of the target community. This translation process makes the threshold concept from the other community easier to incorporate, reducing the cognitive load and marking a clear boundary of new understanding, with all of the permanence and transformation that we would expect. In other words, messengers facilitate threshold concept transfer and comprehension. The role of the messenger is to recontextualise the concept into a neutral space, separated from its origins and ready to be modelled into a new area. In the case of Ben-Ari, the 1998 paper provided a Computer Science fronted introduction to key monographs in mathematics and psychology. These monographs recontextualised Vygotsky and Piaget into a mathematical education context. Each in turn provided a way for another author to read and understand the work, and provide it in an even more comprehensible way to their peers. However, this required that the author be exposed to enough work across other disciplines in order to be able to use the language of their discipline in an authentic and wellgrounded manner. Data collection is an essential component of this process but is not sufficient to convey the idea - the nature and skill of the communicator is a significant factor. We would, therefore, expect that messengers are fewer in number and relatively higher in impact than their peers, assuming that they mostly transfer threshold concepts. Given that threshold concepts are transformative, and that many threshold concepts are cross-disciplinary, introducing a new concept successfully and establishing an idea in a new context would lead towards higher citation and enable to the messenger to continue introducing new messages. However, this requires the messenger to continue expending effort to be multi-homed and based in several disciplines at once. BenAri, in this context, had the advantage of a well-written paper that addressed an important issue but at a time, or in a way, that was able to introduce an important idea to a wider range of people.

IV. C ONCLUSIONS AND F UTURE W ORK Educational research concepts, when applied outside of the field of education, are essentially threshold concepts and, as such, must be very carefully introduced, contextualised, delivered by the correct messenger and take into account the many stages that the recipients may occupy. Our ability to develop new teaching techniques based on these sound theoretical principles are exacerbated by the theory/practice divide, where related concepts are separately introduced from two different approaches and risk being artificially separated in the curriculum, rather than integrated. If we accept that a number of the core ideas underpinning successful teaching are threshold concepts, then we have a reason for the delayed introduction of a number of these transformative ideas into the classroom. Now we have to identify the messages, the messengers and how we will provide scaffolding to communicate these ideas. Learning about learning, as a teaching practitioner in a discipline that does not have a well-established or universal commitment to scholarship of teaching, may be one of the most stressful and challenging environments in which an academic can find him or herself.

B. The Importance of Context The context is an essential consideration, as evidenced by the separation of industry-based practices and theory-based practices. If a survey of industry partners requires more teamwork than we add a teamwork assignment. If theoretical drivers state that the lecture is useless and that all work must be collaborative, then the (hostile) context that has now been

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Accepting that we are as vulnerable as our students to the effect of threshold concepts may provide an important first step towards improving the spread of these ideas. This paper illustrates one possible explanation for the limited adoption of certain educational approaches from existing research and scholarship in learning and teaching. However, this is a multi-faceted problem and an ongoing challenge. This survey is the beginning of a much larger project to map the core ideas and their spread across the literature and the curricula of the Higher Education community. There are many unanswered questions, including whether we ever truly reach a point where an empirically-based educator will accept certain ideas as mundane because of a societal or social shift. Other works planned include the mapping of the spread of citations, including their replacements as messenger works (such as Ben-Ari) take the place of previous references. Is there a bias towards more recently prepared works and do limitations on physical libraries, the limited search ability of older texts and the sheer volume of pre-existing work conspire to overwhelm the novice? We are also working on materials and methods to introduce exemplars and pragmatic applications for the more challenging concepts. This may engender mimicry but if we accept that some of our colleagues will, by undertaking this work, enter the liminal state, then we must be prepared to scaffold and support them until such time as they attain mastery.

[14] J. H. F. Meyer and R. Land, “Threshold concepts and troublesome knowledge (2): Epistemological considerations and a conceptual framework for teaching and learning,” Higher Education, vol. 49, no. 3, pp. 373–388, Apr. 2005. [15] D. N. Perkins and F. Martin, “Fragile knowledge and neglected strategies in novice programmers,” in Papers presented at the first workshop on empirical studies of programmers on Empirical studies of programmers. Norwood, NJ, USA: Ablex Publishing Corp., 1986, pp. 213–229. [16] A. Eckerdal, R. McCartney, J. E. Mostr¨om, K. Sanders, L. Thomas, and C. Zander, “From limen to lumen: computing students in liminal spaces,” in Proceedings of the third international workshop on Computing education research, ser. ICER ’07. New York, NY, USA: ACM, 2007, pp. 123–132. [17] A. Schwill and U. Paderborn, “Fundamental ideas of computer science,” Bull. European Assoc. for Theoretical Computer Science, vol. 53, 1994. [18] M. McCracken, V. Almstrum, D. Diaz, M. Guzdial, D. Hagan, Y. B.D. Kolikant, C. Laxer, L. Thomas, I. Utting, and T. Wilusz, “A multinational, multi-institutional study of assessment of programming skills of first-year cs students,” in Working group reports from ITiCSE on Innovation and technology in computer science education, ser. ITiCSEWGR ’01. New York, NY, USA: ACM, 2001, pp. 125–180. [19] R. Lister, E. S. Adams, S. Fitzgerald, W. Fone, J. Hamer, M. Lindholm, R. McCartney, J. E. Mostr¨om, K. Sanders, O. Sepp¨al¨a, B. Simon, and L. Thomas, “A multi-national study of reading and tracing skills in novice programmers,” in Working group reports from ITiCSE on Innovation and technology in computer science education, ser. ITiCSEWGR ’04. New York, NY, USA: ACM, 2004, pp. 119–150. [20] J. Mead, S. Gray, J. Hamer, R. James, J. Sorva, C. S. Clair, and L. Thomas, “A cognitive approach to identifying measurable milestones for programming skill acquisition,” in Working group reports on ITiCSE on Innovation and technology in computer science education, ser. ITiCSE-WGR ’06. New York, NY, USA: ACM, 2006, pp. 182–194. [21] J. Boustedt, A. Eckerdal, R. McCartney, J. E. Mostr¨om, M. Ratcliffe, K. Sanders, and C. Zander, “Threshold concepts in computer science: do they exist and are they useful?” in Proceedings of the 38th SIGCSE technical symposium on Computer science education, ser. SIGCSE ’07. New York, NY, USA: ACM, 2007, pp. 504–508. [22] M. T. Flanagan and J. Smith, “From Playing to Understanding: The Transformative Potential of Discourse Versus Syntax in Learning to Program,” in Threshold Concepts Within the Disciplines, R. Land, J. H. F. Meyer, and J. Smith, Eds. Sense Publishers, 2008, ch. 7, pp. 91–103. [23] R. McCartney, A. Eckerdal, J. E. Mostrom, K. Sanders, and C. Zander, “Successful students’ strategies for getting unstuck,” in Proceedings of the 12th annual SIGCSE conference on Innovation and technology in computer science education, ser. ITiCSE ’07. New York, NY, USA: ACM, 2007, pp. 156–160. [24] D. Shinners-Kennedy, “The Everydayness of Threshold Concepts: State as an Example from Computer Science,” in Threshold Concepts Within the Disciplines, R. Land, J. H. F. Meyer, and J. Smith, Eds. Sense Publishers, 2008, ch. 9, pp. 119–128. [25] M. Guzdial and K. Carroll, “Exploring the lack of dialogue in computersupported collaborative learning,” in Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community, ser. CSCL ’02. International Society of the Learning Sciences, 2002, pp. 418–424. [26] R. Dawkins, The Selfish Gene. Oxford University Press, 1976. [27] Gladwell, The Tipping Point: How Little Things Can Make a Big Difference. Little Brown, 2000. [28] K. Samuelowicz and J. Bain, “Revisiting academics’ beliefs about teaching and learning,” Higher Education, vol. 41, pp. 299–325, 2001. [29] A. Kohn, Punished by Rewards: The Trouble with Gold Stars, Incentive Plans, A’s, Praise, and Other Bribes . Houghton-Mifflin, 1999. [30] D. Pink, “Dan pink on motivation,” 2009. [31] R. Bareiss and M. Radley, “Coaching via cognitive apprenticeship,” in Proceedings of the 41st ACM technical symposium on Computer science education, ser. SIGCSE ’10. New York, NY, USA: ACM, 2010, pp. 162–166. [32] A. Brouwers and W. Tomic, “A longitudinal study of teacher burnout and perceived self-efficacy in classroom management,” Teaching and Teacher Education, vol. 16, pp. 239–253, 2000.

R EFERENCES [1] P. T. Afer, “Heauton Timorumenos,” 1857. [2] A. Lieberman and D. H. P. Mace, “Teacher Learning: the Key to Educational Reform,” Journal of Teacher Education, no. 3, pp. 226– 234, May/June 2008. [3] I. Bakkenes, J. D. Vermunt, and T. Wubbels, “Teacher learning in the context of educational innovation: Learning activities and learning outcomes of experienced teachers,” Learning and Instruction, vol. 20, no. 6, pp. 533 – 548, 2010. [4] L. S. Shulman and J. H. Shulman, “How and What Teachers Learn: A Shifting Perspective,” Journal of Curriculum Studies, vol. 36, no. 2, pp. 257–271, Mar-Apr 2004. [5] J. H. F. Meyer and R. Land, “Threshold Concepts and Troublesome Knowledge Linkages to Ways of Thinking and Practising,” in Improving Student Learning Ten Years On., C. Rust, Ed. Oxford, 2003. [6] M. Ben-Ari, “Constructivism in computer science education,” in Proceedings of the twenty-ninth SIGCSE technical symposium on Computer science education, ser. SIGCSE ’98. New York, NY, USA: ACM, 1998, pp. 257–261. [7] A. Eckerdal, R. McCartney, J. E. Mostr¨om, M. Ratcliffe, K. Sanders, and C. Zander, “Putting threshold concepts into context in computer science education,” in Proceedings of the 11th annual SIGCSE conference on Innovation and technology in computer science education, ser. ITICSE ’06. New York, NY, USA: ACM, 2006, pp. 103–107. [8] M. Gibbons, Higher education relevance in the 21st century. World Bank, 1998. [9] J. Piaget, The Origins of Intelligence in Children. International University Press, 1952. [10] W. G. Perry, Forms of Intellectual and Ethical Development in the College Years: A Scheme. Holt, Rinehart, and Winston, 1970. [11] L. S. Vygotsky, Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, 1978. [12] D. Perkins, “The Many Faces of Constructivism.” Educational Leadership, vol. 57, no. 3, pp. 6–11, November 1999. [13] J. Hamer, Q. Cutts, J. Jackova, A. Luxton-Reilly, R. McCartney, H. Purchase, C. Riedesel, M. Saeli, K. Sanders, and J. Sheard, “Contributing student pedagogy,” SIGCSE Bull., vol. 40, no. 4, pp. 194–212, Nov. 2008.

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