id12099 mapping distributed cognition: a ...

Mapping Distributed Cognition: A Collaborative Constructionist Approach Inmaculada Arnedillo Sánchez, Centre for Research in IT in Education Trinity College Dublin, Ireland [email protected] Ann FitzGibbon Centre for Research in IT in Education Trinity College Dublin, Ireland [email protected]

Abstract: Concept mapping is widely reported in the literature as a technique to capture and represent internal knowledge (Cañas et al., 2001; Jonassen, Carr, & Yueh, 1998; M c Neil, 2004; Novak). Common uses of this tool in educational settings include assessment (M c Neil, 2004) and content/understanding organisation (West, Park, Pomeroy, & Sandoval, 2002), among others. This paper is concerned with the opportunity for learning that concept maps afford (Kinchin & Hay, 2000; M cAleese, 1998). This learning opportunity is analyzed in relation to the concepts of Constructionism (Papert, 1993b) and Distributed cognition (Perkins, 1993). In particular, this paper presents the experiences of postgraduate students undertaking a master’s programme in the field of Information Communication Technology (ICT) and Education. It discusses the use of concept maps as a constructionist tool to facilitate an exercise of collaborative distributed cognition.

Introduction The integration of technology and learning is a demanding task. It is an exercise on modifying mental models, “thought process that provides a representation of some entity or system” (Craik in Mc Neil, 2004, p. 1795). This is the experience of the authors who run a postgraduate programme in the field of Information Communication Technology (ICT) and Education in which the participants are evenly divided into ‘techies’ and ‘educationalists’. Within this context, a major challenge is to integrate and comb ine the views or mental models of the participants in the course. The chosen strategy to achieve our goal is a good shock, “the shock of our thoughts coming into co n t act with that of others" (Piaget, 1928, p. 204). The M.Sc. programme is strongly grounded in Constructionist principles (Papert, 1993a, 1993b). In line with these principles, this paper explores the use of concept mapping as a constructionist tool that enables students to represen t their individual abstract knowledge tangibly: thus, allowing them to create an ‘object to think with’ that “can be shown, discussed, examined, probed and admired” (Papert, 1990). When in groups, the concept map becomes a resource of distributed information facilitating the ‘shocking processes’ of collaborative distributed cognition. The paper initially presents a brief review of relevant literature, followed by a description of the programme and the students. The methodology is given and the results presented and discussed.

Literature Review Concept Map: Definition and common uses in education An abundance of concept map definitions are found in the literature. For instance Novak, credited with developing the technique in the 1960s, based it on David Ausubel's proposal that ‘learning takes p lace by the assimilation of new concepts and propositions into existing concept propositional frameworks held by the learner’; he defines Arnedillo Sánchez, I., & FitzGibbon, A. (2005). Mapping distrib uted cognition: a collab orative constructionist approach. In C. Crawford & R. Carlsen & I. Gibson & K. McFerrin & J. Price & R. Weber & D. A. Willis (Eds.), Society for Information Technology & Teacher Education International Conference Annual. Phoenix: Association for the Advancement of Computing in Education, 1100 - 1107.

concept maps as ‘tools for organizing and representing knowledge’ (Novak, pp.1,2). Cristea & Okamoto, in line with the representative function of concept maps, regard these as graphs or diagrams (Cristea & Okamoto, 2001) and McAleese suggests that they can also ‘… be seen in terms of a “learning environment”’ (McAleese, 1998, p. 4). The recurrence of the graphical characteristic of concept maps is also highlighted by Lawless et al. who favour the term ‘concept sorting’ rather than ‘concept mapping’: the former being ‘a simple, yet powerful way … to generate, sort, arrange and rearrange any set of elements… in a visually explicit manner...’ (Lawless et al., 1998, p. 219). Jonassen et al. introduce the notion of 'semantic networking tools' as methods of providing visual screen tools for producing concept maps , and identify them as Mindtools since they require students to think about what they know in meaningful ways (Jonassen et al., 1998). The previous definitions share the common ground of visual, graphical representation of an individual’s understanding. The product becomes a map when the relationships between the elements and their descriptions are added. Various roles are attributed to concept maps ranging from ‘framework’ for making ‘internal knowledge explicit in a visual form that can easily be examined and shared’ (Cañas, Leake, & Wilson, 1999, p.1), to ‘a ubiquitous tool’ (McAleese, 1998) with many uses. In the educational arena, four major functions are attributed to concept maps: instructional display (Jacobs -Lawson & Hershey, 2002; Lawson, 1994), evaluation device (Holder, 2004; Lawless et al., 1998; Lawson, 1994; West et al., 2002), curriculum organiser (Lawson, 1994), and index of understanding (Jacobs-Lawson & Hershey, 2002; Lawson, 1994; West et al., 2002). McAleese, contradicting the views of others, argues that concept maps should not be used “to evaluat e what learners know; rather, they allow learners an opportunity to engage in the process of learning” (McAleese, 1998, p.8). This view is also supported by Kinchin & Hay who argue for concept maps as “a qualitative instrument to aid the process of meaning ful learning” (Kinchin & Hay, 200, p. 46). The authors concur with McAleese and Kinchin & Hay and support the use of concept mapping as a technique to facilitate and engage students in meaningful learning. Concept Maps: Constructinist and Distributed Cognition Tools Constructionism advocates the construction of tangible (often ‘technological’) artefacts in order to support “the construction that takes place in the head” that “often happens especially felicitously when it is supported by construction of a more public sort in the world” (Papert, 1993a), by way of creating a product that “can be shown, discussed, examined, probed and admired” (Papert, 1990). Constructionist notions are also reported by Lawless in reviewing methods of concept sorting that utilise physical objects to facilitate the process: the Crawford Slip Method (utilising slips of papers), the Storyboarding method (utilising cards) and concept sorting with hexagons (utilising magnets on a whiteboard) (Lawless et al., 1998). The foregoing are examples of non-ICT-supported techniques to develop concept maps. In recent years however, the uptake of ICT in the educational field has seen the development of specific software to ease the creation and development of concept maps. Some of these include BrainBox and FreeMind freely available as well as many other commercial products. The creation of ICT-based concept maps is not exclusive to specific concept mapping software and for instance, word processing and presentation packages are commonly use d to develop concept maps. The common denominator of all the above-mentioned applications is their constructionist nature that allows students to create tangibly, manipulate, develop and show the representation of their understanding. Thus, they can facilitate the constructionist “cycle of internalisation of what is outside, then externalisation of what is inside and so on” (Papert, 1990). Distributed cognition shares with Constructivism the concept of representation of internal knowledge in the outside world and it is understood as a representation of the individual cognition in the outside world (Perkins, 1993). In a group context, the individual representation becomes a resource of distributed information for the members of the group. This resources is thought to facilitate the process of the individual’s construction and reconstruction of his/her knowledge (Stoyanova & Kommers, 2002). Stoyanova & Kommers (2002) draw the distinction between distributed cognition and shared cognition. They propose that the latter places a stronger emphasis on the need for a common framework among collaborators in order for these to be able to internalize and integrate knowledge to their own cognitive structures (Stoyanova & Kommers, 2002). This is an interesting concept that remains outside of the scope of this study, which merely attempts to map distributed cognition within the framework of a constructionist collaborative concept map exercise. Arnedillo Sánchez, I., & FitzGibbon, A. (2005). Mapping distrib uted cognition: a collab orative constructionist approach. In C. Crawford & R. Carlsen & I. Gibson & K. McFerrin & J. Price & R. Weber & D. A. Willis (Eds.), Society for Information Technology & Teacher Education International Conference Annual. Phoenix: Association for the Advancement of Computing in Education, 1100 - 1107.

Collaborati ve Learning: Definition and Mechanisms The term ‘Collaborative Learning’ is used to describe a situation in which an interaction is expected to occur, the occurrence of this interaction yields learning (Roschelle & Teasley, 1995). Collaboration involves the sharing of knowledge, sharing requires the articulation of an individual’s understanding of that knowledge. Articulation forces a person to reflect; this reflection leads to better understanding of one’s own thinking process (Brown, Collins, & Duguid, 1989). Crook identifies three mechanisms by which collaboration facilitates learning: conflict, articulation and co construction (Crook, 1994, pp. 133-139). Conflict or disagreement will naturally arise as the result of interactions between individuals. This cognitive conflict has the effect of forcing learners to reflect and construct new conceptual structures. Articulation encourages the learners to consciously consider their own knowledge before it is spoken in a public forum and it can in turn catalyse a student’s reflection and development. Both mechanisms conflict and articulation facilitate knowledge construction ‘within’ the learner. Nonetheless, when these mechanisms are enacted in the context of a group the emphasis shifts from disagreement and conflict to mutual engagement. T his process leads to a co-construction of knowledge (Vygotsky, 1978). It has been claimed that using a computer as an agent, or ‘intellectual partner,’ not only assists but can enhance the learning process (Salomon, 1993). Learning through collaboration when mediated by computers is often characterised by intellectually superior performances that cannot be accounted for by individual’s cognition alone (Salomon, Perkins, & Globerson, 1991). The proposition of this study is to map the superior distributed cognition of groups engaged in constructionist collaborative concept mapping.

The Context: MSc IT in Education Programme The course in question is a new two-year, part-time Master’s programme in the area of Information Technology in Education. The participants of the course are lifelong learners with a full-time occupation and from an extremely varied background spectrum; thus in any one year it is not unusual to have a cohort of learners made up of teachers from primary, secondary and tertiary levels (some with postgraduate degrees), trainers in a variety of subjects and contexts (communities, corporations, formal educational institutions, and so on), software engineers, solicitors and barristers, musicians, technical support personnel, Armed forces personnel, e-learning developers, housewives, and so forth. The course has an average intake of 25 participants. The first year is taught and the second year is devoted to a research dissertation.

Methodology The study took place during the first term of the Learning theory module in which the students are exposed to the main schools of thoughts of learning theory with particular emphasis on theories informing the pedagogical use of ICT. The module although in “nature” theoretical has a very hands -on practical approach and is project-based, problem-solving oriented and student-centred. Participants and Study Design In the second session of the module the 25 students taking the programme were briefly introduced to the principles and basic techniques of concept mapping. They were introduced to two concept mapping applications, BrainBox and FreeMind. Subsequently, they were asked to develop their individual concept map of their individual knowledge, understanding and vision of the relationship between ICT and learning/education. The students were offered the choice to create the map either with the applications presented with any other application they felt was appropriate or with pen and paper. This array of options was offered in order to allow the students to concentrate on the creation of the concept map and to avoid possible drawbacks from the lack of familiarity with the applications. After having completed the exercise volunteers were invited to present and discuss their concept maps with the class in order to facilitate “the shock of our thoughts coming into contact with that of others" (Piaget, 1928, p. 204).

Arnedillo Sánchez, I., & FitzGibbon, A. (2005). Mapping distrib uted cognition: a collab orative constructionist approach. In C. Crawford & R. Carlsen & I. Gibson & K. McFerrin & J. Price & R. Weber & D. A. Willis (Eds.), Society for Information Technology & Teacher Education International Conference Annual. Phoenix: Association for the Advancement of Computing in Education, 1100 - 1107.

The individual concept maps were analys ed against Kinchin & Hay’s three main concept map structures: chain, spoke and net. These correspond to different levels of understanding and concept complexity being the net the most complex and the other two less so (Kinchin & Hay, 2000). This analysis served as the basis to determine the composition of the eight ‘mixed-concept map’ groups of varying size that were formed to engage in the creation and development of constructionist collaborative concept maps. In the following session the students were asked to revisit their own concept map and to construct a collaborative concept map in their allocated group. As in the previous session, on the completion of the exercise volunteer groups were invited to present and discuss their concept maps with their peers. The exact same procedure, the creation of an individu al concept map and presentation and the creation of a collaborative concepts map (in the same groups) and presentation, was repeated in subsequent sessions. Data and Data Analysis In total 52 concept maps were returned: 20 individual concept map (ICM) 1, 8 group concept map (GCM) 1, 16 ICM 2 and 8 GCM 2. The exercise is part of the many in-class activities that the students undertake not for assessment purposes which may explain the missing follow-up individual concept maps. The data in this study is restricted to those students who submitted both ICMs and therefore includes 36 concept maps distributed in five groups: 13 ICM 1, 13 ICM 2, 5 GCM 1 and 5 GCM 2. The group concept maps that did not meet this criterion were not taken into the sample to be analysed, since individual contributions (individual concept maps) were missing and it would have been impossible to map individual contributions to the groups’ concept maps. In order to map the occurrences of distributed cognition the concept maps were analysed against a criteria based on the one developed by Stoyanova & Kommers (2002). Individual concept maps were analysed in terms of:  Fluency. It is understood as the total number of concept present in an individual’s concept map. It is measure by counting the number of nodes in a concept map.  Enrichment. It is defined as the change in the number of concepts present in the individual’s concept maps. It is measure as the difference in concepts in ICM 1 and ICM 2.  Knowledge Acquisition. It is taken to represent the number of new concepts represented by a student. It is measured by the number of new concepts in ICM 2 not found in ICM 1.  Creativity. It is representative of the number of new concepts created by an individual after the collaboration. It is measured by the number of concepts in the ICM 2 that cannot be found in the ICM 1 either on the GCM 1  Retention. It represents the numbers of concepts that an individual carries through from ICM 1 to ICM 2. Group Concept maps were analysed in terms of:  Fluency. It is understood as the total number of concept present in a group’s concept map. It is measure by counting the number of nodes in a concept map.  Enrichment. It is defined as the change in the number of concept present in the group’s concept maps. It is measure as the difference in concepts in GCM 1 and GCM 2.  Knowledge Acquisition. It is taken to represent the number of new concepts represented by a group. It is measured by the number of new concepts in GCM 2 not found in GCM 1.  Creativity. It is representative of the number of new concepts created by the group as a result of the collaboration. Creativity in GCM 1 is measured by the number of concepts in GCM 1 that cannot be found in the ICM 1 of any of the members of the group. Creativity in GCM 2 is measured by the number of concepts in the GCM 2 that cannot be found in the GCM 1 either on the ICM 1 of any of the members of the group.  Retention. The numbers of concepts that a group carries through from GCM 1 to GCM 2.  Individual to Group Transfer. The number of concepts from an ICM found in a GCM.  Group to Individual Transfer. The number of concepts from a GCM found in an ICM.

Results and Analysis The following section presents the results of the constructionist collaborative. Datadesk and Excel were used to analyse the data; however the small sample size precluded in -depth statistical analysis. The results are discussed in terms of the occurrence of distributed cognition. Arnedillo Sánchez, I., & FitzGibbon, A. (2005). Mapping distrib uted cognition: a collab orative constructionist approach. In C. Crawford & R. Carlsen & I. Gibson & K. McFerrin & J. Price & R. Weber & D. A. Willis (Eds.), Society for Information Technology & Teacher Education International Conference Annual. Phoenix: Association for the Advancement of Computing in Education, 1100 - 1107.

As might be anticipated fluency is more prevalent in the group maps; with one exception the groups increased their number of concepts in the second map (Fig. 1). In contrast, in the ICM scenario four students decreased the number of concepts in ICM 2; student number 5 who had the largest decrease commented “ Did you ever get the feeling you were going backwards!!!” (Fig. 2). This illustrates the difficulty some students have in identifying and integrating the data they were being exposed within the course structures. It must be restated that the authors are not suggestin g that fewer concepts in the ICMs is a negative situation. The quality of the concepts is not part of this study. Some of the initial concepts were discarded because the students realised their inappropriateness.

Figure 1: Group Fluency & Enrichment There were no significant relationships between either gender of student or academic background and fluency or enrichment. There was a slight but not significant tendency (p=0.16) for students who had an ICT background to contribute more concepts. The data suggest that the occurrences of fluency and enrichment is facilitated by the distributed cognition in the collaborative concept mapping situations.

Figure 2: Individual Fluency and Enrichment Apart from group 5, which created no less than 18 new concepts, creativity and retention in the GCM scenario (Fig. 3) are minimal with little increase in either. However there is substantial knowledge acquisition in GCM 2. The number of new concepts generated by the groups (Fig. 3) once again seems to suggest tha t the cognition process is facilitated by the GCM activity. Likewise, knowledge acquisition and creativity in the ICMs (Fig. 4) point to the facilitating role of the collaborative concept map and the access to distributed cognition in order to enable stud ents to generate new concepts. It should be noted that for the majority of the participants the value of creativity equals Arnedillo Sánchez, I., & FitzGibbon, A. (2005). Mapping distrib uted cognition: a collab orative constructionist approach. In C. Crawford & R. Carlsen & I. Gibson & K. McFerrin & J. Price & R. Weber & D. A. Willis (Eds.), Society for Information Technology & Teacher Education International Conference Annual. Phoenix: Association for the Advancement of Computing in Education, 1100 - 1107.

that of knowledge construction; this means that the concepts generated were not present in the earlier ICMs or GCMs.

Figure 3: Group Knowledge Acquisition, Creativity & Retention The previous charts and data analysis seem to indicate that the distributed cognition of the group is greater than the sum of the cognition of its individual members. This is suggested by the increased fluency found in the GCM 2 (Fig. 1) and the knowledge acquisition and creativity reported in Fig 3. That being the case, one would also suspect that the group would influence the individual in a noticeable manner.

Figure 4: Individual Knowledge Acquisition, Creativity & Retention


Figure 5: Individual-group Transfer & Group-individual Transfer The data from this study does not support this hypothesis. In fact, it is evident from the data reported in Fig. 5 that the group had almost no influence on the individual in terms of the number of concepts transferred from the GCM to the ICM. This may indicate that a more qualitative analysis of the data is imperative in order to gain insight into the occurrence, or lack, of transfer from the group to the individual. Further studies could be focused in this direction.

Conclusion This study has attempted to map distributed cognition, a representation of the individual cognition in the outside world (Perkins, 1993), in the context of a constructionist collaborative concept map exercise. In the context of a group, it was hoped that the individual representation became a resource of distributed information for the members of the group and that these resources would have help the process of the individual’s construc tion and reconstruction of his/her knowledge (Stoyanova & Kommers, 2002). The concept maps were analysed against criteria based on the one developed by Stoyanova & Kommers (2002) in an attempt to track the occurrence of cognition and its distribution. The data will need to be revisited, taking a qualitative approach, so that those elements that cannot be accounted for in figures, such as quality of concepts and student’s thinking behind their choices of concepts. can be elucidated. Fig. 6 shows an example of the spatial reconfiguration of one group’s maps. The principal objective of the study was to capture distributed cognition. This was attempted by inviting the participants to create individual as well as group concept maps. The data collected suggests that the exercise was successful in facilitating the construction of distributed cognition. This is supported by the abundance of concepts (fluency) generated by the groups, and new concepts (knowledge construction and creativity) generated by both the groups and individuals. The authors had hypothesised that the group, its distributed cognition, would have had a significant influence on the distributed cognition of the individual as represented in the individual concept map 2. This hypothesis was not verified by the data collected. Further research is required in order to overcome the limitations of this study in terms of data sample, and qualitative analysis. Future work should also aim in the direction of sheding light over the transfer from the grou p to the individual. Without doubt, the distributed cognition of the group facilitates the individual construction and reconstruction of knowledge. The dilemma for the authors remains how to map this transfer of cognition.


Figure 6. Examples of GCMs


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