Towards a Framework for CSCL Research

Although collaborative learning, often supported by computer networks (widely called computer supported collaborative learning, or CSCL) is currently being implemented at all levels of education, it has not always proven to be the wonder-tool that educators envisioned and has often not lived up to the high expectations that educators had for it. In this introduction to the special issue on computer supported collaborative learning (CSCL), a framework for research on CSCL is presented. This framework is presented in the form of a 3 X 3 X 3 cube, with the dimensions Level of Learning (cognitive, social, and motivational), Unit of Learning (individual, group/team, and community) and Pedagogical measures (interactive, representational, and guiding). Based on this framework, the different contributions are discussed, and the empty cells - which should form the basis for further theoretical research – become evident

The Effects of constructing domain-specific representations on coordination processes and learning in a CSCL-environment

Slof, B., Erkens, G., & Kirschner, P. A. (2012). The effects of constructing domain-specific representations on coordination processes and learning in a CSCL-environment. Computers in Human Behavior, 28, 1478-1489. doi:10.1016/j.chb.2012.03.011This study examined the effects of scripting learners’ use of two types of representational tools (i.e., causal and simulation) on their online collaborative problem-solving. Scripting sequenced the phase-related part-task demands and made them explicit. This entailed (1) defining the problem and proposing multiple solutions (i.e., problem-solution) and (2) evaluating solutions and coming to a definitive solution (i.e., solution-evaluation). The causal tool was hypothesized to be best suited for problem solution and the simulation tool for solution evaluation. Teams of learners in four experimental conditions carried out the part-tasks in a predefined order, but differed in the tools they received. Teams in the causal-only and simulation-only conditions received either a causal or a simulation tool for both part-tasks. Teams in the causal-simulation and simulation-causal conditions received both tools in suited and unsuited order respectively. Results revealed that teams using the tool suited to each part-task constructed more task appropriate representations and were better able to share and negotiate knowledge. As a consequence, they performed better on the complex learning-task. Although all learners individually gained more domain knowledge, no differences were obtained between conditions

Coordinating collaborative problem-solving processes by providing part-task congruent representations

Slof, B., Erkens, G., & Kirschner, P. A. (2010, July). Coordinating collaborative problem-solving processes by providing part-task congruent representations. In K. Gomez, L. Lyons, & J. Radinsky (Eds.), Learning in the Disciplines: Proceedings of the 9th International Conference of the Learning Sciences (ICLS 2010) Volume 1 (pp. 675-682). Chicago IL: International Society of the Learning Sciences.This study investigated the effects of representational scripting on computer-supported collaborative solving of a complex problem. The premise was that effective student interaction would be evoked when the problem-solving task was structured into part-tasks supported representations congruent to the part-tasks (i.e., representational scripting). It was hypothesized that this would lead a better coordination of student discussions of the concepts, principles and procedures in the knowledge domain and consequently to better problem-solving performance. In triads, 39 secondary education students worked on a case-based business-economics problem in four experimental conditions. In one condition groups received three representations, each congruent to one of the three part-tasks. In the other three conditions, groups received one of the representations for all three part-tasks, thus a representation congruent to one part-task, but incongruent to the other two. The results show that using representational scripting evoked more communicative activities and led to better problem-solving performance

Representational scripting to support students’ online problem-solving performance

Slof, B., Erkens, G., & Kirschner, P. A. (2010, July). Representational scripting to support students’ online problem-solving performance. In K. Gomez, L. Lyons, & J. Radinsky (Eds.), Learning in the Disciplines: Proceedings of the 9th International Conference of the Learning Sciences (ICLS 2010) Volume 1 (pp. 476-483). Chicago IL: International Society of the Learning Sciences.This study investigated the effects of representational scripting on student learning while online collaboratively solving a complex problem. The premise here is that effective student interaction would be evoked when the problem-solving task is structured into part-tasks that are supported by providing part-task congruent representations (i.e., representational scripting). It was hypothesized that such an approach would lead to a more appropriate student interaction and as a consequence better problem-solving performance. In triads secondary education students worked on a case-based business-economics problem in four experimental conditions, namely one condition in which the groups received representations that were congruent for all three part-tasks and three conditions in which the groups received one of these representations for all three part-tasks. The results show that using representational sripting indeed leads to a more elaborated discussion about the content of the knowledge domain (i.e., concepts, solutions and relations) and to better problem-solving performance

Visualization of argumentation as shared activity

The use of argumentation maps in CSCL does not always provide students with the intended support for their collaboration. In this chapter we compare two argumentation maps from two research projects, both meant to support the collaborative writing of argumentative essays based on external sources. In the COSAR-project, the Diagram-tool with which students could specify positions, proarguments, con-arguments, supports, refutations and conclusions in a free graphical format to write a social studies essay, was highly appreciated by students and teachers, but did not result in better essays. In the CRoCiCL-project, the Debate-tool with which students could specify positions, proarguments, con-arguments, supports and refutations in a structured graphical format, meant to visualize the argumentative strength of the positions, resulted in better history essays. The difference in representational guidance between both tools might explain these differences in effects, with the Debate-tool stimulating students to attend to the justification of positions and their strengths

Matching presentational tools' ontology to part-task demands to foster problem-solving in business economics

Slof, B., Erkens, G., & Kirschner, P. A. (2010, July). Matching representational tools’ ontology to part-task demands to foster problem-solving in business economics. In K. Gomez, L. Lyons, & J. Radinsky (Eds.), Learning in the Disciplines: Proceedings of the 9th International Conference of the Learning Sciences (ICLS 2010) Volume 2 (pp. 16-18). Chicago IL: International Society of the Learning Sciences.Collaborative problem-solving is often regarded as an effective pedagogical method beneficial for both group and individual learning. The premise underlying this approach is that through a dynamic process of eliciting one’s own knowledge, discussing this with peers, and establishing and refining the group’s shared understanding of the knowledge domain, students acquire new knowledge and skills and process them more deeply (e.g., O'Donnell, Hmelo-Silver, & Erkens, 2006). However, due to its complexity (i.e., diversity in concepts, principles and procedures, see Miller & VanFossen, 2008) students in business economics encounter difficulties with acquiring a well-developed understanding of the knowledge domain (e.g., Marangos & Alleys, 2007). When solving problems, students, therefore, rely primarily on surface features such as using objects referred to in the problem instead of the underlying principles of the knowledge domain, and employ weak problem-solving strategies such as working via a means-ends strategy towards a solution (e.g., Jonassen & Ionas, 2008). This hinders students in effectively and efficiently coping with their problem-solving task because the ease with which a problem can be solved often depends on the quality of the available problem representations (e.g., Ploetzner, Fehse, Kneser, & Spada, 1999). To this end, it would be beneficial if students are supported in acquiring and applying suitable representations (e.g., Ainsworth, 2006). Research on concept mapping (Nesbit & Adesope, 2006; Roth & Roychoudhury, 1993) has shown that the collaborative construction of external representations (i.e., concept maps) can guide students’ collaborative cognitive activities and beneficially affect learning. Due to its ontology (i.e., objects, relations, and rules for combining them, see Van Bruggen, Boshuizen, & Kirschner, 2003) a representational tool enables students to co-construct a domainspecific content scheme fostering students’ understanding of the knowledge domain in question. Problemsolving tasks, however, are usually composed of fundamentally different part-tasks (i.e., problem orientation, problem solution, solution evaluation), that each requires a different perspective on the knowledge domain and, thus, another representational tool with a different ontology. To be supportive for problem-solving, the ontology provided in a representational tool must be matched to the part-task demands and activities of a specific problem phase. Otherwise, effective problem-solving may be hindered (e.g., Van Bruggen et al.). The goal of the study presented in this paper is to determine whether an instructional design aimed at providing ontologically part-task congruent support in the representational tools leads to more successful problem-solving performance in the field of business economics

Group awareness of social and cognitive performance in a CSCL environment: Effects of a peer feedback and reflection tool

Phielix, C., Prins, F. J., Kirschner, P. A., Erkens, G., & Jaspers, J. (2011). Group awareness of social and cognitive performance in a CSCL environment: Effects of a peer feedback and reflection tool. Computers in Human Behavior, 27(3), 1087-1102. doi:10.1016/j.chb.2010.06.024A peer feedback tool (Radar) and a reflection tool (Reflector) were used to enhance group performance in a computer-supported collaborative learning environment. Radar allows group members to assess themselves and their fellow group members on six traits related to social and cognitive behavior. Reflector stimulates group members to reflect on their past, present and future group functioning, stimulating them to set goals and formulate plans to improve their social and cognitive performance. The underlying assumption was that group performance would be positively influenced by making group members aware of how they, their peers and the whole group perceive their social and cognitive behavior in the group. Participants were 108 fourth-year high school students working in dyads, triads and groups of four on a collaborative writing task, with or without the tools. Results demonstrate that awareness stimulated by the peer feedback and reflection tools enhances group-process satisfaction and social performance of CSCL-groups

Successfully carrying out complex learning tasks through guiding teams’ qualitative and quantitative reasoning

Slof, B., Erkens, G., Kirschner, P. A., Janssen, J., & Jaspers, J. G. M. (2012). Successfully carrying out complex learning tasks through guiding teams' qualitative and quantitative reasoning. Instructional Science, 40, 623-643. DOI: 10.1007/s11251-011-9185-2This study investigated whether and how scripting learners’ use of representational tools in a Computer Supported Collaborative Learning (CSCL)-environment fostered their collaborative performance on a complex business-economics task. Scripting the problem-solving process sequenced and made its phase-related part-task demands explicit, namely defining the problem and proposing multiple solutions, followed by determining suitability of the solutions and coming to a definitive problem solution. Two tools facilitated construction of causal or mathematical domain representations. Each was suited for carrying out the part-task demands of one specific problem-solving phase; the causal was matched to problem-solution phase and the mathematical (in the form of a simulation) to the solution-evaluation phase. Teams of learners (N = 34, Mean age = 15.7) in four experimental conditions carried out the part-tasks in a predefined order, but differed in the representational tool/tools they received during the collaborative problem-solving process. The tools were matched, partly matched or mismatched to the part-task demands. Teams in the causal-only (n = 9) and simulation-only (n = 9) conditions received either a causal or a simulation tool and were, thus, supported in only one of the two part-tasks. Teams in the simulation-causal condition (n = 9) received both tools, but in an order that was mismatched to the part-task demands. Teams in the causal-simulation condition (n = 7) received both tools in an order that matched the part-task demands of the problem phases. Results revealed that teams receiving part-task congruent tools constructed more task-appropriate representations and had more elaborated discussions about the domain. As a consequence, those teams performed better on the complex learning-task