Abstract
One of the main difficulties during the design of collaborative learning activities is adequate group formation. In any type of collaboration, group formation plays a critical role in the learners’ acceptance of group activities, as well as the success of the collaborative learning process. Nevertheless, to propose both an effective and pedagogically sound group formation is a complex issue due to multiple factors that influence group arrangement. The current (and previous) learner’s knowledge and skills, the roles and strategies used by learners to interact among themselves, and the teacher’s preferences are some examples of factors to be considered while forming groups. To identify which factors are essential (or desired) in effective group formation, a well-structured and formalized representation of collaborative learning processes, supported by a strong pedagogical basis, is desirable. Thus, the main goal of this paper is to present an ontology that works as a framework based on learning theories that facilitate group formation and collaborative learning design. The ontology provides the necessary formalization to represent collaborative learning and its processes, while learning theories provide support in making pedagogical decisions such as gathering learners in groups and planning the scenario where the collaboration will take place. Although the use of learning theories to support collaborative learning is open for criticism, we identify that they provide important information which can be useful in allowing for more effective learning. To validate the usefulness and effectiveness of this approach, we use this ontology to form and run group activities carried out by four instructors and 20 participants. The experiment was utilized as a proof-of-concept and the results suggest that our ontological framework facilitates the effective design of group activities, and can positively affect the performance of individuals during group learning.









Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Notes
An improvement of group performance does not guarantee an improvement of learning (Dillenbourg 2002).
Such a scheme should be understood as a suggestion to improve the quality of CL and not as imposed rules.
More information about this framework can be found in http://edont.qee.jp/omnibus/
W(A)-goal: W stands for the Whole-group and A stands for Arrangement.
The Role Holder concept is a very deep concept to treat roles adequately in ontologies. Further information about the definition of this concept can be found in (Mizoguchi et al. 2007).
References
Alfonseca, E., Carro, R. M., Martín, E., Ortigosa, A., & Paredes, P. (2006). The impact of learning styles on student grouping for collaborative learning: a case study. User Modeling and User-Adapted Interaction, 16(3–4), 377–401.
Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89(4), 369–406.
Aronson, E., & Patnoe, S. (1997). The jigsaw classroom: Building cooperation in the classroom (2nd ed.). New York: Addison Wesley Longman.
Bandura, A. (1971). Social learning theory. New York: General Learning.
Barkley, E., Cross, K. P., & Major, C. H. (2005). Collaborative learning techniques: A practical guide to promoting learning in groups. San Francisco: Jossey Bass.
Barros, B., Verdejo, M. F., Read, T., & Mizoguchi, R. (2002). Applications of a collaborative learning ontology. In Proceedings of the Mexican International Conference on Artificial Intelligence, LNCS 2313, 103–118.
Cognition and Technology Group at Vanderbilt. (1992). Anchored instruction in science education. In R. Duschl & R. Hamilton (Eds.), Philosophy of science, cognitive psychology, and educational theory and practice (pp. 244–273). Albany: SUNY.
Collins, A. (1991). Cognitive apprenticeship and instructional technology. In L. Idol & B. F. Jones (Eds.), Educational values and cognitive instruction: Implications for reform (pp. 121–138). Hillsdale: Erlbaum.
Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2001). Introduction to algorithms. Cambridge: The MIT.
Deibel, K. (2005). Team formation methods for increasing interaction during in-class group work. ACM SIGCSE Bulletin, 37(3), 291–295.
Dillenbourg, P. (2002). Over-scripting CSCL: The risks of blending collaborative learning with instructional design. In P. A. Kirschner (Ed.), Three worlds of CSCL. Can we support CSCL? (pp. 61–91). Heerlen: Open University Nederland.
Devedzic, V. (2006). Semantic web and education. New York: Springer.
Endlsey, W. R. (1980). Peer tutorial instruction. Englewood Cliffs: Educational Technology.
Ertmer, P. A., & Newby, T. J. (1993). Behaviorism, cognitivism, constructivism: comparing critical features from an instructional design perspective. Performance Improvement Quarterly, 6(4), 50–70.
Faria, E. S. J., Adán-Coello, J. M., Yamanaka, K. (2006). Forming groups for collaborative learning in introductory computer programming courses based on students’ programming styles: An empirical study. In Procceedings of the ASEE/IEEE Frontiers in Education Conference, S4E-6–S4E-11.
Fiechtner, S. B., & Davis, E. A. (1985). Why some groups fail: a survey of students’ experiences with learning groups. Organizational Behavior Teaching Review, 9(4), 75–88.
Graf, S., & Bekele, R. (2006). Forming heterogeneous groups for intelligent collaborative learning systems with ant colony optimization. In Proceedings of Intelligent Tutoring Systems, LNCS 4053, 217–226.
Greer, J., McCalla, G., Cooke, J., Collins, J., Kumar, V., Bishop, A., & Vassileva, J. (1998). The Intelligent Helpdesk: Supporting Peer-Help in a University Course. International Conference on Intelligent Tutoring Systems, LNCS 1452, 494–503.
Harrer, A., McLaren, B. M., Walker, E., Bollen, L., & Sewall, J. (2006). Creating cognitive tutors for collaborative learning: steps toward realization. User Modeling and User-Adapted Interaction, 16(3–4), 175–209.
Hayashi, Y., Bourdeau, J., & Mizoguchi, R. (2006). Ontological support for a theory-eclectic approach to instructional and learning design. In Proceedings of the European Conference on Technology Enhanced Learning, LNCS 4227, 155–169.
Hayashi, Y., Bourdeau, J., & Mizoguchi, R. (2008). Structurization of learning/instructional design knowledge for theory-aware authoring systems. In Proceedings of the International Conference on Intelligent Tutoring Systems, LNCS 5091, 573–582.
Inaba, A., & Mizoguchi, R. (2004). Learners’ roles and predictable educational benefits in collaborative learning. In Proceedings of the International Conference on Intelligent Tutoring Systems, LNCS 3220, 285–294.
Inaba, A., Supnithi, T., Ikeda, M., & Mizoguchi, R. (2000). How can we form effective collaborative learning groups. In Proceedings of Intelligent Tutoring Systems, LNCS 1839, 282–291.
Inaba, A., Ohkubo, R., Ikeda, M., & Mizoguchi, R. (2002). An interaction analysis support system for CSCL. In Proceedings of the International Conference on Computers in Education. IEEE Press. 358–362.
Inaba, A., Ikeda, M., & Mizoguchi, R. (2003). What learning patterns are effective for a learner’s growth? In Proceedings of the International Conference on Artificial Intelligence in Education, 219–226.
Isotani, S., & Mizoguchi, R. (2006). An integrated framework for fine-grained analysis and design of group learning activities. In Proceedings of the International Conference on Computers in Education, IOS Press, v. 151, 193–200.
Isotani, S., & Mizoguchi, R. (2007). Deployment of ontologies for an effective design of collaborative learning scenarios. In Proceedings of the International Workshop on Groupware, LNCS 4715, 223–238.
Isotani, S., & Mizoguchi, R. (2008). Adventures in the boundary between domain-independent ontologies and domain content for CSCL. In Proceedings of the International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, LNAI 5179, 523–532.
Kobbe, L., Weinberger, A., Dillenbourg, P., Harrer, A., Hämäläinen, R., & Fischer, F. (2007). Specifying computer-supported collaboration scripts. International Journal of Computer-Supported Collaborative Learning, 2(2–3), 211–224.
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. New York: Cambridge University Press.
Miao, Y., Hoeksema, K., Hoppe, H. U., & Harrer, A. (2005). CSCL scripts: Modelling features and potential use. In Proceedings of the International Conference on Computer Support for Collaborative Learning, 423–432.
Mizoguchi, R., Sunagawa, R., Kozaki, K., & Kitamura, Y. (2007). The model of roles within an ontology development tool: Hozo. Applied Ontology, 2(2), 159–179.
Muhlenbrock, M. (2005). Formation of learning groups by using learner profiles and context information. In Proceedings of the International Conference on Artificial Intelligence in Education, 507–514.
Ounnas, A., Davis, H., & Millard, D. (2008). A framework for semantic group formation. In Proceedings of the IEEE International Conference on Advanced Learning Technologies, 34–38.
Psyche, V., Bourdeau, J., Nkambou, R., & Mizoguchi, R. (2005). Making learning Design standards works with an ontology of educational theories. In Proceedings of the International Conference on Artificial Intelligence in Education, 539–546.
Resta, P., & Laferrière, T. (2007). Technology in support of collaborative learning. Educational Psychology Review, 19(1), 65–83.
Rumelhart, D. E., & Norman, D. A. (1978). Accretion, tuning, and restructuring: Three modes of learning. In J. W. Cotton & R. Klatzky (Eds.), Semantic factors in cognition (pp. 37–53). Hillsdale: Erlbaum.
Romiszowski, A. J. (1981). Designing instructional systems. New York: Nichols.
Salomon, G. (1993). Distributed cognitions. Cambridge: Cambridge University Press.
Sassenberg, K., & Karl-Andrew, W. (2008). Group-based self-regulation: the effects of regulatory focus. European Review of Social Psychology, 19, 126–164.
Soh, L., Khandaker, N., & Jiang, H. (2008). I-MINDS: a multiagent system for intelligent computer-supported collaborative learning and classroom management. Journal of Artificial Intelligence in Education, 18(2), 119–151.
Soller, A. (2001). Supporting social interaction in an intelligent collaborative learning system. International Journal of Artificial Intelligence in Education, 12(1), 40–62.
Soller, A., Martínez-Monés, A., Jermann, P., & Muehlenbrock, M. (2005). From mirroring to guiding: a review of state of the art technology for supporting collaborative learning. Journal of Artificial Intelligence in Education, 15(4), 261–290.
Spiro, R. J., Coulson, R. L., Feltovich, P. J., & Anderson, D. K. (1988). Cognitive flexibility theory: Advanced knowledge acquisition in ill-structured domains. In Proceedings of the Annual Conference of the Cognitive Science Society, 375–383.
Stahl, G., Koschmann, T., & Suthers, D. (2006). CSCL: An historical perspective. Cambridge handbook of the learning sciences (pp. 409–426). Cambridge: Cambridge University Press.
Strijbos, J. W., & Fischer, F. (2007). Methodological challenges for collaborative learning research. Learning & Instruction, 17(4), 389–393.
Strijbos, J. W., Martens, R. L., & Jochems, W. M. G. (2004). Designing for interaction: six steps to designing computer-supported group-based learning. Computers and Education, 42(4), 403–424.
Suthers, D. D., Dwyer, N., Medina, R., & Vatrapu, R. (2007). A framework for eclectic analysis of collaborative interaction. In Proceedings of the International Conference on Computer Supported Collaborative Learning (CSCL), 694–703.
Vygotsky, L. S. (1978). Mind in society: The development of the higher psychological processes. Cambridge: Harvard University Press. (re-publication).
Wessner, M., & Pfister, H. (2001). Group formation in computer-supported collaborative learning. In Proceedings of ACM CSCW, 24–31.
Acknowledgement
We would like to thank the reviewers and editors of the ijCSCL for their helpful comments and suggestions. We also would like to thank the Nippon Foundation, the Association of Nikkei & Japanese Abroad, JICA (Japan International Cooperation Agency), IBM Research and the Department of Knowledge Systems (MizLab) for their financial and technical support.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Isotani, S., Inaba, A., Ikeda, M. et al. An ontology engineering approach to the realization of theory-driven group formation. Computer Supported Learning 4, 445–478 (2009). https://doi.org/10.1007/s11412-009-9072-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11412-009-9072-x