Abstract
One of the most important problems faced by teachers is grouping students into proper teams. The task is complex, as many technical and interpersonal factors could affect team dynamics, with no clear indication of which factors may be more relevant. Not only the problem is conceptually complex, but its computational complexity is also exponential, which precludes teachers from optimally applying strategies by hand. The tool presented in this paper aims to cover both gaps: first, it provides a range of grouping strategies for testing, and second, it provides artificial intelligence mechanisms that in practice tone down the computational cost of the problem.
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Alberola, J.M., del Val, E., Sanchez-Anguix, V., Julian, V.: Simulating a collective intelligence approach to student team formation. In: Hybrid Artificial Intelligent Systems, pp. 161–170. Springer (2013)
Amato, C.H., Amato, L.H.: Enhancing student team effectiveness: Application of myers-briggs personality assessment in business courses. Journal of Marketing Education 27(1), 41–51 (2005)
Behfar, K., Friedman, R., Brett, J.M.: The team negotiation challenge: Defining and managing the internal challenges of negotiating teams. In: IACM 21st Annual Conference Paper (2008)
Dunne, E., Rawlins, M.: Bridging the gap between industry and higher education: Training academics to promote student teamwork. Innovations in Education and Teaching International 37(4), 361–371 (2000)
Harackiewicz, J.M., Barron, K.E., Tauer, J.M., Carter, S.M., Elliot, A.J.: Short-term and long-term consequences of achievement goals: Predicting interest and performance over time. Journal of Educational Psychology 92(2), 316 (2000)
Kerr, N.L., Tindale, R.S.: Group performance and decision making. Annu. Rev. Psychol. 55, 623–655 (2004)
Meredith Belbin, R.: Management teams: Why they succeed or fail. Human Resource Management International Digest 19(3) (2011)
Myers, I.B.: The myers-briggs type indicator: Manual (1962)
Ohta, N., Conitzer, V., Ichimura, R., Sakurai, Y., Iwasaki, A., Yokoo, M.: Coalition structure generation utilizing compact characteristic function representations. In: Principles and Practice of Constraint Programming - CP 2009, vol. 5732, pp. 623–638 (2009)
Omar, M., Syed-Abdullah, S.-L., Hussin, N.M.: Analyzing personality types to predict team performance. In: Proceedings of the 2010 International Conference on Science and Social Research (CSSR), pp. 624–628 (2010)
Ounnas, A., Davis, H.C., Millard, D.E.: A framework for semantic group formation in education. Journal of Educational Technology & Society 12(4), 43–55 (2009)
Pieterse, V., Kourie, D.G., Sonnekus, I.P.: Software engineering team diversity and performance. In: Proc. of SAICSIT 2006, pp. 180–186. South African Institute for Computer Scientists and Information Technologists (2006)
Ratcheva, V.: Integrating diverse knowledge through boundary spanning processes-the case of multidisciplinary project teams. International Journal of Project Management 27(3), 206–215 (2009)
Sancho-Thomas, P., Fuentes-Fernández, R., Fernández-Manjón, B.: Learning teamwork skills in university programming courses. Computers & Education 53(2), 517–531 (2009)
Tarricone, P., Luca, J.: Employees, teamwork and social interdependence-a formula for successful business? Team Performance Management: An International Journal 8(3/4), 54–59 (2002)
Val, E.D., Alberola, J.M., Sánchez-Anguix, V., Palomares, A., Teruel, M.D.: A team formation tool for educational environments. In: Trends in Prac. Apps. of Heterogeneous Multi-Agent Systems, vol. 293, pp. 173–181 (2014)
van de Water, H., Ahaus, K., Rozier, R.: Team roles, team balance and performance. Journal of Management Development 27(5), 499–512 (2008)
Varvel, T., Adams, S.G., Pridie, S.J., Ruiz, B.C.: Ulloa. Team effectiveness and individual myers-briggs personality dimensions. Journal of Management in Engineering 20(4), 141–146 (2004)
Yannibelli, V., Amandi, A.: A deterministic crowding evolutionary algorithm to form learning teams in a collaborative learning context. Expert Systems with Applications 39(10), 8584–8592 (2012)
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Alberola, J.M., del Val, E., Sanchez-Anguix, V., Julián, V. (2016). A General Framework for Testing Different Student Team Formation Strategies. In: Caporuscio, M., De la Prieta, F., Di Mascio, T., Gennari, R., Gutiérrez Rodríguez, J., Vittorini, P. (eds) Methodologies and Intelligent Systems for Technology Enhanced Learning . Advances in Intelligent Systems and Computing, vol 478. Springer, Cham. https://doi.org/10.1007/978-3-319-40165-2_3
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DOI: https://doi.org/10.1007/978-3-319-40165-2_3
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