Creating student groups with similar characteristics: A heuristic approach
AbstractThis paper describes an algorithm for classifying elements with binary valued attributes so that the classes are similar. The problem chosen for discussing is that of allocating students to groups within an educational setting. Individual students are described by a set of binary-valued attributes. The objective of the algorithm is to create working groups which are similar to each other in terms of their mix of student attributes. The algorithm uses an information theory measure. The paper also compares the performance of the algorithm to a goal programming formulation of the problem.
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Bibliographic InfoArticle provided by Elsevier in its journal Omega.
Volume (Year): 23 (1995)
Issue (Month): 3 (June)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description
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- Bhadury, Joyendu & Mighty, E. Joy & Damar, Hario, 2000. "Maximizing workforce diversity in project teams: a network flow approach," Omega, Elsevier, vol. 28(2), pages 143-153, April.
- Saber, Hussein M. & Ghosh, Jay B., 2001. "Assigning students to academic majors," Omega, Elsevier, vol. 29(6), pages 513-523, December.
- O'Brien, F. A. & Mingers, J., 1997. "A heuristic algorithm for the equitable partitioning problem," Omega, Elsevier, vol. 25(2), pages 215-223, April.
- Weitz, R. R. & Lakshminarayanan, S., 1997. "An empirical comparison of heuristic and graph theoretic methods for creating maximally diverse groups, VLSI design, and exam scheduling," Omega, Elsevier, vol. 25(4), pages 473-482, August.
- Mustafa, A. & Goh, M., 1996. "Multi-criterion models for higher education administration," Omega, Elsevier, vol. 24(2), pages 167-178, April.
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