A partitioning technique for defining instructional groups
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A technique is presented for partitioning N students into K groups of fixed sizes using a given measure of proximity for all student pairs. The measure of proximity is typically calculated from a set of variables, such as completed curriculum units or learning style, and constitutes the data needed for a criterion of partition “fit”. This latter index is explicitly defined by the sum of within-group proximities and when used in conjunction with the optimization procedure discussed, homogeneous groups can be obtained that satisfy externally imposed size requirements. Finally, a simple generalization is suggested for the related task of grouping students to meet upper limit size constraints only.
- Arabie, P. and Boorman, S. A. (1978). “Constructing block models: How and why,” Journal of Mathematical Psychology, 17: 21–63.
- Armour, G. G. and Buffa, E. S. (1963). “A heuristic algorithm and simulation approach to relative location of facilities,” Management Sciences, 9: 294–309.
- Baker, F. B., Hubert, L. J. and Schultz, J. V. (1977). Quadratic Assignment Program, Laboratory of Experimental Design, University of Wisconsin, Madison.
- Belt, S. L. and Spuck, D. W. (1974). “Computer applications in individually guided education. A computer-based system for instructional management (WIS/SIM),” Working Paper No. 125. Wisconsin Research and Development Center, p. 129.
- Brennan, R. L. and Light, R. J. (1974). “Measuring agreement when two observers classify people into categories not defined in advance,” British Journal of Mathematical and Statistical Psychology, 27: 154–163.
- Glaser, R. H. A. (1959). “A quasi-simplex method for designing suboptimum packages of electronic building blocks (Burroughs 220),” in: Proceedings of 1959 Computer Applications Symposium, Armour Research Foundation, Illinois Institute of Technology, Chicago.
- Hubert, L. (1977). “Nominal scale response agreement as a generalized correlation,” British Journal of Mathematical and Statistical Psychology, 30: 98–103.
- Hubert, L. J. and Schultz, J. V. (1976). “Quadratic assignment as a general data analysis strategy,” British Journal of Mathematical and Statistical Psychology, 29: 190–241.
- Katz, L. (1947). “On the matrix analysis of sociometric data,” Sociometry, 10: 233–241.
- Lawrence, B. F. (1976). “Numerical procedures in the optional grouping of students for instructional purposes,” unpublished Ph.D. thesis, University of Wisconsin, Madison.
- Nicholson, T. A. J. (1971). “A method for optimizing permutation problems and its industrial applications,” in: P. J. A., Welsh (ed.) Combinatorial Mathematics and its Applications. New York: Academic Press.
- Rao, C. R. (1952). Advanced Statistical Methods in Biometric Research, New York: Wiley.
- Rodgers, G. and Linden, J. D. (1973). “Use of multiple discriminant function analysis in the evaluation of three multivariate grouping techniques,” Educational and Psychological Measurement, 33: 787–802.
- Talmage, H. E. (ed.) (1975). Systems of Individualized Education. Berkeley: McCutchon.
- weisgerber, R. A. (ed.) (1971). Developmental Efforts in Individualized Learning. Itasca, Ill.: Peacock.
- Witchita Public Schools. (1975). Administration of the CITE Learning Styles Instrument. Mundoch Teacher Center, Witchita.
- Yates, A. (1966). Grouping In Education. New York: Wiley.
- A partitioning technique for defining instructional groups
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