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The University of Toronto’s Rotman School of Management Uses Management Science to Create MBA Study Groups

Author

Listed:
  • Dmitry Krass

    (Joseph L. Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario, Canada M5S 3E6)

  • Anton Ovchinnikov

    (Joseph L. Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario, Canada M5S 3E6)

Abstract

Business schools look for ways to teach MBA graduates effective group work skills, generally through group-based assignments and projects. However, if not monitored carefully, group work can undermine the learning process; group composition is important. The Rotman School has developed a multiple-well-balanced-study-groups strategy to ensure that students are assigned to several balanced and nonoverlapping groups, which are used in different courses. We formulated the group-creation problem as a mathematical optimization model and implemented it in a user-friendly software package that Rotman MBA office administrators use to create student groups. Switching to computer-generated groups produced better balanced groups, saved much manual effort, and increased levels of satisfaction among students, faculty, and the MBA office personnel.

Suggested Citation

  • Dmitry Krass & Anton Ovchinnikov, 2006. "The University of Toronto’s Rotman School of Management Uses Management Science to Create MBA Study Groups," Interfaces, INFORMS, vol. 36(2), pages 126-137, April.
    • Handle: RePEc:inm:orinte:v:36:y:2006:i:2:p:126-137
    DOI: 10.1287/inte.1050.0194
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    References listed on IDEAS

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    1. K R Baker & S G Powell, 2002. "Methods for assigning students to groups: a study of alternative objective functions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(4), pages 397-404, April.
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    Citations

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    Cited by:

    1. Arne Schulz, 2023. "The balanced maximally diverse grouping problem with integer attribute values," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-27, July.
    2. Stephen Mahar & Wayne Winston & P. Daniel Wright, 2013. "Eli Lilly and Company Uses Integer Programming to Form Volunteer Teams in Impoverished Countries," Interfaces, INFORMS, vol. 43(3), pages 268-284, May-June.
    3. Theresa M. Roeder & Robert M. Saltzman, 2014. "Schedule-Based Group Assignment Using Constraint Programming," INFORMS Transactions on Education, INFORMS, vol. 14(2), pages 63-72, February.
    4. Anton Ovchinnikov & Joseph Milner, 2008. "Spreadsheet Model Helps to Assign Medical Residents at the University of Vermont's College of Medicine," Interfaces, INFORMS, vol. 38(4), pages 311-323, August.
    5. Krass, Dmitry & Ovchinnikov, Anton, 2010. "Constrained group balancing: Why does it work," European Journal of Operational Research, Elsevier, vol. 206(1), pages 144-154, October.
    6. Nahid Rezaeinia & Julio César Góez & Mario Guajardo, 2022. "Efficiency and fairness criteria in the assignment of students to projects," Annals of Operations Research, Springer, vol. 319(2), pages 1717-1735, December.
    7. Arne Schulz, 2022. "A new mixed-integer programming formulation for the maximally diverse grouping problem with attribute values," Annals of Operations Research, Springer, vol. 318(1), pages 501-530, November.
    8. Fernández, Elena & Kalcsics, Jörg & Nickel, Stefan, 2013. "The maximum dispersion problem," Omega, Elsevier, vol. 41(4), pages 721-730.
    9. Binyamin Krauss & Jon Lee & Daniel Newman, 2013. "Optimizing the Assignment of Students to Classes in an Elementary School," INFORMS Transactions on Education, INFORMS, vol. 14(1), pages 39-44, September.
    10. Andrew Bowers & Melissa R. Bowers & Nana Bryan & Paolo Letizia & Spencer Murphy, 2023. "Forming Student Teams to Incorporate Soft Skills and Commonality of Schedule," Interfaces, INFORMS, vol. 53(2), pages 111-127, March.

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