IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v51y2021i6p409-421.html
   My bibliography  Save this article

Developing Optimal Student Plans of Study

Author

Listed:
  • R. Alan Bowman

    (Reh School of Business, Clarkson University Capital Region Campus, Schenectady, New York 12308)

Abstract

Advisors in a small graduate program needed to be able to help students with a wide variety of needs and preferences in terms of starting term, pace of study, program of study, and mode of course delivery to identify plans of study in a dynamic fashion and enable them to follow those plans. Course sections were limited and needed to serve multiple programs and all types of students in those programs. Last-second schedule changes due to overly large or small registration numbers were problematic. Special arrangements to allow students to graduate on time were frequent and costly and lowered academic quality. Analytical tools were developed to help with the planning and alleviate these issues. The tools and the overall approach should be of interest to educational institutions and programs that need to offer a wide variety of students extensive flexibility and choices within a highly constrained scheduling environment.

Suggested Citation

  • R. Alan Bowman, 2021. "Developing Optimal Student Plans of Study," Interfaces, INFORMS, vol. 51(6), pages 409-421, November.
  • Handle: RePEc:inm:orinte:v:51:y:2021:i:6:p:409-421
    DOI: 10.1287/inte.2021.1083
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2021.1083
    Download Restriction: no

    File URL: https://libkey.io/10.1287/inte.2021.1083?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Pongcharoen, P. & Promtet, W. & Yenradee, P. & Hicks, C., 2008. "Stochastic Optimisation Timetabling Tool for university course scheduling," International Journal of Production Economics, Elsevier, vol. 112(2), pages 903-918, April.
    2. Burke, Edmund Kieran & Petrovic, Sanja, 2002. "Recent research directions in automated timetabling," European Journal of Operational Research, Elsevier, vol. 140(2), pages 266-280, July.
    3. Vid Ogris & Tomaž Kristan & Andrej Škraba & Marko Urh & Davorin Kofjač, 2016. "iUrnik: Timetabling for Primary Educational Institutions in Slovenia," Interfaces, INFORMS, vol. 46(3), pages 231-244, April.
    4. Werner Junginger, 1986. "Timetabling in Germany---A Survey," Interfaces, INFORMS, vol. 16(4), pages 66-74, August.
    5. Janice K. Winch & Jack Yurkiewicz, 2014. "Case Article—Class Scheduling with Linear Programming," INFORMS Transactions on Education, INFORMS, vol. 15(1), pages 143-147, September.
    6. Jan Stallaert, 1997. "Automated Timetabling Improves Course Scheduling at UCLA," Interfaces, INFORMS, vol. 27(4), pages 67-81, August.
    7. Scott E. Sampson & James R. Freeland & Elliott N. Weiss, 1995. "Class Scheduling to Maximize Participant Satisfaction," Interfaces, INFORMS, vol. 25(3), pages 30-41, June.
    8. Ofer Strichman, 2017. "Near-Optimal Course Scheduling at the Technion," Interfaces, INFORMS, vol. 47(6), pages 537-554, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fabian Dunke & Stefan Nickel, 2023. "A matheuristic for customized multi-level multi-criteria university timetabling," Annals of Operations Research, Springer, vol. 328(2), pages 1313-1348, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Amy B. Gore & Mary E. Kurz & Matthew J. Saltzman & Blake Splitter & William C. Bridges & Neil J. Calkin, 2022. "Clemson University’s Rotational Attendance Plan During COVID-19," Interfaces, INFORMS, vol. 52(6), pages 553-567, November.
    2. Song, Kwonsik & Kim, Sooyoung & Park, Moonseo & Lee, Hyun-Soo, 2017. "Energy efficiency-based course timetabling for university buildings," Energy, Elsevier, vol. 139(C), pages 394-405.
    3. Vermuyten, Hendrik & Lemmens, Stef & Marques, Inês & Beliën, Jeroen, 2016. "Developing compact course timetables with optimized student flows," European Journal of Operational Research, Elsevier, vol. 251(2), pages 651-661.
    4. Leo Lopes & Meredith Aronson & Gary Carstensen & Cole Smith, 2008. "Optimization Support for Senior Design Project Assignments," Interfaces, INFORMS, vol. 38(6), pages 448-464, December.
    5. Thepphakorn, Thatchai & Pongcharoen, Pupong & Hicks, Chris, 2014. "An ant colony based timetabling tool," International Journal of Production Economics, Elsevier, vol. 149(C), pages 131-144.
    6. Jaime Miranda, 2010. "eClasSkeduler: A Course Scheduling System for the Executive Education Unit at the Universidad de Chile," Interfaces, INFORMS, vol. 40(3), pages 196-207, June.
    7. Biniyam Asmare Kassa, 2015. "Implementing a Class-Scheduling System at the College of Business and Economics of Bahir Dar University, Ethiopia," Interfaces, INFORMS, vol. 45(3), pages 203-215, June.
    8. Boronico, Jess, 2000. "Quantitative modeling and technology driven departmental course scheduling," Omega, Elsevier, vol. 28(3), pages 327-346, June.
    9. Timothy R. Hinkin & Gary M. Thompson, 2002. "SchedulExpert: Scheduling Courses in the Cornell University School of Hotel Administration," Interfaces, INFORMS, vol. 32(6), pages 45-57, December.
    10. Fabian Dunke & Stefan Nickel, 2023. "A matheuristic for customized multi-level multi-criteria university timetabling," Annals of Operations Research, Springer, vol. 328(2), pages 1313-1348, September.
    11. Pillay, N. & Banzhaf, W., 2009. "A study of heuristic combinations for hyper-heuristic systems for the uncapacitated examination timetabling problem," European Journal of Operational Research, Elsevier, vol. 197(2), pages 482-491, September.
    12. Esmaeilbeigi, Rasul & Mak-Hau, Vicky & Yearwood, John & Nguyen, Vivian, 2022. "The multiphase course timetabling problem," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1098-1119.
    13. Schirmer, Andreas & Potzhar, Kathrin, 2001. "Professional course scheduling in airline transport pilot training: A case from Lufthansa flight training," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 539, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    14. Ramiro Saltos & Sebastián Maldonado, 2023. "Case Article—School Timetabling Problem: A Scheduling Problem for High-School Institutions," INFORMS Transactions on Education, INFORMS, vol. 24(1), pages 95-99, September.
    15. Andrea Bettinelli & Valentina Cacchiani & Roberto Roberti & Paolo Toth, 2015. "An overview of curriculum-based course timetabling," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 313-349, July.
    16. Raphael Medeiros Alves & Francisco Cunha & Anand Subramanian & Alisson V. Brito, 2022. "Minimizing energy consumption in a real-life classroom assignment problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1149-1175, December.
    17. Gerhard Post & Samad Ahmadi & Sophia Daskalaki & Jeffrey Kingston & Jari Kyngas & Cimmo Nurmi & David Ranson, 2012. "An XML format for benchmarks in High School Timetabling," Annals of Operations Research, Springer, vol. 194(1), pages 385-397, April.
    18. Massimiliano Caramia & Stefano Giordani, 2020. "Curriculum-Based Course Timetabling with Student Flow, Soft Constraints, and Smoothing Objectives: an Application to a Real Case Study," SN Operations Research Forum, Springer, vol. 1(2), pages 1-21, June.
    19. Mutsunori Banbara & Katsumi Inoue & Benjamin Kaufmann & Tenda Okimoto & Torsten Schaub & Takehide Soh & Naoyuki Tamura & Philipp Wanko, 2019. "$${\varvec{teaspoon}}$$ teaspoon : solving the curriculum-based course timetabling problems with answer set programming," Annals of Operations Research, Springer, vol. 275(1), pages 3-37, April.
    20. P Lara-Velázquez & R López-Bracho & J Ramírez-Rodríguez & J Yáñez, 2011. "A model for timetabling problems with period spread constraints," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 217-222, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orinte:v:51:y:2021:i:6:p:409-421. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.