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An Optimal Slack-Based Course Scheduling Algorithm for Personalised Study Plans

Published: 23 April 2020 Publication History

Abstract

Receiving a degree or learning certificate in a chosen field is often seen as the gateway to a bright future, and an essential building block when paving a way toward a successful career in one's chosen field. However, it is often the case that many undergraduate university students take longer than the expected number of years to attain their degree. This is often a result of poor planning, such as not taking enough courses per semester, or course scheduling conflicts. In this paper, we propose a solution to help mitigate causes associated with poor course planning as reasons why students do not graduate on time. We propose a slack-based algorithm, which uses the prerequisite relationship between courses, to provide a personalized study plan to help university students determine which courses to take each semester in order to achieve optimal graduation time. Each student's recommended study plan is based on the student's personal interests and preferences. This will ensure that the student not only fulfils the university's requirements for graduation in a timely manner, but they also take courses that are appropriately suited to their interests.

References

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U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS). "Undergraduate Retention and Graduation Rates", The Condition of Education 2019: 196--200.
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https://github.com/Lateilla/Slack-Based-Algorithm

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ICEIT 2020: Proceedings of the 2020 9th International Conference on Educational and Information Technology
February 2020
268 pages
ISBN:9781450375085
DOI:10.1145/3383923
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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  • University of Thessaly: University of Thessaly, Volos, Greece

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 April 2020

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Author Tags

  1. Course map
  2. Course scheduling
  3. Personalised study plans
  4. Slack-based scheduling
  5. Study planning

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