Algorithmic Support for Personalized Course Selection and Scheduling

Abstract

The work presented in this paper demonstrates the use of context-aware recommendation to facilitate personalized education, by assisting students in selecting courses and course content and mapping a trajectory to graduation. The recommendation algorithm considers a student's profile and their program's curricular requirements in generating a schedule of courses, while aiming to reduce attributes such as cost and time-to-degree. The resulting optimization problem is solved using integer linear programming and graph-based heuristics. The course selection algorithm has been developed for the Pervasive Cyberinfrastructure for Personalized eLearning and Instructional Support (PERCEPOLIS), which can assist or supplement the degree planning actions of an academic advisor, with assurance that recommended selections are always valid.

Meeting Name

IEEE 44th Annual Computers, Software, and Applications Conference, COMPSAC (2020: Jul. 13-17, Madrid, Spain)

Department(s)

Electrical and Computer Engineering

Second Department

Computer Science

Keywords and Phrases

Context-Aware Recommendation; Integer Linear Programming; PERCEPOLIS; Personalized Education

International Standard Book Number (ISBN)

978-172817303-0

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2020 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

22 Sep 2020

Link to Full Text

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