Abstract

This paper proposes an intelligent recommendation approach to facilitate personalized education and help students in planning their path to graduation. The goal is to identify a path that aligns with a student's interests and career goals and approaches optimality with respect to one or more criteria, such as time-to-graduation or credit hours taken. The approach is illustrated and verified through application to undergraduate curricula at the Missouri University of Science and Technology.

Department(s)

Electrical and Computer Engineering

Comments

National Science Foundation, Grant DUE-1742523

Keywords and Phrases

optimization; PERCEPOLIS; personalized education; recommendation

International Standard Serial Number (ISSN)

0730-3157

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2023 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Jan 2023

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