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.
N. Dobbins et al., "Personalizing Student Graduation Paths Using Expressed Student Interests," Proceedings - International Computer Software and Applications Conference, pp. 142 - 151, Institute of Electrical and Electronics Engineers, Jan 2023.
The definitive version is available at https://doi.org/10.1109/COMPSAC57700.2023.00027
Electrical and Computer Engineering
Keywords and Phrases
optimization; PERCEPOLIS; personalized education; recommendation
International Standard Serial Number (ISSN)
Article - Conference proceedings
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01 Jan 2023