A Multi-Stage Approach to Personalized Course Selection and Scheduling


Recommender systems that utilize pertinent and available contextual information are applicable to and useful in a broad range of domains. This paper utilizes context-aware recommendation to facilitate personalized education and assist students in selecting courses (or in non-traditional curricula, learning artifacts) that meet curricular requirements, leverage their skills and background, and are relevant to their interests. The research contribution described in this paper is a methodology that generates a schedule of courses (and associated course content) that takes into consideration a student's profile, while meeting curricular and prerequisite requirements and aiming to reduce attributes such as cost and time-to-degree. The optimization problem - multiple integer linear programming problems and a single scheduling problem - is solved in stages using a known linear solver as well as graph-based heuristics. The efficacy of the algorithm is demonstrated through a case study.

Meeting Name

IEEE International Conference on Information Reuse and Integration (2017: Aug. 4-6, San Diego, CA)


Computer Science

Second Department

Electrical and Computer Engineering

Research Center/Lab(s)

Intelligent Systems Center

Keywords and Phrases

Curricula; Graphic Methods; Information Use; Optimization; Scheduling; Students; Context-Aware Recommendations; Contextual Information; Integer Linear Programming; Multistage Approach; Optimization Problems; PERCEPOLIS; Personalized Course; Personalized Learning; Integer Programming; Context-Aware Recommendation; Ontologies; Recommender Systems; Computational Modeling; Context Modeling; Object Oriented Modeling; Education Administrative Data Processing; Educational Courses; Graph Theory; Linear Programming; Ubiquitous Computing

International Standard Book Number (ISBN)

978-1538615621; 978-1538615638

Document Type

Article - Conference proceedings

Document Version


File Type





© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Aug 2017