Course Enrollment Recommender System

Over the past decades, higher education has evolved considerably to serve students better and help with their academic success. This includes structural reorganization, adopting new instructional technologies, updating curriculum, etc. Using the Computer Science Department at NEIU as an example, due to the nature of this discipline, the curriculum of the undergraduate and graduate programs is continuously updated to align with the state-of-art technologies in the field. With more courses proposed and prerequisite restrictions changed, students can often feel overwhelmed by the abundance of information.

As part of the 2021 NEIU SCSE Summer research program, this research aims to design and build a prototype course enrollment recommender systems for the NEIU CS Department. The system will benefit both students and their academic advisors. Students will be able to see their personalized recommendations and advisors will be able to reference these recommendations when addressing student questions.

Research Team

  • Past Members

    • Longin Cui (Co-Mentor), Ph.D. candidate in Computer Science, University of Kentucky, May 2021 – August 2021.
    • Muhammad Bangash, undergraduate student in Computer Science, Northeastern Illinois University, May 2021 – August 2021.
    • Mohammad Bilal, undergraduate student in Computer Science, Northeastern Illinois University, May 2021 – August 2021.
    • Wali Chaudhry, undergraduate student in Computer Science, Northeastern Illinois University, May 2021 – August 2021.
    • Luis Rosales, undergraduate student in Computer Science, Northeastern Illinois University, May 2021 – August 2021.

Publications

  • Xiwei Wang, Longyin Cui, Muhammad Bangash, Mohammad Bilal, Luis Rosales and Wali Chaudhry. A Machine Learning-based Course Enrollment Recommender System. Accepted by The 14th International Conference on Computer Supported Education, February, 2022.

Talks

  • Research Presentations

    • A Machine Learning-based Course Enrollment Recommender System. 14th International Conference on Computer Supported Education. April, 2022.

  • Student Presentations

    • Wali Chaudhry, Luis Rosales, Muhammad Bangash, Mohammad Bilal, Longyin Cui, and Xiwei Wang. A Machine Learning-Based Course Enrollment Recommender System. 2021 SACNAS National Diversity in STEM Conference, October 2021.
    • Wali Chaudhry, Luis Rosales, Muhammad Bangash, Mohammad Bilal, Longyin Cui, and Xiwei Wang. A Machine Learning-Based Course Enrollment Recommender System. 13th SCSE Student Research Symposium, Northeastern Illinois University, October 2021.