Publications

Below is a list of published papers, formatted by year.

(2023)

Gary M. Weiss, Luisa A. L. Rosa, Hyun Jeong and Daniel D. Leeds. An Analysis of Grading Patterns in Undergraduate University Courses. Proceedings of the 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC), IEEE, Torino, Italy, June 26-30, 310-315 (official version).

(2022)

Gary M. Weiss, Erik Brown, Michael Riad-Zaky, Ruby Iannone, and Daniel D. Leeds. Assessing Instructor Effectiveness Based on Future Student Performance. Proceedings of The 15th International Conference on Educational Data Mining (EDM22), International Educational Data Mining Society, Durham, UK, July 24-27.

Gary M. Weiss, Joseph Denham, and Daniel D. Leeds. The Impact of Semester Gaps on Student Grades. Proceedings of The 15th International Conference on Educational Data Mining (EDM22), International Educational Data Mining Society, Durham, UK, July 24-27.

Daniel D. Leeds, Cody Chen, Yijun Zhao, Fiza Metla, James Guest, and Gary M. Weiss. Generalized Sequential Pattern Mining of Undergraduate Courses. Proceedings of The 15th International Conference on Educational Data Mining (EDM22), International Educational Data Mining Society, Durham, UK, July 24-27.

(2021)

Gary Weiss, Nam Nguyen, Karla Dominguez and Daniel Leeds. Identifying Hubs in Undergraduate Course Networks Based on Scaled Co-Enrollments. Proceedings of The 14th International Conference on Educational Data Mining (EDM21), International Educational Data Mining Society, Paris France, June 29-July 2, 809-813. [video and poster]

Tess Gutenbrunner, Daniel D. Leeds, Spencer Ross, Michael Riad-Zaky, and Gary M. Weiss.
Measuring the Academic Impact of Course Sequencing using Student Grade Data
. Proceedings of The 14th International Conference on Educational Data Mining (EDM21), International Educational Data Mining Society, Paris France, June 29-July 2, 799-803. [video and poster]

Daniel Leeds, Tianyi Zhang and Gary Weiss. Mining Course Groupings using Academic Performance. Proceedings of The 14th International Conference on Educational Data Mining (EDM21), International Educational Data Mining Society, Paris France, June 29-July 2, 804-808. [video and poster]

Weiss, G. M., Nguyen, N., Dominguez, K., & Leeds, D. D. Identifying Hubs in Undergraduate Course Networks Based on Scaled Co-Enrollments: Extended Version. arXiv preprint arXiv:2104.14500.

Faiza Khan, Gary M. Weiss, and Daniel D. Leeds. Predicting the Academic Performance of Undergraduate Computer Science Students Using Data Mining. In: Arabnia H.R., Deligiannidis L., Tinetti F.G., Tran QN. (eds) Advances in Software Engineering, Education, and e-Learning. Transactions on Computational Science and Computational Intelligence. Springer, Cham, 303-317.

(2020)

Samuel A. Stein, Gary M. Weiss, Yiwen Chen, and Daniel D. Leeds. A College Major Recommendation System. Proceedings of the Fourteenth ACM Conference on Recommender Systems (RECSYS 20), 640-644, September 2020.

Yijun Zhao, Qiangwen Xu, Ming Chen, and Gary M. Weiss. Predicting Student Performance in a Master of Data Science Program using Admissions Data. Proceedings of the 13th International Conference on Educational Data Mining (EDM 2020), 325-333. [video]