Computer Science Ph.D. student Jihyun Park is the lead author on a paper that recently won the best paper award at the 11th International Conference on Educational Data Mining Conference (EDM 2018) in Buffalo, N.Y. The paper, “Understanding Student Procrastination via Mixture Models,” proposes a new approach based on statistical machine learning techniques that can extract and quantify patterns of procrastination observed from student clickstream data in online college courses. In particular, persistent procrastination over the duration of a course was found to be strongly predictive of poorer student outcomes, providing strong evidence that time management is critical for success in online courses.
This work is supported by the National Science Foundation as part of the project Investigating Virtual Learning Environments, a five-year collaboration between the UCI School of Education and the Donald Bren School of Information and Computer Sciences (ICS). The paper was co-authored with Park’s adviser, Chancellor’s Professor of Computer Science Padhraic Smyth, and graduate student Renzhe Yu, postdoctoral scholar Fernando Rodriguez, and professors Rachel Baker and Mark Warschauer (all in the School of Education).
The Educational Data Mining Conference is one of the leading international conferences on the development of computational methods for analyzing education data, with 145 submissions this year, of which 23 (16 percent) were accepted for presentation.