Download Full Text (1.8 MB)
Dr. Jin Soung Yoo
Department of Computer Science
Indiana University – Purdue University Fort Wayne
Most higher education institutions have their student management system which can produce valuable information. However the students’ data is huge and complicated, and it is hard to forecast students’ academic progress. Data mining is a process of extracting and identifying useful information and subsequent knowledge from large databases using statistical and computational analysis techniques. A new research community, educational data mining is recently growing which is intersection of data mining and pedagogy. This work presents the discovery of course sequence patterns from students’ enrollment data. The data was mined using a sequential pattern mining method which was originally developed for analyzing phone call patterns and customer purchase sequences. This work shows how the sequential pattern mining technique is used for the educational data mining. A set of experimental data was prepared in order to find interesting course sequential patterns in the enrollment database. The result showed that the proposed analysis methodology is a useful tool for understanding students’ progression and status.
Computer Sciences | Physical Sciences and Mathematics
Woo, Yei-Sol, "Discovery of Course Enrollment Patterns Using Sequential Data Mining" (2014). 2014 IPFW Student Research and Creative Endeavor Symposium. 6.