Exploring Relationships Between Student Online Usage Patterns and Learning Outcomes in Developmental Mathematics Courses

• In Event: Poster Session 4
  In Poster Session: Quantitative Studies of Data Use

Abstract

This paper explores relationships between student online activities as recorded by a learning management system (LMS) and their learning outcomes in online developmental mathematics courses. In particular, we apply two learning analytics techniques, prediction, and a form of visual data analytics called a clustergram, to examine the online activity data of 300 students collected over five semesters. The results reveal that students’ consistent and ongoing views of learning materials as well as monitoring their performance have positive impacts on learning outcomes. We also examined the online usage patterns in how students accessed topics in developmental mathematics. The results showed that the students tended to view easier topics, while skipping later, more difficult topics such as solving equations and inequalities.

Authors

• Ji-Eun Lee, Utah State University

• Mimi M. Recker, Utah State University