In higher education, a widely used online instructional method to enhance learners\u27 engagement, presence, and achievement is asynchronous online discussions. Yet studies demonstrating their effectiveness, especially in high-failure rate courses like mathematics, remain elusive. The objectives of the study are to investigate 1) what online discussion strategies are associated with positive student performance, 2) to what extent do different structures designed into online discussions impact the kinds of learner interactions, and 3) what types of learner interactions are associated with positive student performance. In particular, by applying a set of text mining and data mining techniques (e.g., Classification and Regression Tree), this study analyzes clickstream and textual data automatically collected by a Learning Management System (LMS) for five consecutive years at a university located in the western U.S. The results of study will inform instructors and instructional designers how to design the better online mathematics courses
