Using Learner Engagement Patterns to Predict MicroMasters Exam Success (Poster 33)

• In Event: AERA Poster Session Wednesday 2:30 p.m.
  In Poster Session: Online Teaching and Learning SIG Poster Session

Abstract

This study used a Long Short-Term Memory (LSTM) model and investigated the factors that influence success in the final comprehensive exam for a MicroMasters program. By analyzing data from 1603 learners who passed four prerequisite MOOCs, we identified key engagement activities in two introductory courses that correlate with higher exam completion rates. The results emphasize the importance of student engagement, forum participation, and interaction with course materials for exam success. These insights can help improve completion rates for the MicroMasters program which will allow more learners to apply these credentials towards their career and educational goals.

Authors

• Rob Moore, University of Florida

• Jinnie Shin, University of Florida

• Woorin Hwang, University of Florida