Student affect has been found to correlate with short- and long-term learning outcomes, including college attendance as well as interest and involvement in Science, Technology, Engineering, and Mathematics (STEM) careers. However, there still remain significant questions about the processes by which affect shifts and develops during the learning…

There is increasing evidence that fine-grained aspects of student performance and interaction within educational software are predictive of long-term learning. Machine learning models have been used to provide assessments of affect, behavior, and cognition based on analyses of system log data, estimating the probability of a student's particular…

This dissertation research focuses on assessing student behavior, academic emotions, and knowledge from a middle school online learning environment, and analyzing their potential effects on decisions about going to college. Using students' longitudinal data ranging from their middle school, to high school, to postsecondary years, I leverage…