Incorporating Student Response Time and Tutor Instructional Interventions into Student Modeling

Chen Lin, Shitian Shen, Min Chi

Abstract: Bayesian Knowledge Tracing (BKT) is one of the most widely adopted student-modeling methods. It uses performance (incorrect,correct) to infer student knowledge state (unlearned, learned). However, performance can be noisy and thus we explored another type of observations -- student response time. Furthermore, we proposed Intervention Bayesian Knowledge Tracing (Intervention-BKT) which can incorporate multiple types of instructional interventions into the conventional BKT model. Our results show that for next-step performance predictions, Intervention-BKT is more effective than BKT; whereas to predict students' post-test scores, including student response time would yield better result than using performance alone.