INTEGRATING COLLABORATION AND INTELLIGENT TUTORING DATA IN THE EVALUATION OF A RECIPROCAL PEER TUTORING ENVIRONMENT
Erin Walker, Nikol Rummel, Kenneth R. Koedinger · Research and Practice in Technology Enhanced Learning · 2022
Intelligent tutoring systems have been successful at increasing student mathematics learning, but may be further improved with the addition of collaborative activities. We have extended the Cognitive Tutor Algebra, a successful intelligent tutoring system for individual learning, with a reciprocal peer tutoring activity designed to increase concep- tual learning. While using our peer tutoring environment, students take on tutor and tutee roles, and engage in both problem-solving actions and dialogue. In a classroom study, we randomly assigned 62 participants to three conditions (adaptive assistance to peer tutoring, fixed assistance to peer tutoring, and individual learning). All condi- tions yielded significant learning gains, but there were no differences between conditions in final outcomes. There were significant process differences, however. We assessed stu- dent interaction using problem-solving information logged by the intelligent tutoring system and collaborative dialogue captured in a chat window. Our analysis integrated these multiple data sources in order to better understand how collaborative dialogue and problem-solving actions might lead to conceptual learning. This rich data sheds light on how students benefitted from the reciprocal peer tutoring activity: Peer tutors learned when they reflected on tutee problem-solving actions, and tutees learned when the tutor’s help was responsive to those actions.