INTEGRATING COLLABORATION AND INTELLIGENT TUTORING DATA IN THE EVALUATION OF A RECIPROCAL PEER TUTORING ENVIRONMENT

Abstract

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.