Developing Self-Regulated Learners Through an Intelligent Tutoring System

Intelligent tutoring systems have been developed to help students learn independently. However, students who are poor selfregulated learners often struggle to use these systems because they lack the skills necessary to learn independently. The field of psychology has extensively studied self-regulated learning and can provide strategies to improve learning, however few of these include the use of technology. The present proposal reviews three elements of self-regulated learning (motivational beliefs, helpseeking behavior, and meta-cognitive self-monitoring) that are essential to intelligent tutoring systems. Future research is suggested, which address each element in order to develop selfregulated learning strategies in students while they are engaged in learning mathematics within an intelligent tutoring system.