Supporting Student Self-regulation in Unsupervised Learning Environments

Abstract

Technology has made it convenient for students today to learn outside of the classroom. However, learning in this kind of setting introduces challenges such as proper time management, maintaining motivation and avoiding distractions. This research investigates how student learning progresses in this unsupervised learning environment and proposes an automated support mechanism that promotes self-regulation to help students learn. The proposed system is not bound to any domain and its methodology supports learning in naturalistic settings. Results gathered from students’ use of a system prototype confirmed the problems students encounter when learning in this environment and their need for support. It also showed that helping students self-regulate made them aware of their learning behavior and helped them identify ways to improve their learning efficiency.