Sidekick Retrospect: A Self-regulation Tool for Unsupervised Learning Environments

Abstract

Self-regulation is an important skill for students to possess. It allows them to learn more effectively and it has been shown to cause better learning gains. Self-regulation is not an easy task especially for poor learners. This is the motivation behind researches that use computer-based learning environments to promote self-regulation through embedded tools that help students keep track of their self-regulation processes. Although these researches have shown promising results, they focus on self-regulation processes inside controlled learning environments. Not much research has been done on learning in unsupervised learning environments where students learn on their own, introducing additional challenges. In this research, we developed software to help students perform self-regulation in this setting. Results showed that the software was able to help students set goals, monitor their activities and evaluate their learning behavior. Students who used the software reported that it made them more aware of the activities they did when they were learning and it also helped them identify what to do in order to improve their learning behavior in succeeding learning sessions.