Feedback for metacognitive support in learning by teaching environments

Abstract

Past research on feedback in computer-based learning envi-ronments has shown that corrective feedback helps immediate learning, whereas guided and metacognitive feedback help in gaining deep understanding and developing the ability to transfer knowledge. Feedback becomes important in discov-ery learning environments, where novice students are often overwhelmed by the cognitive load associated with learning and organizing new knowledge while monitoring their own learning progress. We focus on feedback mechanisms in teachable agent systems to help improve students ’ abilities to monitor their agent’s knowledge, and, in the process their own learning and understanding. Our studies demonstrate the effectiveness of guided metacognitive feedback in preparing students for future learning