Year: 2006
Type: article
Abstract: Past research on feedback in computer-based learning environments 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 discovery 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.
Authors: Gautam Biswas, Jason Tan, Daniel L. Schwartz
Institutions: Vanderbilt University, Stanford University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W2623534379