Abstract

The Web allows self-regulated learning through interaction with large amounts of learning resources. While enjoying the flexibility of learning, learners may suffer from cognitive overload and conceptual and navigational disorientation when faced with various information resources under disparate topics and complex knowledge structures. This study proposed a knowledge visualization (KV) approach to this problem in an online course. The investigation involved the design, development, and evaluation of an enhanced learning system for the course using the proposed approach. The focus was on visualization of domain knowledge structure and integrating the structure with curriculum design, learning resources, learning assessment, intellectual process, and social learning. Survey and interviews with students demonstrated high user satisfaction and acceptance with the developed system and its functions for KV. These findings lay the foundation for further exploration with the system to determine its impact on reducing cognitive load and improving the learning process. (Contains 11 figures and 3 tables.)

Citation

Wang, M., Peng, J., Cheng, B., Zhou, H. & Liu, J. (2011). Knowledge Visualization for Self-Regulated Learning. Journal of Educational Technology & Society, 14(3), 28-42. Retrieved August 6, 2024 from https://www.learntechlib.org/p/75149/.

This record was imported from ERIC on April 19, 2013. [Original Record]

ERIC is sponsored by the Institute of Education Sciences (IES) of the U.S. Department of Education.

Copyright for this record is held by the content creator. For more details see ERIC's copyright policy.

Keywords

• College Seniors
• computer science education
• electronic learning
• Foreign Countries
• Independent Study
• Interviews
• online courses
• Satisfaction
• student attitudes
• Student Surveys
• usability
• Visual Aids