Developing a Large-Scale Adaptive Learning Platform: Integrating Dynamic Concept Maps and Adaptive Recommendations

• In Event: 68.062 - Poster Session 15
  In Poster Session: 68.062-1 - Participation and Adaptation Through Learning Technologies

Abstract

Individual students’ learning strengths and weaknesses can be revealed via analyzing learning activities, learning processes, and learning performances. Online learning platforms can provide various tracking tools for instructors to “observe” or “monitor” individual students’ learning activities. Analysis of this collected data can then be utilized to develop corresponding automatic interventions to achieve goals of adaptive learning in self-paced online environments. This project addresses identified shortcomings in other large-scale learning platforms by integrating dynamic concept maps. In addition, other intelligent components are considered such as personalized learning path recommendations and context-based recommendations for meeting personal learning needs. Addressing the validity of each intelligent component is discussed as a measure of practical application, and recommendations from the development process are noted.

Authors

• Chieh-Feng Chiang, Digital Education Institute, Institute for Information Industry, Taiwan

• Jui-Long Hung, Boise State University

• Brett E. Shelton, Boise State University

• Hsiao-Chien Tseng, Digital Education Institute, Institute for Information Industry, Taiwan

• Jun-Ming Su, Department of Information and Learning Technology, National University of Tainan, Taiwan

• Stephen J. H. Yang, National Central University, Taiwan