Yang Kang | Communication, Media and Learning Technologies Design | Mathematics Science and TechnologySkip to content Skip to main navigation
Transformation from MOOCs to Adaptive MOOCs: Integrating Adaptive Learning System into Massive Open Online CoursesYang Kang, M.A. in Instructional Technology and Media
Massive Open Online Courses (MOOCs) have become a preferred learning trend in recent years, since they make people easily access to the most excellent online educational resources at no cost, regardless of background and experience. However, the high dropout rates in MOOCs have led researchers and educators to consider how to balance between massive participation and student’s learning performance. This paper suggests that adaptive learning could be one approach to ameliorate the challenges. By conducting literature review on previous studies, the paper analyzes four main components of adaptive learning systems: student learning preferences model, diagnostic assessment, learning preferences correction mechanism, and dynamic content sequencing, and synthesizes the important learning variables when building learning preferences model. Based on the conceptual principles of adaptive learning system, this paper proposes several approaches to enhance the adaptiveness in MOOCs environments, from both course design and assessment perspectives.