Using Learning Analytics and Adaptive Formative Assessment to Support At-risk Students in Self-paced Online Learning

Abstract

Online education is growing but facing a problem of high academic failure rates. In self-paced online learning (SPOL), the lack of academic support - social interaction, formative feedback, learning awareness, and academic intervention - is recognized as a critical factor causing the academic failure problem. To facilitate such academic support, this study has identified three relevant technical and pedagogical strategies (formative assessment, adaptive assessment and learning analytics) that could work together as a possible solution. Design-based research is considered for this study to investigate the effectiveness of this solution in the context of STEM disciplines of formal higher online education. A computing course is selected for a case study. The design principles of the adaptive assessment model and the intervention learning analytics model are explained. Also, the expected contributions are summarized at the end.