Learning Path Adaptivity in Support of Flipped Learning: A Knowledge-based Approach

Flipped learning inverts the two learning spaces of traditional education: the classroom group learning space and the homework individual learning space. In flipped learning, learners are exposed to direct instruction for basic knowledge acquisition before coming to the classroom for active learning with the teacher and peers. In recent years, flipped learning has received vast attention from educational practitioners and researchers. However, this study argues that existing e-learning systems mainly serve for learning management and content delivery purposes and lack support for flipped learning. As an innovative educational approach, flipped learning needs more pedagogical elements such as integrated instructional design and adaptive content delivery to achieve effective direct instruction. This study aims to create a learning adaptivity design to effectively support learning in the flipped individual learning space where the teacher is absent. Since teaching involves various pedagogical and content knowledge sources, we propose a conceptual model of teaching as the function of the knowledge triad of curriculum guidance (G), teaching activity (A), and learning object (O). To realize such conceptualization, ontological problem-solving approach is used for knowledge-based system (KBS) development to integrate the relevant knowledge sources. The knowledge model is created using the Protégé platform to develop the OWL-based domain ontology, task ontology, and the SWRL-based semantic rules to enable inference among the GAO triad for learning adaptivity. The case experiment results show that the KBS prototype is able to adaptively guide student learning in the flipped individual learning space with the knowledge sources considered.