Supporting Reflective Teaching Workflow with Real-World Data and Learning Analytics

Abstract

Evidence-based practice stems from medicine. It involves the concept of Real-World Evidence (RWE), which involves the analysis of routinely collected patient data to extract evidence of practice. In this paper, we propose a learning-analytics (LA) based reflective teaching workflow that analyzes data from daily teaching and learning environments. This reflective teaching workflow uses a Learning and Evidence Analytics Framework (LEAF), a specific learning platform that is currently used in multiple Japanese and international educational institutions. This workflow provides a bottom-up approach for producing evidence from routinely collected data on the LA platform. We illustrate a case study in a Japanese high school math class to demonstrate the practical use of this reflective teaching workflow. We draw implications from this reflective workflow towards producing rich and robust evidence in the LEAF system, which should lead to the democratization of evidence-based practice in the classroom.