Learning Habits Mining and Data-driven Support of Building Habits in Education

Abstract

In terms of the learning logs accumulating from real-world educational activities, techniques of learning analytics help understand the characteristics of learners' behaviors. However, extracting learning habits from log data and data-driven support for building learning habits have not yet attracted much attention. Therefore, this research proposes the approach of “Learning Habits Mining,” which aims to extract the types and stages of learning habits from learners' daily learning logs and support learners to build learning habits with data-driven methods. We identify two contributions of this research. First, this research reveals the learning habits of K12 learners and provides an approach to trace the process of building learning habits automatically. Second, this research proposes interventions to the data-driven support for building learning habits so that learners can build learning habits based on evidence derived from learning logs.