Analyzing K-12 Blended MOOC Learning Behaviors

Abstract

We investigate student learning behaviors in a Massive Open Online Course with in-person components. Our goal is to improve the design of the course through learning analytics. The programming language taught, App Inventor, is a drag-and-drop language to create Android applications. We visualize and quantify student behaviors such as automatic and manual saving of code, video sections viewed, and the various forms of knowledge required to understand the course material. It appears students are less likely to go from course material that teaches procedures to other material that teaches procedures than we would expect, and rarely review previous topics covered in the course. We also find students tend to save marginally less at the beginning and end of sessions. However, since the data set is small, our conclusions are limited.