Utilizing Real-Time Descriptive Learning Analytics to Enhance Learning Programming

Abstract

The focus of this case study is the usage of visualized learning analytics coupled with the provision of feedback and support provided to the students and their impact in provoking change at student programming habits. To this end, this chapter discusses mechanisms of capturing and analyzing the debugging habits and the quality of the design solutions provided by the students in the context of an object-oriented programming course. The environment monitored students' programming progression in order to track their behavior and visualize metrics associated with it while the students developed programs in Java. This chapter presents an exploratory study, which provides valuable insights through the lens of the collected evidence from students' use employing semistructured interviews and eye-tracking techniques. It was found that visual learning analytics coupled with some adaptability foster students' learning awareness, support learning by reflection, and increase students' self-confidence. When adaptive and visual learning analytics capabilities are incorporated, it is vital to follow minimal and well-integrated design, focus on meaningful representations for the learners and the tutors, include descriptive visual analytics, and consider incorporating adaptability characteristics.