Assessing Student Performance by Learning Analytics Dashboards

Abstract

In today’s competitive business environment, multiple diverse applications produce a huge amount of data, which are typically referred to as big data. Business Intelligence and Analytics are increasingly applied in public and private sectors for monitoring complex data using dashboards and effectively support decision making. Business dashboards (BDs), as complete executive information systems, enable business performance to be examined toward defined targets in a visual front-end interface.

Institutions in distance learning apply similar methodologies to manage the explosion of educational data by employing data mining and visualization techniques in students' logs. The lack of a daily real-time data analysis and the delay in the immediate presentation of critical information, limit the teachers’ early decisions. With the emergence of Learning Analytics Dashboards (LADs), as a system of collecting, analyzing and simultaneously visualizing vital knowledge in a customizable interface, teachers are provided with information regarding current students’ progress.

This study explores specific LADs in the Moodle platform, applied to a seminar offered by the Educational Content Methodology and Technology Laboratory of the Hellenic Open University and visualizes the findings of students’ interactions. The papers’ contribution concerns the enhancement of teacher decision-making and student self-reflection by monitoring their activity and providing accurate feedback on time.