Conceptual framework for process-oriented feedback through Learning Analytics Dashboards

Abstract

The number of students enrolled in online higher education courses is increasing, and as a result, more data on their learning process is being generated. By exploring this student behavior data through learning analytics, both student and teacher can be provided with process-oriented feedback in the form of dashboards. However, little is known about the typology of relevant feedback in the dashboard to different learning objectives, students and teachers. Although most dashboards and the feedback they provide are based solely on student performance indicators, research shows that such feedback is not sufficient. This article attempts to define a conceptual model that visualizes the relationships between the design of a Learning Analytics Dashboard (LAD) and the concepts of learning science in order to provide process-oriented feedback that supports the regulation of learning. The aim of the work is not to propose a specific design of the LAD to provide feedback, but rather a conceptual framework for the choice of concepts for that design, and therefore to help understand future data needs as a basis for the educational feedback of the dashboards. As a conclusion of our research, we can say that having LADs adapted to any profile (student, teacher, etc.) can improve decision-making processes by showing each user the information that interests them most in the way that best enables them to understand it.