Analytics Prototype for Data Driven Decision Making for Blended Learning Strategies in HEI

Abstract

In this paper we present a tool that introduces data-driven decision making concerning the implementation and adoption of blended learning in higher education. We identified key groups from the university’s administration that are directly involved in the learning and teaching processes and captured their goals and perspectives in the context of eLearning processes. We used these perspectives and goals to sketch out systematical introduction of data-driven decision making processes which can create sustainable impact on their work and the blended learning scenarios. This resulted in building a web-based prototype that visualizes usage statistics and analytics of the log data extracted from the university-wide learning platform. This prototype contains indicators and visualizations mapped to the goals and perspectives of the identified key user groups, in order to provide insight how the different faculties teach and learn utilizing the platform and provides actionable intelligence to better distribute resources and support the staff and students in their respective blended learning scenarios.