From data to action: leveraging e-learning logs for educational decision-making

Abstract

E-learning platforms generate vast amounts of log data that capture detailed records of learner interactions, providing a rich resource for understanding and improving the learning experience. This article explores how e-learning log data can be transformed into actionable insights to inform educational decisions. By examining key metrics and parameters in available streaming data, educators can identify areas for curriculum improvement, intervention strategies, and personalised learning paths. Data quality issues, privacy concerns, and the need for advanced analytics tools such as machine learning and data visualisation techniques to harness the full potential of log data are discussed. The article analyses a case study from Estonian higher education institutions using log data from the Moodle platform to analyse learning outcomes and identify intervention strategies to prevent dropout/improve learning outcomes. The aim of this article is to provide actionable solutions for education stakeholders seeking to bridge the gap between raw data and actionable strategies by promoting a data-driven approach to e-learning optimisation.