HOW BIG DATA ANALYTICS WILL RESHAPE E-LEARNING?

Abstract

Over the last several years, analytics and data mining have become new challenges for educational field and the idea of using the great benefits of automated methods for making sense of educational data received a significant boost. This paper gives an overview about learning analytics and educational data mining and also explains the way they are used in order to improve the support for educators and learners in their strive to achieve high quality learning outcomes (or results) and the way they improve decision making process in academic environment to maximize strategic outcomes. The amount of data being digitally collected and stored is vast and heterogeneous. As a result, the science of data management and analysis is also advancing to enable educational field to convert this vast resource into information and knowledge that helps teachers and educational organizations to achieve their objectives. Computer scientists have invented the term big data to describe this evolving technology. Big data has been successfully used in the many areas of activity, and the e-learning in particular. New educational technologies have allowed students, educators and managers to generate tremendous data via mobile devices, learning management systems, social networks, cognitive biometrics technologies and so on, resulting in what has been called as big data. Learning analytics and educational data mining techniques allow big data to be analysed from different perspectives, including monitoring students' activities, designing pedagogical interventions to support students, prediction of the learning success, failure, and potential dropouts, adaptation/personalization of learning content and learning tasks. Sometimes, in order to apply automated methods to analyse an educational context, it is required the use some type of personal data that should help university to build detailed student profile, and achieve competitive advantage. However, learning analytics and data mining do pose a threat to some important ethical values like privacy and individuality.