Educational data mining and big data framework for e-learning environment

Abstract

E-learning data consists of large volume of educational data and available with complex and hybrid data architecture. Capturing of student performances, student evaluation and student's interaction information are one of the challenges faced by the e-learning software users at the time of analysis. Integrating student data along with educational data for analysis needs complex system design framework. New innovations in e-learning also facilitates augmented learning, adaptive learning, web based learning, activity based learning, and project based learning. Education technology interventions using learning management system, content management system, advanced distributed learning; sharable content object reference models and application program interfaces enhanced and extended the e-learning frameworks to a greater horizon. Present technology also ensures transformations of e-learning information without any geographical barriers. These educational and student or user data combined together forms big data architecture under e-learning environment and mining these big data for various requirements or knowledge discoveries needs innovative approaches. This paper identifies and evaluates various e-learning models and associated education technology paradigm. The research further explores and proposes a new framework for big data integrations. The paper also discusses the scope of future research on data mining and role of big data in e-learning environment.