A Systematic analysis of Data-intensive MOOCs and their key Challenges

Abstract

Big Data blends modern technologies with numerous data management techniques to handle a wide variety of concerns that occur when operating with data of huge volume, variety and velocity. Big data deals with complex semi-structured and unstructured data from several sources and formats which include Social Media content in free form, data from E-commerce sites, Weather forecasting statistics, Clinical Diagnosis, Share Market Transactions and Smart Computing Environments. In the same way, big data offers substantial prospects in the discipline of Education, E- Learning and Learning Analytics. Application of big data analytics in E-Learning helps to assess the quality of Teaching, Development of Curriculum, predict learning outcomes, Career Development and Readiness, Attrition Risks and Feedback Analysis. The Massive Open Online Courses (MOOCs) have produced a major influence on E-Learning with the availability of Live and pre-recorded Lectures, Easy-to-learn Tutorials, Novel Assessment Methodologies, Quick feedback and results. In this paper, we present the various Technologies that formulate the MOOCs and address the learning paradigms and key challenges.