Personal learning environments: A Big Data perspective

Abstract

Problem Statement: Traditional instructional learning based platforms (e.g., Learning Management Systems) and master – apprentice model is not sufficient for the companies and their human capital anymore. Employees should lead their vocational competence in a connected, fast changing world. It is a great challenge for enterprises and people to find relevant learning resources in an unstructured, scattered, distributed,  and overwhelmingly large amount of information ocean and un-learn / learn continuously in this environment.Purpose of Study: Personal Learning Environments enhanced with Big Data analysis opportunities and emerging technologies seem a solution for the aforementioned problem. This study aims to propose a preliminary Personal Learning Environment Architecture leveraging Big Data possibilities.Methods: Systematic literature review method is used to review the literature reviews  including the research of Big Data in education and personal learning environments.Findings and Results: Based on the literature knowledge captured, a preliminary personal learning environment architecture is synthesized and proposed.Conclusions and Recommendations: Proposed preliminary architecture seems to address basic usecases in the literature. However a detailed data gathering should be conducted in a large enterprise using more sophisticated technics such as field surveys, descriptive analytics and case studies. Although the architecture is promising for the personal learning environments, it needs systematic validation with more data both technologically and andragogically.

 Keywords: big data in education, personal learning environment, personal learning assistant, learning mentor, learning analytics.