Big Data and Learning Analytics in Higher Education: Demystifying Variety, Acquisition, Storage, NLP and Analytics

TL;DR

This paper discusses how big data, learning analytics, and NLP can be integrated to improve decision-making and student support in higher education, addressing challenges like attrition and evolving environments.

Contribution

It provides a comprehensive overview of big data and NLP applications in higher education and introduces an integrated analytics system for supporting academic decisions.

Findings

Enhanced decision-making capabilities for academic authorities

Potential reduction in student attrition rates

Implementation of a distributed analytics system

Abstract

Different sectors have sought to take advantage of opportunities to invest in big data analytics and Natural language processing, in order to improve their productivity and competitiveness. Current challenges facing the higher education sector include a rapidly changing and evolving environment, which necessitates the development of new ways of thinking. Interest has therefore increased in analytics as part of the solution to many issues in higher education, including the rate of student attrition and learner support. This study provides a comprehensive discussion of big data, learning analytics and use of NLP in higher education. In addition, it introduces an integrated learning analytics solution leveraging a distributed technology system capable of supporting academic authorities and advisors at educational institutions in making decisions concerning individual students.