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

arXiv: https://arxiv.org/abs/1801.06052 · HTML: https://mlsanity.com/paper/1801.06052/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jan 2018.

## Built on by (most cited first, 2 of 2)

- [Physics-Informed Neural Network Method for Solving One-Dimensional Advection Equation Using PyTorch](https://mlsanity.com/paper/2103.09662/) (2021)
- [Natural Language Processing Accurately Categorizes Indications, Findings and Pathology Reports from Multicenter Colonoscopy](https://mlsanity.com/paper/2108.11034/) (2021)

## Abstract (arXiv)

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.