Big Data in Educational Data Mining and Learning Analytics

B R Pra kash, Dr.M. Hanuman thappa, V.R. Kavitha

International Journal of Innovative Research in Computer and Communication Engineering · 2014 · 32 citations · 8 references

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Concepts

TL;DR

Educational data mining and learning analytics are increasingly used in higher education to develop tools that uncover patterns in learning data, aiming to improve services, student grades, and retention, though the rapid growth of experiments makes distinguishing fact from fiction challenging. This issue brief aims to help policymakers and administrators understand how analytics and data mining have been—and can be—applied for educational improvement.

Abstract

Educational data mining and learning analytics are used to research and build models in several areas that can influence learning systems. Higher education institutions are beginning to use analytics for improving the services they provide and for increasing student grades and retention. With analytics and data mining experiments in education starting to proliferate, sorting out fact from fiction and identifying research possibilities and practical applications are not easy. This issue brief is intended to help policymakers and administrators understand how analytics and data mining have been—and can be—applied for educational improvement. At present, educational data mining tends to focus on developing new tools for discovering patterns in data. These patterns are generally about the micro concepts involved in learning, learning analytics.

References

8