Performance Analysis and Prediction in Educational Data Mining: A Research Travelogue

TL;DR

This paper surveys the evolution of educational data mining from 2002 to 2014, highlighting its potential to improve educational effectiveness through analysis and prediction of large educational datasets.

Contribution

It provides a comprehensive review of educational data mining research over a decade, identifying gaps and future directions in the field.

Findings

Educational data mining is in nascent stages with untapped potential.

No unified approach exists among existing research.

Data mining can significantly enhance educational decision-making.

Abstract

In this era of computerization, education has also revamped itself and is not limited to old lecture method. The regular quest is on to find out new ways to make it more effective and efficient for students. Nowadays, lots of data is collected in educational databases, but it remains unutilized. In order to get required benefits from such a big data, powerful tools are required. Data mining is an emerging powerful tool for analysis and prediction. It is successfully applied in the area of fraud detection, advertising, marketing, loan assessment and prediction. But, it is in nascent stage in the field of education. Considerable amount of work is done in this direction, but still there are many untouched areas. Moreover, there is no unified approach among these researches. This paper presents a comprehensive survey, a travelogue (2002-2014) towards educational data mining and its scope in future.