Tools for Educational Data Mining

Author:

Slater Stefan1,Joksimović Srećko2,Kovanovic Vitomir3,Baker Ryan S.1,Gasevic Dragan4

Affiliation:

1. Columbia University

2. Moray House School of Education The University of Edinburgh

3. School of Informatics The University of Edinburgh

4. Moray House School of Education and School of Informatics The University of Edinburgh

Abstract

In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will highlight the utility that these tools have with respect to common data preprocessing and analysis steps in a typical research project as well as more descriptive information such as price point and user-friendliness. We will also highlight niche tools in the field, such as those used for Bayesian knowledge tracing (BKT), data visualization, text analysis, and social network analysis. Finally, we will discuss the importance of familiarizing oneself with multiple tools—a data analysis toolbox—for the practice of EDM/LA research.

Publisher

American Educational Research Association (AERA)

Subject

Social Sciences (miscellaneous),Education

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