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A Survey on Pre-Processing Educational Data

  • Cristóbal Romero
  • José Raúl Romero
  • Sebastián Ventura
Chapter
First Online:
Part of the Studies in Computational Intelligence book series (SCI, volume 524)

Abstract

Data pre-processing is the first step in any data mining process, being one of the most important but less studied tasks in educational data mining research. Pre-processing allows transforming the available raw educational data into a suitable format ready to be used by a data mining algorithm for solving a specific educational problem. However, most of the authors rarely describe this important step or only provide a few works focused on the pre-processing of data. In order to solve the lack of specific references about this topic, this paper specifically surveys the task of preparing educational data. Firstly, it describes different types of educational environments and the data they provide. Then, it shows the main tasks and issues in the pre-processing of educational data, Moodle data being mainly used in the examples. Next, it describes some general and specific pre-processing tools and finally, some conclusions and future research lines are outlined.

Keywords

Educational data mining process Data pre-processing Data preparation Data transformation 

Abbreviations

AIHS

Adaptive and intelligent hypermedia system

ARFF

Attribute-relation File Format

CBE

Computer-based education

CSV

Comma-separated values

DM

Data mining

EDM

Educational data mining

HTML

Hypertext Markup language

ID

Identifier

IP

Internet Protocol

ITS

Intelligent tutoring system

KDD

Knowledge discovery in databases

LMS

Learning management system

MCQ

Multiple choice question

MIS

Management information system

MOOC

Massive Open Online Course

OLAP

Online Analytical Processing

SQL

Structured Query Language

WUM

Web Usage Mining

WWW

World Wide Web

XML

Extensible Markup Language

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Notes

Acknowledgments

This research is supported by projects of the Regional Government of Andalucía and the Ministry of Science and Technology, P08-TIC-3720 and TIN-2011-22408, respectively, and FEDER funds.

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© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Cristóbal Romero
    • 1
  • José Raúl Romero
    • 1
  • Sebastián Ventura
    • 1
  1. 1.Department of Computer Science and Numerical AnalysisUniversity of Córdoba Campus de RabanalesCórdobaSpain

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