The Impact of Data Preprocessing on the Quality and Effectiveness of E-Learning

Authors

  • Mounia Rahhali Engineering, Systems and Applications Laboratory, ENSA, Sidi Mohamed Ben Abdellah University, Fez, Morocco
  • Lahcen Oughdir Engineering, Systems and Applications Laboratory, ENSA, Sidi Mohamed Ben Abdellah University, Fez, Morocco
  • Youssef Lahmadi Engineering, Systems and Applications Laboratory, ENSA, Sidi Mohamed Ben Abdellah University, Fez, Morocco
  • Mohammed Zakariae El Khattabi Engineering, Systems and Applications Laboratory, ENSA, Sidi Mohamed Ben Abdellah University, Fez, Morocco

Keywords:

Big Data, Pre-processing, Data Mining, Educational data mining

Abstract

This article provides a mini review of pre-processing techniques for educational big data in data mining. With the increasing availability of educational data, there is a need for efficient pre-processing techniques that can handle the volume, variety, and velocity of data. The article discusses various pre-processing techniques, including data cleaning, data transformation, and data reduction. The review concludes that pre-processing is a critical step in data mining, and the selection of appropriate techniques depends on the characteristics of the data and the research objectives.

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Published

23.02.2024

How to Cite

Rahhali, M. ., Oughdir, L. ., Lahmadi, Y. ., & El Khattabi, M. Z. . (2024). The Impact of Data Preprocessing on the Quality and Effectiveness of E-Learning. International Journal of Intelligent Systems and Applications in Engineering, 12(16s), 59–65. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4783

Issue

Vol. 12 No. 16s (2024)

Section

Research Article

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