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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Educational Data Mining & Students’ Performance Prediction

Author 1: Amjad Abu Saa
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 5 · Published 2016 · Cited by 129

DOI: https://doi.org/10.14569/IJACSA.2016.070531

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Abstract

It is important to study and analyse educational data especially students’ performance. Educational Data Mining (EDM) is the field of study concerned with mining educational data to find out interesting patterns and knowledge in educational organizations. This study is equally concerned with this subject, specifically, the students’ performance. This study explores multiple factors theoretically assumed to affect students’ performance in higher education, and finds a qualitative model which best classifies and predicts the students’ performance based on related personal and social factors.

Keywords

Data Mining Education Students Performance Patterns

How to Cite this Article

Saa, A. A. (2016). Educational Data Mining & Students’ Performance Prediction. International Journal of Advanced Computer Science and Applications, 7(5). https://doi.org/10.14569/IJACSA.2016.070531

Saa, Amjad Abu. "Educational Data Mining & Students’ Performance Prediction." International Journal of Advanced Computer Science and Applications, vol. 7, no. 5, 2016, https://doi.org/10.14569/IJACSA.2016.070531.

@article{Saa2016,
  title     = {Educational Data Mining & Students’ Performance Prediction},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {5},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Amjad Abu Saa},
  doi       = {10.14569/IJACSA.2016.070531},
  url       = {https://doi.org/10.14569/IJACSA.2016.070531}
}

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