A Mobile Application for Early Prediction of Student Performance Using Fuzzy Logic and Artificial Neural Networks

Authors

DOI:

https://doi.org/10.3991/ijim.v14i02.10940

Keywords:

A mobile App, Predictive systems, Fuzzy algorithm, Neural Network, Peda-gogy

Abstract


Identifying students at risk or potentials excellent students is increasingly important for higher education institutions to meet the needs of the students and develop efficient learning strategy. Early stage prediction can give an indication of the students’ performance during their study years. This helps tailoring an appropriate learning strategy for different groups.

This work develops a novel framework for a mobile app to predict the students’ performance before starting the Universities’ education. The framework is built on a University’s students data from year 2009-2017. It has three main components, namely, a neural network model that predicts the GPA, a mobile App that tests basic knowledge in different domains, and a fuzzy model that estimates the future students’ performance. 

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Published

2020-02-10

How to Cite

Nosseir, A., & Fathy, Y. (2020). A Mobile Application for Early Prediction of Student Performance Using Fuzzy Logic and Artificial Neural Networks. International Journal of Interactive Mobile Technologies (iJIM), 14(02), pp. 4–18. https://doi.org/10.3991/ijim.v14i02.10940

Issue

Vol. 14 No. 02 (2020)

Section

Papers

License

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