AN APPROACH METHOD TO PREDICT STUDENTS’ EXAM PERFORMANCE USING CLUSTERING METHODS WITH PREDICTION MODEL

Authors

Shallaw Mohammed Ali Department of computer engineering techniques, Al-Qalam university college, Kirkuk, Iraq,
Noor Jasim Mohammed Electrical and computer engineering

Keywords:

Prediction model, clustering; K-means method, Fuzzy c-means, Hierarchal

Abstract

The abilities of predicting human’s behavior have increased dramatically in the new era of data mining applications. one of these applications is the attempts of predicting students’ performance based on their activities and parental level of study. In this work, we present an approach method of predicting students’ exam performance using clustering methods of (Fuzzy c-means, K-means and Hierarchal) combined with artificial neural network model of prediction. The results show that the use of clustering algorithms in the prediction process provides a high quality of prediction from (70% to 95%). This work also involves a comparison between these algorithms, which shows that the highest quality of predication can be obtained by using K-means method

References

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Published

2021-11-25

How to Cite

Shallaw Mohammed Ali, & Noor Jasim Mohammed. (2021). AN APPROACH METHOD TO PREDICT STUDENTS’ EXAM PERFORMANCE USING CLUSTERING METHODS WITH PREDICTION MODEL. European Journal of Research Development and Sustainability, 2(11), 29-32. Retrieved from https://scholarzest.com/index.php/ejrds/article/view/1448