Abstract

Conclusion. The correct classification of unsuccessful students with high performance shows that the model effectively predicts these students. However, the lower accuracy rates obtained in predicting successful students indicate that additional variables (taking private lessons and courses, etc.) should be examined to improve the performance of the ANN model for this group.

Keywords: Artificial neural networks, central examination, scholarship, classification, digital educational content

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