HIGHLIGHTS
- who: Balqis Albreiki from the Department of Computer have published the research: Extracting topological features to identify at-risk students using machine learning and graph convolutional network models, in the Journal: (JOURNAL)
- what: This approach has been extended to enhance the underlying structure, resulting in a knowledge graph. From the studies mentioned above, it is clear that most of this research is primarily concerned with employing basic features and ML approaches to predict students` performance with reasonable accuracy. This study proposes a hybrid_approach based on knowledge graphs and ML for predicting student academic performance, particularly . . .
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