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Direct linkHayat Sahlaoui; El Arbi Abdellaoui Alaoui; Said Agoujil; Anand Nayyar – Education and Information Technologies, 2024
Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…
Descriptors: Sampling, Classification, Algorithms, Prediction
Kavale, Kenneth A.; LeFever, Gretchen B. – Journal of Educational Research, 2007
The authors critiqued the M. K. Lovelace (2005) meta-analysis of the Dunn and Dunn Model of Learning-Style Preferences (DDMLSP). The conclusion that Lovelace reported in her meta-analysis that learning-style instruction is a beneficial form of instructional delivery is unjustified because of critical conceptual and practical problems. Those…
Descriptors: Cognitive Style, Doctoral Dissertations, Meta Analysis, Teaching Methods
