Adapting Fleming-Type Learning Style Classifications to Deaf Student Behavior

This study presents the development of a novel integrated data fusion and assimilation technique to classify learning experiences patterns among deaf students using Fleming’s model together with Thai Sign Language. Data were collected from hearing disabilities (Grades 7–9) studying at special schools in Khon Kaen Udon Thani, Thailand. research used six classification algorithms being resynthesized improved via application feature selection, imbalanced corrected synthetic minority oversampling technique. The collection was evaluated 10-fold validation. revealed that multi-layer perceptron algorithm yields highest accuracy. These results are intended for further studies involving problems.