Table 1.
Summary of studies and limitations.
Fig 1.
Proposed framework for student adaptability and performance.
Fig 2.
Hybrid feature extraction strategy.
Fig 3.
Correlation Matrix on (a) Student Performance and (b) Adaptability Dataset.
Fig 4.
Proposed WResNeXt-G model.
Table 2.
WideResNeXt-GRU parameter values optimized by MJA.
Fig 5.
Demographic and tech insights (Adaptability).
Fig 6.
Class distribution across topics (Performance).
Fig 7.
Average ratings for each feedback aspect (Students feedback).
Fig 8.
Correlation heatmap of feedback aspects (Students feedback).
Fig 9.
CF of WResNeXt-GMJ model.
Fig 10.
CF of BERT model.
Fig 11.
CF of CNN model.
Fig 12.
CF of SVM model.
Table 3.
Performance evaluation on adaptability dataset.
Table 4.
Performance evaluation on student performance dataset.
Fig 13.
CF of SVM model.
Table 5.
Execution time comparison.
Table 6.
Evaluation of the WResNeXt-GMJ and current methods using statistical.