Fig 1.
A typical learning path.
Table 1.
Summary of key studies in learning path analysis.
Fig 2.
The pipeline of the proposed model.
Fig 3.
The technical principle of the CRNN model.
Fig 4.
How knowledge points are organized using the Transformer Model.
Fig 5.
The technical rationale for the PPO reinforcement learning model.
Table 2.
Summary of datasets used in the study.
Fig 6.
Comparison of model performance on the EdNet dataset.
Table 3.
Experiment 1: Knowledge tracing performance.
Fig 7.
Comparison of predictive performance on the OULAD dataset.
Table 4.
Experiment 2: Student outcome prediction.
Fig 8.
Comparison of the models efficiency for handling multi-platform and hierarchical data using EdNet dataset.
Table 5.
Experiment 3: Efficiency analysis.
Fig 9.
Model training efficiency comparison.
Table 6.
Ablation study results.
Fig 10.
Ablation study results.
Table 7.
Performance comparison between CRNN and baseline methods.
Fig 11.
Performance comparison between CRNN and baseline methods.
Table 8.
Statistical significance of performance improvements.