Table 5 AI and technology used in intelligent tutoring systems
Objective | Category | Technology description | Count |
|---|---|---|---|
Performance Prediction | Supervised Learning | Logistic or Linear Regression: 5, SVM (Support Vector Machine): 5, BayesNet/NB (Nayes Network or Naive Bayes): 4, RF (Random Forest) 3, NN (Neural Network) 4, AB/XGBoost (Adaptive or Extreme Gradient Boosting): 3, CART (Classification and Regression Tree): 2 | 33 |
Unsupervised Learning | KNN (K Nearest Neighborhood): 4 | 4 | |
Others | Novel approach or other models | 7 | |
Learning Behavior Analysis | Unsupervised Learning | KNN: 4, SVM: 2 | 6 |
Supervised Learning | Regression: 1, RF: 1, NN: 1, XGBoost: 2 | 5 | |
Others | Novel approach or refer to other studies | 3 | |
Instructors Support | Natural Language Processing Support | LDA (Latent Dirichlet Allocation): 1, DistilBERT (Distilled Bidirectional Encorder Representing Transformer): 1, NLTK (Python Natural Language Tool Kit): 1, PyCharm (Python Development Kit): 1 | 4 |
Decision-Making and Facial Recognition | HMM (Hidden Mokov Models): 1, Azure for ER (Emotional Recognition), OpenCV (Facial Detection Kit) | 3 | |
Others | Novel approach/refer to other studies | 1 | |
Engagement & Dropout Prediction | SVM | Support Vector Machine | 1 |
Supervised Learning | SVM: 1, RF: 1, XGBoost: 1, GB (Gradient Boosting): 1, NN: 1 | 4 | |
Others | Novel approach/Refer to other studies | 1 | |
Adaptation/Personalization | CNN (Facial) | Convolutional Neural Network | 1 |
TensorFlow | TensorFlow Object Detection API | 1 | |
Replika API | Chatbot API | 1 | |
Learning Intervention | Sending reminding through email | 1 | |
System Reminding | System reminds instructors | 2 | |
Assessment | Guidelines | Guidelines for system architects | 2 |
Explanation | XAI | Counterfactual and SHAP method | 2 |