Big Data-Driven Innovation in University Ceramic Education and Teaching Practices
27 feb 2025
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Publicado en línea: 27 feb 2025
Recibido: 13 oct 2024
Aceptado: 28 ene 2025
DOI: https://doi.org/10.2478/amns-2025-0101
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© 2025 Zhenguang Wang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
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Ablation Study Results: Performance of ST-GCN Model with Components Removed on WikiArt Dataset
| Component Removed | Task Completion Time (TCT) (min) | Skill Improvement (SI) (%) | Creativity Deviation (CD) | Error Rate (ER) (%) | Model Stability (MS) (Std Dev) | Training Efficiency (TE) (%) |
|---|---|---|---|---|---|---|
| Full Model | 14.3 | 45.6 | 8.7 | 3.2 | 1.5 | 92.1 |
| Without ST-GCN Backbone | 18.6 | 33.2 | 7.1 | 5.5 | 4.2 | 75.3 |
| Without Attention Mechanism | 16.7 | 40.1 | 8.1 | 4.5 | 3 | 82.5 |
| Without Adaptive Learning | 15.8 | 42.3 | 8.3 | 4 | 2.8 | 87.3 |
| Without Real-Time Feedback | 17.1 | 38.9 | 7.6 | 4.8 | 3.5 | 81.1 |
Comparative Performance of Different Models in Pottery Education
| Model | Task Completion Time (TCT) (min) | Skill Improvement (SI) (%) | Creativity Score (CS) | Response Time (FRT) (s) | Accuracy (%) | Feedback Effectiveness (%) | Student Satisfaction (SS) (%) |
|---|---|---|---|---|---|---|---|
| Our Model | 14.3 | 45.6 | 8.7 | 3.2 | 89.5 | 93.1 | 91.7 |
| RNN-LSTM[ |
17.9 | 39.4 | 7.9 | 5.1 | 86.8 | 87.4 | 85.3 |
| CNN-Based[ |
16.8 | 41.1 | 8.1 | 4.3 | 88.2 | 89.7 | 87.2 |
| Traditional Evaluation (Manual)(Unit) | 22.1 | 30.8 | 7.2 | N/A | 83.4 | N/A | 78.5 |
| Transformer XL[ |
16.4 | 42.2 | 8.3 | 4.8 | 88.7 | 90.2 | 87.5 |
| BERT-Gen | 18.2 | 37.9 | 7.6 | 5.3 | 86.1 | 86.4 | 83.1 |
| T5-Large[ |
15.9 | 43.8 | 8.5 | 4.2 | 89.2 | 92.4 | 89.3 |
| BART | 16.7 | 40.5 | 8 | 4.5 | 88.4 | 90.1 | 86.8 |