Refining Graduation Classification Accuracy with Synergistic Deep Learning Models
Learning Analytics plays an important role in monitoring and improving educational outcomes, but is often challenged by limited dataset sizes, resulting from privacy regulations and curriculum changes. This paper proposes the LATCGAd (Learning Analysis by Transformer with Conditional Generative Adve...
Saved in:
| Main Authors: | Son Nguyen Thi Kim, Quynh Nguyen Huu, Minh Bui Tuan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2025-06-01
|
| Series: | Cybernetics and Information Technologies |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/cait-2025-0016 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hybrid Deep Learning Framework for High-Accuracy Classification of Morphologically Similar Puffball Species Using CNN and Transformer Architectures
by: Eda Kumru, et al.
Published: (2025-07-01) -
How Students Learn: Perspective of Medical Graduates about Teaching-Learning and Academic Performance
by: Supriya Dhakne-Palwe, et al.
Published: (2025-06-01) -
Enhancing diabetic retinopathy classification accuracy through dual-attention mechanism in deep learning
by: Abdul Hannan, et al.
Published: (2025-12-01) -
Usage of Learning Management System Web Analytics in Blended Learning Self-Study Evaluation
by: G. P. Ozerova
Published: (2020-09-01) -
The phenomenon of declining relative earnings of graduates
by: Marek Rocki
Published: (2025-06-01)