Predictive Model to Analyse Real and Synthetic Data for Learners' Performance Prediction Using Regression Techniques
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often h...
Saved in:
| Main Authors: | SHABNAM ARA S.J, Tanuja R, Manjula S.H |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Online Learning Consortium
2025-03-01
|
| Series: | Online Learning |
| Online Access: | https://olj.onlinelearningconsortium.org/index.php/olj/article/view/4390 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Machine learning for workpiece mass prediction using real and synthetic acoustic data
by: D. S. Whittaker, et al.
Published: (2025-06-01) -
XGBoost To Enhance Learner Performance Prediction
by: Soukaina Hakkal, et al.
Published: (2024-12-01) -
Real-time earthquake magnitude prediction using designed machine learning ensemble trained on real and CTGAN generated synthetic data
by: Anushka Joshi, et al.
Published: (2025-05-01) -
A synthetic data-driven machine learning approach for athlete performance attenuation prediction
by: Mauricio C. Cordeiro, et al.
Published: (2025-05-01) -
Synthetic data for privacy-preserving clinical risk prediction
by: Zhaozhi Qian, et al.
Published: (2024-10-01)