William Villegas-Ch
Biographic Data
| ID | 9817610 |
|---|---|
| NAME | William Villegas-Ch |
| GIVEN NAMES | William |
| FAMILY NAME | Villegas-Ch |
| SIGNATURE | VILLEGAS-CH W |
| AFFILIATIONS | Universidad de Las Américas |
| ORCID | 0000-0002-5421-7710 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Modeling informal learning as a dynamic interaction process in digital learning environments
Digital learning environments in higher education generate large volumes of interaction data that reflect a substantial portion of the learning processes occurring outside of formally assessed activities. However, these informal learning dynamics remain difficult to observe and analyze systematically due to their non-evaluative, irregular, and self-organized nature. Most current approaches to educational analytics focus on aggregate indicators or…
Machine learning models for academic performance prediction
The integration of artificial intelligence in education has enabled the development of predictive models for academic performance. However, most existing approaches lack interpretability and do not provide actionable insights for decision-making. This study addresses these limitations by deploying optimized machine learning models, specifically XGBoost and Random Forest, to predict student performance considering geographically, institutional, so…
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Machine learning models for academic performance prediction
The integration of artificial intelligence in education has enabled the development of predictive models for academic performance. However, most existing approaches lack interpretability and do not provide actionable insights for decision-making. This study addresses these limitations by deploying optimized machine learning models, specifically XGBoost and Random Forest, to predict student performance considering geographically, institutional, so…
Modeling informal learning as a dynamic interaction process in digital learning environments
Digital learning environments in higher education generate large volumes of interaction data that reflect a substantial portion of the learning processes occurring outside of formally assessed activities. However, these informal learning dynamics remain difficult to observe and analyze systematically due to their non-evaluative, irregular, and self-organized nature. Most current approaches to educational analytics focus on aggregate indicators or…
Online Learning and Analytics (2 works) · Artificial Intelligence (1 works) · Computer Science (1 works) · Data science (1 works) · Database (1 works) · Decision support system (1 works) · Decision tree (1 works) · Educational Data Mining (1 works) · Educational Environments and Student Outcomes (1 works) · Explainable Artificial Intelligence (XAI (1 works)