The European Context of AI in Education
The integration of artificial intelligence into educational systems represents a strategic priority for the European Union. Policies concerning digital skills, the Digital Education Action Plan, and the AI Act outline a framework in which schools are called upon to become data-driven, inclusive, and technologically aware. It is within this context that the study “Enhance Student Well-being and Digital Literacy with Machine Learning and Spatial Analysis,” presented within the European academic sphere, is situated.
Research Objectives
The research analyzes the relationship between digital literacy, student well-being, and academic performance in three Italian secondary school classes (N=64). The objective is to understand how digital competencies and classroom spatial dynamics influence educational outcomes, providing evidence useful for Italian and European educational policies.
Methodology: Machine Learning and Spatial Econometrics
The study integrates Machine Learning models, including Random Forest and neural networks, with spatial econometric models such as the Spatial Autoregressive Model (SAR) and Geographically Weighted Regression (GWR). The data include grades, well-being questionnaires, digital competence tests, LMS logs, and classroom seating arrangements.
The Random Forest model explained 55% of the variance in final grades (R²=0.55), while the SAR model achieved an R²=0.725, highlighting a significant effect of proximity between students on academic performance.
Main Results
During the semester, an average increase in grades from 5.34 to 6.15 was recorded, along with an improvement in well-being from 0.48 to 0.95. Proximity to high-performing students was associated with an average increase of 0.38 points in final grades, demonstrating the impact of spatial dynamics.
Students with higher levels of digital literacy showed better academic results and higher levels of psychological well-being, confirming the importance of digital competencies as a strategic lever for learning.
Implications for Italian and European Schools
The results suggest that educational policies should permanently integrate digital literacy into curricula and consider the physical design of school spaces as a determining factor. The combination of AI, data analysis, and conscious classroom design can support more equitable and targeted educational strategies.
Within a European context oriented toward digital sovereignty and the technological transformation of education, these findings reinforce the importance of investments in teacher training, digital infrastructures, and the ethical governance of data.
Future Perspectives
The authors highlight the need to expand the sample size and replicate the study in other European contexts. Future research could integrate federated learning approaches in order to combine predictive performance and privacy protection, in line with the GDPR and European AI guidelines.
Conclusion
The integration of machine learning, spatial analysis, and digital literacy offers a replicable model for improving both academic performance and student well-being. The challenge for Italian and European schools is not merely to adopt artificial intelligence, but to govern its use in an ethical, inclusive, and evidence-based manner.
