Applied Artificial Intelligence in Education: Generative Tools, Learning Analytics, Assessment, and Governance

Artificial intelligence is becoming increasingly embedded in educational systems through generative tools, learning analytics, educational data mining, automated feedback, adaptive assessment, and predictive models. These developments offer new possibilities to personalize instruction, support early identification of students’ needs, improve assessment practices, and strengthen data-informed decision-making across schools and universities. At the same time, the implementation of AI-based systems raises important questions regarding validity, explainability, fairness, privacy, transparency, and governance, as well as their practical implications for teachers’ work and institutional practice.This Research Topic aims to gather applied and systems-oriented contributions on the design, implementation, evaluation, and governance of AI-based systems in education. In particular, we welcome studies on generative AI applications for teaching, feedback, and assessment; learning analytics and educational data mining for prediction and student support; explainable AI in educational decision-making; validation and benchmarking of AI-enabled assessment tools; teacher workload, professional practice, and institutional adoption of AI; and ethical, legal, and equity issues associated with AI deployment at scale. Contributions should focus on specific AI applications, methods, interventions, or governance frameworks, rather than broad theoretical discussions of psychological adaptation to AI in educational contexts.Areas of interest include, but are not limited to:• Generative AI tools for teaching, learning support, feedback, and assessment• Learning analytics, educational data mining, and predictive models in education• Explainable AI and trustworthy AI for educational decision-making• Validation, benchmarking, and evaluation of AI-based educational systems• AI-supported assessment, automated feedback, and adaptive testing• Teacher workload, professional practice, and institutional implementation of AI• Ethical, privacy, transparency, bias, and governance issues in educational AI• Empirical, methodological, longitudinal, and intervention studies on AI deployment in educational settingsThis Research Topic welcomes original research articles, empirical studies, systematic reviews, other reviews, meta-analyses, and methods papers. Topic editors: Juan Pedro Martínez-Ramón, Inmaculada Méndez, Cecilia María Ruiz Esteban Source: https://www.frontiersin.org/research-topics/79277/applied-artificial-intelligence-in-education-generative-tools-learning-analytics-assessment-and-governance