Artificial Intelligence Across Educational Contexts: Adoption, Experiences, and Responsible Practice

Artificial intelligence (AI) is transforming teaching, learning, assessment, student support, and institutional decision-making. Recent advances in generative AI, intelligent tutoring systems, automated feedback, adaptive learning, and learning analytics have created opportunities to personalise learning, improve accessibility, support educators, and enhance institutional efficiency. However, the rapid adoption of these technologies has also intensified concerns about bias, transparency, privacy, surveillance, academic integrity, unequal access, and the preservation of human agency. Evidence regarding the educational value of AI remains uneven, particularly across educational levels, disciplines, cultures, and stakeholder groups. Although emerging studies highlight the potential of AI-supported learning and assessment, ongoing debates concern reliability, explainability, teacher and learner agency, professional identity, and the appropriate balance between automation and human judgement. Shared evidence, policy frameworks, and pedagogical models for responsible implementation remain underdeveloped. Interdisciplinary research is therefore needed to examine not only what AI can do, but also how it is adopted, experienced, governed, and evaluated in diverse educational settings.This Research Topic aims to advance an evidence-informed understanding of the adoption, use, governance, and impact of AI across educational contexts. It seeks to identify effective pedagogical and organisational practices, examine emerging risks and inequalities, and clarify the conditions required for ethical, transparent, inclusive, and sustainable implementation. Contributions may investigate how AI influences learning outcomes, assessment practices, educator workload, professional roles, learner autonomy, and institutional decision-making. The Research Topic also aims to explore how AI literacy can be developed among educators, students, leaders, and policymakers, and how human–AI collaboration can be designed to preserve professional judgement, meaningful educational relationships, and trust.To gather further insights across schools, higher education, vocational education, teacher education, workplace learning, and lifelong learning, we welcome articles addressing, but not limited to, the following themes:Generative AI and large language models in educationIntelligent tutoring and adaptive learning systemsAutomated assessment, feedback, and gradingLearning analytics and AI-supported decision-makingAI literacy and digital competenceTeacher and student perceptions, attitudes, and experiencesTeacher agency, professional identity, and changing rolesLearner autonomy, engagement, and learning outcomesAcademic integrity and assessment redesignEquity, inclusion, accessibility, and educational inequalityBias, fairness, transparency, explainability, and trustPrivacy, data protection, surveillance, and cybersecurityInstitutional readiness, leadership, and organisational changePolicy development, regulation, and AI governanceHuman–AI collaboration and the preservation of professional judgementResistance, unintended consequences, and implementation challengesCross-cultural, cross-disciplinary, and comparative perspectivesParticipatory, design-based, and responsible innovation approachesWe invite original research articles, systematic and scoping reviews, conceptual and theoretical papers, methodological studies, case studies, policy analyses, perspectives, and brief research reports using qualitative, quantitative, mixed-methods, comparative, design-based, or interdisciplinary approaches. Topic editors: Georgios P. Georgiou, Antonios Kafa Source: https://www.frontiersin.org/research-topics/84184/artificial-intelligence-across-educational-contexts-adoption-experiences-and-responsible-practice