The Cognitive Science of AI-Supported Learning: Mechanisms, Development, and Learner Agency

This Research Topic examines how cognitive science and developmental theory can advance understanding of learning in environments supported by artificial intelligence (AI) and digital technologies. It focuses on the cognitive, emotional, motivational, social, and developmental mechanisms through which learners construct knowledge, regulate learning, reason, make decisions, and develop as learners.AI-supported learning systems, including adaptive technologies, intelligent tutoring systems, learning analytics, and generative AI, are increasingly used to personalize instruction, provide feedback, and expand access to educational resources. However, their effects on learning and development remain uncertain. Many systems prioritize efficiency, automation, and measurable performance, while giving less attention to metacognition, cognitive control, motivation, reflection, learner autonomy, and the development of independent thinking. This raises important questions about when AI genuinely supports meaningful learning and when it may constrain learner agency, critical thinking, creativity, or well-being.The Research Topic aims to connect cognitive and developmental theory with the design, implementation, and evaluation of AI-supported learning. It welcomes research examining how attention, memory, cognitive load, executive function, reasoning, metacognition, motivation, emotion, and social cognition influence learning with AI. It also encourages work investigating developmental differences, individual differences, and the role of prior knowledge, cognitive ability, motivation, and educational background in shaping learners’ responses to AI-supported instruction.Contributions may use behavioral, psychophysiological, EEG/ERP, neuroimaging, computational, learning-analytic, or mixed methods. The Research Topic welcomes theoretical and empirical studies, reviews, methodological contributions, and design-based research across school, higher education, professional, and lifelong learning settings.Themes include, but are not limited to:- Cognitive mechanisms of learning with AI, including attention, memory, cognitive load, reasoning, executive function, and cognitive control- Metacognition, self-regulated learning, motivation, engagement, emotion, learner autonomy, and learner agency- Cognitive and developmental differences in responses to AI-supported learning across learner populations and educational stages- Adaptive learning systems, intelligent tutoring, generative AI, personalized feedback, and human-AI collaboration- Behavioral measurement, cognitive assessment, learning analytics, EEG/ERP, neuroimaging, and multimodal approaches- Effects of AI-supported learning on critical thinking, creativity, decision-making, well-being, and academic development- Inclusive and accessible approaches that support comprehension, participation, metacognition, and independent learning- Theoretical models linking learning processes, cognitive development, learner agency, and underlying brain-behavior mechanisms Topic editors: Lorna Uden, Gregory Siy Ching, Hsu-Wen Huang Source: https://www.frontiersin.org/research-topics/86581/the-cognitive-science-of-ai-supported-learning-mechanisms-development-and-learner-agency