Implications of artificial intelligence in learning and education
- Submission status
- Open
- Submission deadline
Artificial Intelligence (AI) has the potential to revolutionize learning and teaching, introducing a new and unfamiliar type of learner. Such technology is fundamentally a tool for our disposal, and like any tool, we must understand how it works and how best to deploy it.
This special Collection in npj Science of Learning invites research on the functional operation and capability of modern AI, and the consequent implications of its use as a technology to enhance learning and pedagogy. We particularly welcome articles that examine AI's strengths, weaknesses and opportunities in teaching and learning, and those that address ethical, societal, and broader educational considerations associated with its implementation.
We will consider theoretical work and review papers, and give highest priority to empirical studies on human-AI interaction. We will not consider work focused only on AI, e.g; algoritm analysis. Please see here for guidance.
Editors
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Benjamin Ultan Cowley, PhD
Faculty of Educational Sciences, University of Helsinki, Finland.
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Darryl Charles, PhD
Senior Lecturer in Games Design, School of Arts & Humanities, Faculty of Arts, Humanities & Social Sciences, Ulster University, Northern Ireland
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Xiaoqing Gu, PhD
Professor, Head of Department of Educational Information Technology, East China Normal University, Shanghai, China
Dr. Benjamin Cowley is an Associate Professor for AI in Learning and Education at the Faculty of Educational Sciences, University of Helsinki, and also a Docent of cognitive science. He has a background in Computer Science, and works at the intersection of these areas, leading his group HiPerCog to study how we learn to perform cognitive tasks to a high level. The group uses methods from computational modelling to psychophysiology and cognitive neuroscience, to conduct studies on the gamut of cognitive performance, from domain experts, to regular individuals developing skills, to the clinical population of ADHD.
Dr. Darryl Charles is a Senior Lecturer in Game Design at Ulster University where his core interest is in Artificial Intelligence and Creative Technologies. His interests include machine learning in games, intelligent interactive digital storytelling, player profiling & and adaptive gameplay, and serious applications of virtual reality. Recently, he has been focusing on AI procedural content generation and especially the rapid development of applications using Large Language Models (LLMs). He is a member of Ulster’s AI and Learning Workgroup, which is looking at the impact of existing and emerging AI technologies on learning and teaching.
Dr. Xiaoqing Gu is a Professor and Head of Department of Educational Information Technology at East China Normal University, Shanghai, China. Her research interests include learning science and learning technology, computer-supported collaborative learning (CSCL), learning analytics and leaner profiling, ICT-integrated pedagogical innovation.
