This volume captures a pivotal moment in education: the emergence of AI as both a transformative tool and a significant disruptor. AI has become deeply embedded within classrooms, examinations, tutoring platforms, and policymaking. This volume adopts an interdisciplinary approach, integrating psychometrics, cognitive science, classroom practice, AI engineering, and ethics to explore the impact of AI affordances. It examines how we define fairness, creativity, and equity in an AI-driven landscape, addressing questions of critical importance to researchers, policymakers, and practitioners alike. 
“This volume, edited by Alina von Davier and Duanli Yan, makes a major contribution because it addresses the developments in AI in education and human learning with breadth, rigor, and conceptual seriousness. The topic is expansive, the implications are substantial, and the field is moving quickly. Few edited collections could do justice to that combination of urgency and complexity. This volume manages to do so with impressive breadth and coherence. The volume brings together an outstanding group of authors across psychometrics, cognitive science, learning sciences, classroom practice, language assessment, and artificial intelligence. The result is a collection that captures the complexity of the present moment while offering a clear account of how AI is reshaping learning and assessment.” 
-----  Dragan Gašević

Dr. Alina A. von Davier is the Chief of Assessment at Duolingo, where she provides strategic leadership for the Duolingo English Test. She is also the Founder and CEO of EdAstra Tech, a partner with LearnLaunch Accelerator, and a renowned researcher specializing in computational psychometrics, and AI for educational applications. An executive leader with expertise in building exceptional R&D teams, she serves as a board member, strategic advisor, and investor, bringing extensive technology and commercial acumen, and sector insight to EdTech organizations globally.

Dr. Duanli Yan is an innovative researcher at Measurement Incorporated, where she focuses on AI-based applications in educational assessment. She previously served as the Director of Data Analysis and Computational Research at ETS, where she led evaluations for automated scoring engine upgrades. Dr. Yan possesses extensive expertise in adaptive testing, psychometric research, test security, and the implementation of emerging technologies.

The editors have published extensively in peer-reviewed journals and authored several influential books. Their co-edited volume, Computerized Multistage Testing: Theory and Applications (2014), received the 2016 AERA Division D award for Significant Contribution to Educational Measurement.