The Role of AI in Assessment: Revolutionizing Education examines how artificial intelligence (AI) is transforming the evaluation of learning and addresses the urgent need for innovative assessment methodologies. It analyzes both the opportunities and the constraints of AI-driven assessment, responding to the growing demand for approaches that harness AI capabilities rigorously and responsibly.Adopting an interdisciplinary perspective, this book introduces foundational AI concepts, including reinforcement learning, neural networks, deep learning, and large language models, and makes these complex topics accessible to educators, researchers, and policymakers. Chapters on ethics, equity, and personalized learning provide a systematic treatment of AI's implications for educational measurement and accountability.With a practical and forward-looking orientation, this volume explores applications such as automatic item generation, automated essay scoring, game-based assessment, and test security. Case studies illustrate implementation strategies and provide guidance for integrating AI into contemporary assessment systems.This resource is designed for educators, researchers, psychometricians, administrators, and policymakers seeking to design, evaluate, and govern AI-enabled assessment frameworks. It is also well suited for graduate courses in educational technology, assessment, data science in education, and AI ethics.

The Role of AI in Assessment: Revolutionizing Education examines how artificial intelligence (AI) is transforming the evaluation of learning and addresses the urgent need for innovative assessment methodologies. It analyzes both the opportunities and the constraints of AI-driven assessment, responding to the growing demand for approaches that harness AI capabilities rigorously and responsibly.Adopting an interdisciplinary perspective, this book introduces foundational AI concepts, including reinforcement learning, neural networks, deep learning, and large language models, and makes these complex topics accessible to educators, researchers, and policymakers. Chapters on ethics, equity, and personalized learning provide a systematic treatment of AI's implications for educational measurement and accountability.With a practical and forward-looking orientation, this volume explores applications such as automatic item generation, automated essay scoring, game-based assessment, and test security. Case studies illustrate implementation strategies and provide guidance for integrating AI into contemporary assessment systems.This resource is designed for educators, researchers, psychometricians, administrators, and policymakers seeking to design, evaluate, and govern AI-enabled assessment frameworks. It is also well suited for graduate courses in educational technology, assessment, data science in education, and AI ethics.

The Role of AI in Assessment: Revolutionizing Education examines how artificial intelligence (AI) is transforming the evaluation of learning and addresses the urgent need for innovative assessment methodologies. It analyzes both the opportunities and the constraints of AI-driven assessment, responding to the growing demand for approaches that harness AI capabilities rigorously and responsibly.Adopting an interdisciplinary perspective, this book introduces foundational AI concepts, including reinforcement learning, neural networks, deep learning, and large language models, and makes these complex topics accessible to educators, researchers, and policymakers. Chapters on ethics, equity, and personalized learning provide a systematic treatment of AI's implications for educational measurement and accountability.With a practical and forward-looking orientation, this volume explores applications such as automatic item generation, automated essay scoring, game-based assessment, and test security. Case studies illustrate implementation strategies and provide guidance for integrating AI into contemporary assessment systems.This resource is designed for educators, researchers, psychometricians, administrators, and policymakers seeking to design, evaluate, and govern AI-enabled assessment frameworks. It is also well suited for graduate courses in educational technology, assessment, data science in education, and AI ethics.