Advancing AI in Science Education

Advancing AI in Science Education

Envisioning Responsible and Ethical Practice

This edited volume offers a timely, domain-specific examination of how artificial intelligence (AI) is reshaping the foundations of science teaching and learning. As AI transforms scientific work, societal expectations, and the skills future citizens need, science education stands at a pivotal crossroads. This book highlights the major shifts AI is driving—redefining educational goals, reshaping classroom procedures, expanding learning materials, enabling dynamic assessment, and altering the competencies students must develop to thrive in an AI-driven world of scientific inquiry and decision-making.

Through critical analysis and vivid examples from core scientific practices, the authors reveal AI’s dual capacity to enrich and complicate science education. AI offers unprecedented personalization, efficiency, and access to authentic scientific practices, yet also raises concerns around fairness, transparency, privacy, accountability, and the preservation of human judgment. To navigate these tensions, this book introduces the

Responsible and Ethical Principles (REP)
framework, an action-oriented lens for guiding design, use, and governance that ensures AI advances equity, scientific integrity, and democratic participation. Scholars demonstrate how REP principles inform ethical goals, inclusive materials, trustworthy assessments, and transformative learning outcomes, sometimes constraining as well as enabling AI use as a partner rather than a replacement.

Ultimately,

Advancing AI in Science Education
argues that even as AI reshapes schooling, science education must remain fundamentally human. Empathy, creativity, ethical judgment, and shared meaning-making within scientific communities anchor responsible AI-supported learning and guide an equitable, human-centered future for science education.

This edited volume offers a timely, domain-specific examination of how artificial intelligence (AI) is reshaping the foundations of science teaching and learning. As AI transforms scientific work, societal expectations, and the skills future citizens need, science education stands at a pivotal crossroads. This book highlights the major shifts AI is driving—redefining educational goals, reshaping classroom procedures, expanding learning materials, enabling dynamic assessment, and altering the competencies students must develop to thrive in an AI-driven world of scientific inquiry and decision-making.

Through critical analysis and vivid examples from core scientific practices, the authors reveal AI’s dual capacity to enrich and complicate science education. AI offers unprecedented personalization, efficiency, and access to authentic scientific practices, yet also raises concerns around fairness, transparency, privacy, accountability, and the preservation of human judgment. To navigate these tensions, this book introduces the

Responsible and Ethical Principles (REP)
framework, an action-oriented lens for guiding design, use, and governance that ensures AI advances equity, scientific integrity, and democratic participation. Scholars demonstrate how REP principles inform ethical goals, inclusive materials, trustworthy assessments, and transformative learning outcomes, sometimes constraining as well as enabling AI use as a partner rather than a replacement.

Ultimately,

Advancing AI in Science Education
argues that even as AI reshapes schooling, science education must remain fundamentally human. Empathy, creativity, ethical judgment, and shared meaning-making within scientific communities anchor responsible AI-supported learning and guide an equitable, human-centered future for science education.

Chapters 2 and 11 are licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Highlights

• Integrates AI with 3D science learning and NGSS standards Offers groundbreaking framework for responsible AI use in science classrooms Guides educators in balancing innovation with accountability across curriculum, instruction, and assessment

Über den Autor

Xiaoming Zhai, Associate Professor in Science Education and AI, (courtesy) Associate Professor in Computer Science and in Statistics, serves as Directors of the AI4STEM Education Center and the National GENIUS Center at University of Georgia, USA. His research pioneers the use of AI to transform STEM education. He has published widely, serves as guest editor of various journals, chaired the 2022 and 2025 AI in STEM education conferences, and co-founds and -leads NARST’s RAISE group. He edited Uses of Artificial Intelligence in STEM Education (Oxford, 2024) and Artificial Intelligence in STEM Education Research (Springer, 2026). Dr. Zhai is a leading voice in shaping the future of AI for STEM education.

Kent J. Crippen, Professor of STEM Education at University of Florida, USA. His research advances a resilient STEM workforce by designing environments that immerse students in authentic science and engineering practices. The Crippen Research Group investigates learning and participation across interdisciplinary contexts, including extended reality, AI and data science, engineering design, and molecular modeling. With strong funding and national honors, including as AAAS Fellow, Crippen’s scholarship emphasizes innovation, integrity, impact, and teamwork. He serves as Editor-in-Chief of the Journal of Science Education and Technology, founding editor of the Advances in Technology-Rich Science Education book series, and co-leads NARST’s RAISE RIG.