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 drivingredefining 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 AIs 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.
