This edited volume explores how artificial intelligence (AI) is transforming science education across multiple dimensions—including theoretical, pedagogical, ethical, and practical aspects. Aimed at science educators, curriculum developers, researchers, and policymakers, the book brings together 19 chapters authored by experts in science education, educational technology, and artificial intelligence. The book addresses a growing need for educational innovation in the age of AI, offering both conceptual insights and hands-on strategies to integrate AI tools into science teaching, learning, assessment, and teacher education. It introduces foundational AI concepts relevant to educational contexts, highlights prompt writing and engineering as emerging pedagogical skills, and discusses the ethical implications of AI use in classrooms. Key topics include the development of adaptive and data-driven learning environments, the role of AI in teaching the Nature of Science, and the integration of AI-supported tools to foster 21st-century competencies such as creativity, argumentation, data literacy, and scientific process skills. The book also presents AI-enhanced instructional strategies—ranging from flipped learning to drama-based science teaching—and showcases sample lesson plans suitable for K-12 and higher education contexts. By combining evidence-based research with application-focused examples, this book aims to support educators and decision-makers in navigating the rapidly evolving landscape of AI in education. It offers actionable insights to help stakeholders make informed decisions and design future-ready science education experiences. This volume is particularly relevant as science educators and systems worldwide grapple with how best to prepare students for an AI-augmented future. It provides a structured, interdisciplinary framework to harness AI’s potential while addressing associated pedagogical and ethical challenges.
This edited volume explores how artificial intelligence (AI) is transforming science education across multiple dimensions—including theoretical, pedagogical, ethical, and practical aspects. Aimed at science educators, curriculum developers, researchers, and policymakers, the book brings together 19 chapters authored by experts in science education, educational technology, and artificial intelligence. The book addresses a growing need for educational innovation in the age of AI, offering both conceptual insights and hands-on strategies to integrate AI tools into science teaching, learning, assessment, and teacher education. It introduces foundational AI concepts relevant to educational contexts, highlights prompt writing and engineering as emerging pedagogical skills, and discusses the ethical implications of AI use in classrooms. Key topics include the development of adaptive and data-driven learning environments, the role of AI in teaching the Nature of Science, and the integration of AI-supported tools to foster 21st-century competencies such as creativity, argumentation, data literacy, and scientific process skills. The book also presents AI-enhanced instructional strategies—ranging from flipped learning to drama-based science teaching—and showcases sample lesson plans suitable for K-12 and higher education contexts. By combining evidence-based research with application-focused examples, this book aims to support educators and decision-makers in navigating the rapidly evolving landscape of AI in education. It offers actionable insights to help stakeholders make informed decisions and design future-ready science education experiences. This volume is particularly relevant as science educators and systems worldwide grapple with how best to prepare students for an AI-augmented future. It provides a structured, interdisciplinary framework to harness AI’s potential while addressing associated pedagogical and ethical challenges.
Oktay Bektaş
Artificial intelligence in science education practices AI-based teaching tools for STEM classrooms Generative AI in science curriculum development Ethical use of AI in educational assessment Nature of Science instruction with artificial intelligence Adaptive learning frameworks using AI in schools AI-integrated flipped classroom strategies in science Drama-based learning and artificial intelligence in education Game-based science teaching with AI technologies Professional development in science education with AI Data literacy in secondary science education with AI tools AI-supported creativity and argumentation in science lessons Pedagogical frameworks for teaching science with AI Prompt engineering for science educators and students Personalized learning in science classrooms using AI