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[2602.18471] Charting the Future of AI-supported Science Education: A Human-Centered Vision
Summary
This article discusses the transformative potential of AI in science education, proposing a human-centered framework for its ethical integration, focusing on educational goals, instructional practices, and the evolving roles of teachers and learners.
Why It Matters
As AI continues to influence various sectors, its role in education is critical. This article highlights the need for responsible AI integration in science education, ensuring that it enhances learning while upholding ethical standards and equity. It addresses the importance of redefining scientific literacy to include AI literacy, preparing students for a future where AI is prevalent.
Key Takeaways
- AI can enrich inquiry and personalize learning in science education.
- A human-centered framework is essential for the responsible integration of AI.
- Redefining scientific literacy to include AI literacy is crucial for future learners.
- Teachers' roles will evolve in AI-supported classrooms, necessitating new instructional strategies.
- Critical engagement with AI is needed to prevent reinforcing existing inequities.
Computer Science > Computers and Society arXiv:2602.18471 (cs) [Submitted on 9 Feb 2026] Title:Charting the Future of AI-supported Science Education: A Human-Centered Vision Authors:Xiaoming Zhai, Kent Crippen View a PDF of the paper titled Charting the Future of AI-supported Science Education: A Human-Centered Vision, by Xiaoming Zhai and Kent Crippen View PDF Abstract:This concluding chapter explores how artificial intelligence (AI) is reshaping the purposes, practices, and outcomes of science education, and proposes a human-centered framework for its responsible integration. Drawing on insights from international collaborations and the Advancing AI in Science Education (AASE) committee, the chapter synthesizes developments across five dimensions: educational goals, instructional procedures, learning materials, assessment, and outcomes. We argue that AI offers transformative potential to enrich inquiry, personalize learning, and support teacher practice, but only when guided by Responsible and Ethical Principles (REP). The REP framework, emphasizing fairness, transparency, privacy, accountability, and respect for human values, anchors our vision for AI-supported science education. Key discussions include the redefinition of scientific literacy to encompass AI literacy, the evolving roles of teachers and learners in AI-supported classrooms, and the design of adaptive learning materials and assessments that preserve authenticity and integrity. We highlight both opportuniti...