Science Literacy: Generative AI as Enabler of Coherence in the Teaching, Learning, and Assessment of Scientific Knowledge and Reasoning

2026-03-01

AI Summary

This study addresses the persistent disconnect among teaching, learning, and assessment in K–16+ science literacy education, which impedes the development of the scientific reasoning competencies demanded in the AI era. To bridge this gap, the work proposes an integrative educational framework centered on generative artificial intelligence as a core enabling technology, systematically unifying these three interrelated components to enhance the coherence and efficacy of science knowledge and reasoning instruction. By designing and implementing AI-augmented instructional and assessment tools, the project not only demonstrates the transformative potential of generative AI in fostering science literacy but also identifies critical implementation challenges. The findings contribute a theoretically grounded and practically viable pathway toward scalable, interdisciplinary AI-enhanced educational paradigms.

Technology Category

• Knowledge Representation and Reasoning: Qualitative Reasoning
• Natural Language Processing: Generation
• Philosophy and Ethics of AI: Artificial General Intelligence

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

Abstract

This chapter examines the potential of generative AI in enhancing science literacy across the K-16+ grade span, including its benefits as well as the conceptual and practical challenges that doing so presents. It begins with a discussion of what defines science literacy in the era of AI, including how AI has changed science and the demand for future citizens to be scientifically literate when AI is applied in their careers and lives. The chapter further discusses why science literacy presents such a challenge in K-16+ educational settings. It then develops an argument for the type of architecture needed for AI to assist in solving the problem by bringing coherence to the teaching, learning, and assessment of science knowledge and reasoning. Components of this architecture are illustrated with respect to the AI tools and capabilities needed for design and implementation. The chapter concludes with a consideration of what has been learned regarding both science literacy and AI, as well as what remains to be learned, including the research and development (R&D) needed, and the generalizability of this science literacy case to other disciplinary learning and knowledge domains.

Problem

• science literacy
• generative AI
• K-16+ education
• scientific reasoning
• coherence in education

Innovation

• Generative AI
• Science Literacy
• Coherence
• AI-enhanced Education
• K-16+ Learning