Preparing K–12 Students With AI Literacy: Proposed Framework, Progression, and Task Design Principles

Authors

  • Srijita Chakraburty Indiana University Author
  • Teresa Ober ETS Research Institute Author
  • Lei Liu ETS Research Institute Author

DOI:

https://doi.org/10.64634/46jn1p41

Keywords:

AI literacy, K-12 education, skills assessment, skills progresion, task design

Abstract

This paper presents a conceptual framework for AI literacy, a hypothesized learning progression, and assessment design principles for advancing AI literacy among K–12 learners. Recognizing the importance of technical competencies alongside ethical awareness, the framework integrates foundational knowledge, societal implications, and practical applications of AI. Key competencies include ethical decision-making, AI-powered collaboration, and critical evaluation of AI outputs. Developed through an evidence-centered design (ECD) process involving a review of existing literature and frameworks, the proposed AI literacy framework and progression maps a hypothesized trajectory of students’ skill development, providing a structured pathway for improvement with behavior indicators connected to core AI literacy subskills. In this way, the framework and progression may offer educators a roadmap to apply scaffolded and differentiated teaching strategies that actively foster learners’ skill acquisition. To further support connections between assessment and instruction, we introduce three design principles for task design: ensuring relevance to learners, minimizing barriers to resource access, and providing opportunities for skill advancement. These design principles may guide the creation of activities that evaluate and enhance students’ AI literacy. By aligning scaffolded assessments and learning activities with the progression, this framework bridges instruction, assessment, and students’ skill development. It ultimately may be used to support students in developing skills to critically and ethically engage with AI technologies, preparing them to navigate the digital landscape by fostering inclusive instruction that deepens students’ understanding of AI concepts.

Chakraburty, S., Ober, T. M., & Liu, L. (2025). Preparing K–12 students with AI literacy: Proposed framework, progression, and task design principles (Research Report No. RR-25-14). ETS. https://doi.org/10.64634/46jn1p41

 

Author Biographies

Cover of ETS Research Report Series No. RR-25-14 Preparing K–12 Students With AI Literacy:  Proposed Framework, Progression, and  Task Design Principles

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Published

2025-11-21