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Study Defines Epistemic AI Literacy for Student-AI Co-Programming

Mengqian Wu· July 2, 2026 View original

Summary

This research introduces Epistemic AI Literacy (EAIL) as a framework to understand how students interact with generative AI in programming, focusing on their epistemic aims and processes. It reveals a significant lack of mastery-oriented engagement and reliable strategies among students using AI for coding.

This study proposes a new conceptual framework called Epistemic AI Literacy (EAIL) to analyze how students engage with generative AI, particularly in programming tasks. EAIL views AI literacy as an evolving epistemic phenomenon shaped by dynamic human-AI interactions across various domains. The research applies the AIR framework (epistemic aims, ideals, and reliable processes) to examine how students' goals and methods manifest during AI-supported co-programming. Analyzing a large dataset of student-AI programming dialogues, the study identified key dimensions of epistemic aims, such as mastery orientation, and epistemic processes, including outsourcing, explanation seeking, verification seeking, prompt monitoring, and epistemic justification. The findings indicate a widespread deficit in EAIL, with a vast majority of student interactions exhibiting non-mastery aims and less reliable strategies like simple outsourcing or verification. Only a small percentage demonstrated high epistemic engagement, combining mastery goals with advanced justification strategies.

Why it matters

Understanding EAIL is crucial for educators and AI tool developers to design better learning environments and AI systems that foster deeper, more reliable learning and problem-solving skills in students and professionals.

How to implement this in your domain

  1. 1Integrate explicit instruction on critical evaluation and justification of AI outputs into AI-assisted learning curricula.
  2. 2Develop AI tools that prompt users for deeper reasoning and explanation-seeking rather than just output acceptance.
  3. 3Design educational activities that encourage mastery-oriented goals over simple task completion when using AI.
  4. 4Implement assessment methods that evaluate users' epistemic processes and not just the correctness of their final AI-assisted solutions.

Who benefits

EdTechEducationSoftware DevelopmentAI Development

Key takeaways

  • Epistemic AI Literacy (EAIL) describes how users critically engage with AI outputs.
  • Many students lack advanced EAIL, relying on superficial AI interaction strategies.
  • Mastery-oriented learning and robust epistemic processes are vital for effective AI use.
  • Educational approaches and AI tool design must evolve to foster better EAIL.

Original post by Mengqian Wu

"arXiv:2607.00211v1 Announce Type: new Abstract: Epistemic thinking plays a central role in students' learning processes when applying generative artificial intelligence (GenAI), particularly in programming contexts where learners must construct queries, evaluate and validate AI-g…"

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