Constructing Epistemic AI Literacy: Detecting Epistemic Aims and Processes in Student-AI Co-Programming

构建认知型人工智能素养：在学生与人工智能协同编程中检测认知目标与过程

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-generated outputs, and regulate problem-solving strategies. 摘要： 在应用生成式人工智能（GenAI）时，认知思维在学生的学习过程中发挥着核心作用，特别是在编程情境下，学习者必须构建查询、评估并验证人工智能生成的输出，以及调节解决问题的策略。

This study introduces the conceptual framework of Epistemic AI Literacy (EAIL), reframing AI literacy as a process-oriented epistemic phenomenon that emerges through dynamic human-AI interactions across different domains. 本研究引入了“认知型人工智能素养”（Epistemic AI Literacy, EAIL）的概念框架，将人工智能素养重新定义为一种过程导向的认知现象，这种现象通过不同领域中动态的人机交互而产生。

Drawing on the AIR (epistemic aims, ideals and reliable epistemic processes) framework, this study examines how epistemic aims and epistemic processes are enacted in GenAI-supported co-programming activities and explores scalable approaches for operationalizing these constructs in interaction data. 本研究借鉴 AIR（认知目标、理想与可靠的认知过程）框架，探讨了在生成式人工智能支持的协同编程活动中，认知目标和认知过程是如何实现的，并探索了在交互数据中将这些构念操作化的可扩展方法。

Using a large dialogue dataset of human-AI co-programming, this study identifies observable dimensions of epistemic aims (i.e., mastery-oriented aims) and epistemic processes (i.e., outsourcing, explanation seeking, verification seeking, prompt monitoring, and epistemic justification). 通过使用大规模的人机协同编程对话数据集，本研究确定了认知目标（即掌握导向目标）和认知过程（即外包、寻求解释、寻求验证、提示词监控和认知辩护）的可观察维度。

The results reveal a prevalent lack of EAIL, with 78.8% of student-GenAI interactions relying on non-mastery-oriented aims and less reliable epistemic strategies like outsourcing and verification-seeking. 研究结果揭示了 EAIL 的普遍缺失，78.8% 的学生与生成式人工智能的交互依赖于非掌握导向的目标，以及诸如外包和寻求验证等可靠性较低的认知策略。

Conversely, only 11.1% of interactions showed high epistemic engagement, where mastery-oriented aims were coupled with advanced epistemic strategies like epistemic justification in a more reliable epistemic process. 相反，仅有 11.1% 的交互表现出高水平的认知参与，在这些交互中，掌握导向的目标与认知辩护等高级认知策略相结合，形成了一种更可靠的认知过程。