学生与人工智能互动的三条路径：面向高阶思维的约束优先设计
Three Pathways of Student-AI Interaction: Constraint-First Design for Higher-Order Thinking
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中文总结 AI 辅助
本文提出学生-AI互动三条路径框架及下一代教学蓝图，通过定性分析验证，旨在促进高阶思维。研究识别三种互动模式，并表明教学框架可能影响学生路径选择。
中文摘要 AI 辅助
在教育环境中，学生如何与人工智能（AI）系统互动，可能决定这种互动是支持还是取代批判性思维。本文提出两项贡献。第一项是“学生与AI互动的三条路径”（Three Paths of Student-AI Interaction），这是一个类型学框架，识别出学生与AI互动的三种性质不同的模式：被动回顾（Passive Review）、直接提问（Direct Question）和策略性对话（Strategic Dialogue）。第二项是“下一代教学蓝图”（Next Level Teaching Blueprint, NLTB），这是一个三阶段教学设计系统，旨在使策略性对话更可能发生。研究对来自一门本科生研究方法课程的50条随机抽样的学生-AI互动消息进行了定性内容分析，以检验该类型学。两位人类编码者实现了68%的路径层面一致性（κ=.48），其中在策略性对话识别上的一致性为80%。作为第三编码者的GPT-5产生了类似的总体分布，并引入了一个人类方案中缺失的编码类别。在主要研究者的分类中，路径1（被动回顾）占交流的46%，路径2（直接提问）占18%，路径3（策略性对话）占36%。第二个描述性检查的数据集主要包含策略性对话内容，初步表明教学框架可能影响学生采取哪条路径。总之，三条路径框架和NLTB共同提供了一种描述学生-AI互动的语言，以及一种支持高阶互动的设计方法。
英文摘要
How students interact with artificial intelligence (AI) systems in educational settings may determine whether that interaction supports or displaces critical thinking. This paper introduces two contributions. The first is the Three Paths of Student-AI Interaction, a typological framework identifying three qualitatively distinct modes of student-AI engagement: Passive Review, Direct Question, and Strategic Dialogue. The second is the Next Level Teaching Blueprint (NLTB), a three-stage instructional design system intended to make Strategic Dialogue more likely. Qualitative content analysis of 50 randomly sampled student-AI interaction messages from an undergraduate research methods course was used to examine the typology. Two human coders achieved 68% path-level agreement ($κ$ = .48), with 80% agreement on Strategic Dialogue identification specifically. GPT-5, used as a third coder, produced a similar overall distribution and introduced a coding category absent from the human scheme. Path 1 (Passive Review) accounted for 46% of exchanges in the primary researcher's classifications, Path 2 (Direct Question) for 18%, and Path 3 (Strategic Dialogue) for 36%. A second, descriptively examined dataset contained predominantly Strategic Dialogue content, offering a preliminary indication that instructional framing may influence which path students take. Together, the Three Paths framework and the NLTB contribute a language for describing student-AI interaction and a design approach for supporting higher-order engagement.
发表机构
- University of Tennessee, Knoxville（田纳西大学诺克斯维尔分校）
机构由 AI 辅助整理，请以论文原文为准。
