探索学生对使用生成式人工智能辅助问题提出的看法
Exploring Students' Perceptions of Using Generative AI-Assisted Problem Posing
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中文总结 AI 辅助
本研究调查学生对生成式人工智能辅助问题提出的看法，发现提示工程培训可改善学生与生成式人工智能的互动，学生总体支持该方法，为推广相关培训及融入结构化学习奠定基础。
中文摘要 AI 辅助
问题提出是一种教学实践，要求学生生成新颖问题或对遇到的问题进行有意义的变式，它支持学习迁移并强化物理学科的问题解决技能。然而，生成物理问题可能颇具挑战性，尤其对新手学习者而言。本研究调查学生对一种方法的看法，该方法旨在促进学生使用生成式人工智能（Generative AI），以最大化其益处并限制风险。学生被介绍将生成式人工智能辅助问题提出作为一种自学技巧。本研究采用现象学方法，调查学生对培训如何塑造人工智能交互、对使用生成式人工智能进行问题提出的态度，以及学生如何看待将其融入个人学习实践的看法。研究结果表明，学生在接受提示工程（prompt engineering）技术培训后，感知到与生成式人工智能的互动发生了积极变化。本研究还揭示，学生对该问题提出技巧总体持积极看法，仅有一小部分学生对使用生成式人工智能存在犹豫。这些结果为更广泛地引入和采用生成式人工智能的培训方法，以及继续将生成式人工智能融入问题提出等结构化学习技巧奠定了基础。
英文摘要
Problem posing, a pedagogical practice that asks students to generate novel problems or meaningful variations to problems encountered, supports transfer of learning and strengthens problem-solving skills in physics. However, generating physics problems can be challenging, particularly for novice learners. This study investigates students' perceptions of an approach to facilitate their use of Generative AI in ways that maximize their benefits and limit risks. Students were introduced to Generative AI-assisted problem posing as a self-study technique. This study utilizes a phenomenological approach to investigate students' perceptions on how training shaped AI interactions, attitudes towards problem posing with Generative AI, and how students view its incorporation into personal study practices. Results of this study suggest that students perceived a positive change in their interactions with Generative AI after receiving training on prompt engineering techniques. This study also reveals that students hold generally positive views towards the problem-posing technique, with a smaller subset of students showing hesitations towards using Generative AI. These results lay the foundation to introduce and employ training methods for Generative AI more widely and to continue to incorporate Generative AI into structured study techniques, like problem posing.
