arXiv cs.AI· Candace Walkington, Mingyu Feng, Itffini Pruitt-Britton, Theodora Beauchamp, Andrew Lan·· 3 小时前AI 评分32
研究探析：中学数学教师如何用 ChatGPT 生成个性化任务中的"教师在环"作用
Should There be a Teacher In-the-Loop? A Study of Generative AI-Personalized Tasks Middle School
AI 导读
一项研究让 7 名初中数学教师用 ChatGPT 将课程中的题目改写成贴合学生兴趣的个性化版本，并分析其提示词策略与学生的开放式反馈。结果显示，教师在环生成的个性化往往粒度较粗，而学生更偏好涉及自身流行文化兴趣的更细粒度定制；教师还通过提示词调整流行文化引用并修正题目的深度、伦理或真实性问题，展现出认知能动性。
正文 · 原文
Abstract:Large language models can be used to design instructional tasks to align to students needs. These generative AI models can create tasks that correspond to students out-of-school interests in areas like sports or music, which may enhance students interest in learning. However, little is known about teachers processes for creating or modifying tasks with generative AI, despite commercial AI companies claims that they will save teachers time. In the present study, 7 middle school mathematics teachers used ChatGPT to create personalized versions of problems in their curriculum to correspond to their students interests. The prompting moves teachers made and their students open-ended feedback on personalized problems were examined through thematic analysis. Teachers efficiency when creating problems and the ratings of their 7th grade students who received personalized assignments were examined. Results from this sample suggest that having a teacher-in-the-loop may result in generative AI-enhanced personalization being enacted at a broad grain size, whereas students often expressed preference for a smaller grain-size where they receive specific popular culture references that interest them. Teachers used prompting to adjust popular culture references and address issues with the depth, ethics, or realism of the problems generated, in some cases showing epistemic agency. The article closes with an exploratory, design-focused look at scalability trade-offs with teacher-facing personalization, patterns of teacher prompting practices, and opportunities for teachers to exercise epistemic and ethical monitoring of personalization outputs.
| Subjects: | Computers and Society (cs.CY); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2602.15876 [cs.CY] |
| (or arXiv:2602.15876v2 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2602.15876 arXiv-issued DOI via DataCite |
|
| Journal reference: | Educational Technology Research & Development (2026) |
| Related DOI: | https://doi.org/10.1007/s11423-026-10756-2
DOI(s) linking to related resources |
Submission history
From: Candace Walkington [view email]
[v1]
Mon, 2 Feb 2026 19:36:38 UTC (4,167 KB)
[v2]
Wed, 11 Nov 2026 22:10:09 UTC (827 KB)
来源：arXiv cs.AI · arxiv.org