Should There be a Teacher In-the-Loop? A Study of Generative AI-Personalized Tasks Middle School
Department of Teaching and Learning（教学与学习系）；Southern Methodist University（南方 Methodist 大学）；WestEd（西斯特教育）；American Institutes for Research（美国研究机构）；University of Massachusetts Amherst（马萨诸塞大学阿姆赫斯特分校）
Candace Walkington, Mingyu Feng, Itffini Pruitt-Britton, Theodora Beauchamp, Andrew Lan
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.
Probe Before You Preach: Conformal Ambiguity Sets and Neuro-Symbolic Counterfactual Probing for Diagnosing Algebraic Misconceptions in Middle School Mathematics
Integrated Science, Technology, Engineering and Mathematics (STEM) Education through Active Experience of Designing Technical Toys in Vietnamese Schools
The Illusion of Understanding: How Middle-Schoolers Fail to Regulate Inquiry with ChatGPT in a Science Task
Hector Research Institute, University of Tübingen（蒂宾根大学赫克托研究所）；Department of Psychology, University of California Berkeley（加州大学伯克利分校心理学系）；Inria Research center, University of Bordeaux（波尔多大学法国国家信息与自动化研究所研究中心）
A community-driven optimization framework for redrawing school attendance boundaries
Georgia Institute of Technology（佐治亚理工学院）；Northeastern University（东北大学）；University of Michigan（密歇根大学）；Winston-Salem/Forsyth County Schools（温斯顿-塞勒姆/福赛斯县学区）；Virginia Commonwealth University（弗吉尼亚联邦大学）
V-Math: An Agentic Approach to the Vietnamese National High School Graduation Mathematics Exams
CIRTech Institute, HUTECH University, Ho Chi Minh City, Viet Nam（CIRTech研究院，HUTECH大学，胡志明市，越南）；Faculty of Information Technology, HUTECH University, Ho Chi Minh City, Vietnam（信息科技学院，HUTECH大学，胡志明市，越南）；Nguyen Thai Hoc High School, Gia Lai Province, Vietnam（Nguyen Thai Hoc高中，嘉莱省，越南）；Office of Scientific Research, Technology Management and International Cooperation, Tien Giang University, Vietnam（科研办公室，技术管理与国际合作办公室，Tien Giang大学，越南）
本文提出自主智能体框架 V-Math，集成问题生成、求解解释与个性化导师三个 AI 智能体，支持越南高中生备考及教师辅助出题，初步评估显示其能高准确率生成合规考题并提供连贯解释。
Exploring Teachers' Perception of Artificial Intelligence: The Socio-emotional Deficiency as Opportunities and Challenges in Human-AI Complementarity in K-12 Education
Michigan State University（密歇根州立大学）；University of Pittsburgh（匹兹堡大学）
