OpenAI Blog

Teaching students to think and learn through questions

The article announces an AI-powered initiative for educators, celebrating Teachers’ Day with resources in Brazilian Portuguese. It highlights the Study Mode feature, designed to help teachers facilitate active, step‑by‑step learning for their students.

OpenAI Blog
Aug 31, 2023

Teaching with AI

We’re releasing a guide for teachers using ChatGPT in their classroom—including suggested prompts, an explanation of how ChatGPT works and its limitations, the efficacy of AI detectors, and bias.

OpenAI Blog
Aug 26

Learning never stops: How AI makes learning continuous

OpenAI’s new report examines how students and educators are using ChatGPT to create a more continuous learning experience, extending support beyond traditional classroom settings. It highlights the role of AI in facilitating ongoing educational engagement and resource accessibility. The study showcases practical applications of AI tools in modern learning environments.

arXiv AI
Sep 28

Adapting for AI: How elementary teachers adjust their practices for an AI-integrated curriculum

The article examines how three elementary teachers implemented a conversational AI‑based curriculum using the ToyTalk platform during a three‑week summer camp. Over 13 instructional days, teachers employed adaptive practices—repair, differentiation, translation, and balancing—to navigate tensions among technology, learners, and instruction. Their understanding of AI and instructional roles evolved throughout the camp, leading to design implications for deploying conversational AI in elementary classrooms.

By Fasika Melese, Ruiyang Wu, Xinyue Cui, Joanna Perkins, Xiaoyi Tian, Tiffany Barnes, Shiyan Jiang
arXiv AI
Sep 18

Edustories: A Collection of Real-world Case Studies from Classroom Practices

Edustories is a dataset of 1,492 teacher‑written case studies that detail real elementary and high‑school classroom situations involving challenging student behavior, pedagogical interventions, and their outcomes. The collection is designed to enable research on AI assistance in collective teaching contexts, such as evaluating large language models’ ability to predict the success of teacher interventions. Comparative tests show that current models achieve 58% accuracy, below the 64% accuracy of human experts, indicating a gap between AI and human expertise in predicting classroom outcomes.

By Michal \v{S}tef\'anik, Jan Nehyba, Jirina Karasova, Martin Fico, Lucie \v{S}karkov\'a, Mark\'eta Ko\v{s}atkov\'a, David Kosatka
arXiv AI
Aug 19

Analysis of Types of Inquiries in Student-AI Interaction: A case study of two CS2 tasks

The study examines the nature of questions students pose to generative AI during two CS2 programming tasks, classifying 830 interactions into 18 categories based on the Graesser taxonomy. Results reveal that a limited set of question types dominates student inquiries and that the distribution of question types shifts significantly as the task progresses.

By Matin Amoozadeh, Amin Alipour
arXiv AI
Oct 2

Feedback Without the Wait: Piloting a Generative AI Practice Platform in a Large Maths Class

The paper describes a pilot study of a generative AI practice platform designed to give immediate, scaffolded feedback to students in a large mathematics class. By moving human oversight to the verification of solutions rather than real‑time grading, the platform aims to reduce delays while maintaining trust and accountability. The study investigates student engagement, perceived value, and reliability of the AI feedback, and explores how these findings might apply to other engineering subjects.

By Lili Chen, Gavin Buskes, Yuxin Ren, Chin Tong Leong