
AI4STEM
@ai4stem
Fostering interdisciplinary collaboration in artificial intelligence for the advancement of STEM education.
ID: 1415018251029975047
https://coe.uga.edu/research/labs/ai4stem 13-07-2021 18:40:29
203 Tweet
121 Followers
293 Following


This paper by Xiaoming Zhai provides a framework that specifies teachers ' roles and agencies in the era of Genenerative AI—Observer, Adopter, Collaborator, and Innovator—each represents different levels of GenAI engagement in the classrooms rdcu.be/d0F3o

🎉New publication Alert! "Generative AI for Culturally Responsive Science Assessment: A Conceptual Framework" by MATTHEW NYAABA, Xiaoming Zhai & Morgan Z. Faison explores how AI can create culturally tailored K-12 assessments. 📄mdpi.com/2227-7102/14/1… #AI #Education #Science

Hurry!!! open access to Uses of Artificial Intelligence in STEM Education for a month Xiaoming Zhai UGA Mary Frances Early College of Education ~~ academic-marketing.oup.com/c/1b4XdsgZnBpT…

🎉 New publication alert! “Realizing Visual Question Answering for Education: GPT-4V as a Multimodal AI” in TechTrends. This work highlights the power of Vision Language Models in making education more efficient and inclusive. UGA Mary Frances Early College of Education Xiaoming Zhai doi.org/10.1007/s11528…


🚨 New Pub UGA Mary Frances Early College of Education ! 📄 “From Campus to Market: The Algorithmic Influence on Academic Capitalism” in IEEE Technology and Society Magazine! How are algorithms shaping decision-making, commercialization, and academic structures? 🔗 Read here: doi.org/10.1109/MTS.20…


🌍 AI4STEM UGA Mary Frances Early College of Education UGA Research hosted an NSF-funded International Conference on Advancing AI in Science Education, bringing together top scholars. Keynotes from Ryan Baker, Stephen Pruitt, Travis Allen & James Lester explored AI in personalized learning, policy, & ethics 🚀







🚨 A game-changer for teacher assessment! Can AI assess teachers’ pedagogical expertise? LLMs like ChatGPT can score teachers’ PCK as effectively as humans—with low bias across tasks and high consistency. Read AIED paper: arxiv.org/abs/2505.19266 UGA UGA Mary Frances Early College of Education

AI scoring systems may unintentionally penalize English Language Learners. Our new study reveals disparities in AI-driven assessments & shows how unbalanced data worsens bias. Urgent need for fairness in AI tools! Full paper: doi.org/10.48550/arXiv… UGA Mary Frances Early College of Education UGA


