A comprehensive collection of academic research on generative AI in preK12 education organized into three categories:
Descriptive - Research that describes how generative AI is being used in classrooms, schools, or districts or how products are designed and built.
Impact (includes RCT + Quasi-Experimental) - Studies that test how well something works including but not limited to randomly dividing people into groups and comparing the results.
Review - Studies that combine and summarize all the research on a specific genAI topic to find patterns and answers.
We aim to include all research in the above categories on generative AI in preK12 education in the US. As research diverges from genAI for preK12 in the US - such as machine learning, education systems beyond preK12, or studies conducted outside the US - inclusion in the repository is based on relevance to our target audiences:
Superintendents, state, and federal K12 leaders
Education support organizations (unions, parent groups, etc.)
Leadership and product teams at technology companies
Academic researchers
Global education leaders
The Research Repository includes pre-published works but does not include journalism on AI for education.
Our goal is to establish a dynamic community of practice that will challenge and positively shape the future of AI in education. Thank you for joining us, your contributions are valued and appreciated.
The AI in Education at Oxford University (AIEOU) interdisciplinary research hub is led by Dr Sara Ratner (Principal Investigator), Professor Rebecca Williams (Co-Investigator) and Professor Elizabeth Wonnacott (Co-Investigator) thanks to an award from the Social Sciences Division with the support the Department of Education at the University of Oxford.
AIEOU aims to promote a research-informed, ethical, human-centered approach to AI in Education through collaboration and knowledge exchange. Working across the four pillars of design, regulation, implementation and impact, researchers at the University of Oxford will collaborate and convene with expert colleagues and key stakeholders from around the world to establish a shared research agenda. We seek to co-create a use case for AI in Education that represents best practice in quality teaching and learning.
John Hopfield e Geoffrey Hinton fizeram "descobertas fundamentais e invenções que permitiram o aprendizado de máquina por meio de redes neurais artificiais", afirma comissão do prêmio