bookmarks (hide)3633
- FreeDi - collaborative decision-making platform
- This collection of patterns is a practical resource for teachers and educational developers in higher education to support Connected Learning at Scale (CLaS). It offers educational design patterns and contextual examples that can be reused and adapted. Browse the site to access the patterns and learn about the CLaS project at the University of Sydney Business School.
- Versa is UCSF's secure generative artificial intelligence (AI) platform.
- Read Our Generative AI Playbook After six years of building AI-powered literacy tools and developing more than 300 unique AI models, we've distilled our most valuable insights into a comprehensive playbook that shares our entire process. For Education Leaders As you evaluate AI solutions for your schools, this playbook gives you the critical questions to ask vendors and the frameworks to assess if their tools are truly designed for student success. You'll understand what makes AI effective in educational settings and be able to distinguish between superficial AI implementations and those with deep pedagogical foundations. For EdTech AI Developers Skip years of trial and error by learning from our experience. We share our step-by-step development process, technical approaches, and proven methodologies for creating AI that truly enhances learning. From dataset creation to evaluation frameworks, you'll find actionable insights that can be applied immediately to your own AI development work. For Philanthropic Partners When funding educational AI initiatives, it's crucial to identify organizations with the expertise and ethical approach to create meaningful impact. Our playbook provides the evaluation criteria and key indicators of effective AI implementation, helping you direct resources to organizations genuinely capable of advancing educational equity through technology.
- The next generation of Conversational Agents uses the latest Gemini models, enabling human-like, high definition voices, comprehension, and the ability to understand emotions — so the AI agents can adapt during conversations. The product supports streaming video, so the AI agents can interpret and respond to what they see in real-time from customer devices. It will also simplify how AI agents are built, leveraging our latest Gemini models and Agent Development Kit, with a no-code console. Users will have a variety of tools to interact and perform specific tasks with other applications (like add to cart, and checkout) through API calls.
- The next-gen development platform - Easily build and operate generative AI applications. Create Assistants API and GPTs based on any LLMs.
- Cogniti is designed by educators, and built by educators, to empower educators. Create steerable and accurate agents powered by generative AI. Cogniti is designed to let teachers build custom chatbot agents that can be given specific instructions, and specific resources, to assist student learning in context-sensitive ways.
- NOLAI is the National Education Lab AI. Financed by the government, from 2022 to 2032 academics and businesses are working with primary, secondary and special needs education on using smart technology in the classroom.
- We are a first-in-the-nation office for AI policy, regulation and innovation, signifying Utah’s commitment to being at the forefront of AI policy and collaborative regulation. The office consults with businesses, academic institutions, and other stakeholders to facilitate dialogue on regulatory proposals to foster innovation and safeguard public safety. We also have authority to craft regulatory mitigation agreements that facilitate the deployment of AI in novel ways. Through these proactive measures, Utah is setting a new standard and leading the nation in AI innovation and regulation.
- 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.
- Turn your ideas into products, in minutes. The first all-in-one AI platform to easily build fully functioning apps - without coding.
- 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.
- AI tutors are here, but so far the research on efficacy is mixed. Here is some of the most intriguing research conducted so far.
- What the Research Says about AI Tutoring To kick-off this new WTRS series, I'm going to take a look at AI Tutors.
- Diffit is an AI tool teachers use to get “just right” instructional materials, saving tons of time and helping all students to access grade level content.
- Standards-aligned, differentiated, AI-powered lesson plans and classroom resources for teachers.
- Brisk is the best AI for teachers and schools, offering free AI tools for education that fit seamlessly into your routine. With an AI lesson plan generator and tools for instruction, feedback, and differentiation, Brisk helps lighten your workload. Grade essays before the bell or create lesson plans in seconds. Install now and thank yourself all year!
- Create and adapt classroom-ready educational resources in minutes with Monsha, the best AI tool for teachers, educators, and schools. Save valuable hours on course, unit, and lesson planning with ease. Generate and differentiate lessons, quizzes, worksheets, presentations, assessments and more.
publications (hide)3075
- Proceedings of the Annual Meeting of the Cognitive Science Society, 28, (2006)
- 3rd IEA International research conference TIMSS, page 1-18. (2008)
- Computers and Education: Artificial Intelligence, (2025)
- (2025)
- Cognitive Development, 15 (3): 309-328 (2000)
- Educational psychologist, 46 (3): 141-167 (2011)
- Journal of Educational Psychology, 114 (4): 734 (2022)
- Contemporary Educational Psychology, 29 (2): 186-204 (2004)Epistemological Development and Its Impact on Cognition in Academic Domains.
- Educational Psychology Review, 37 (2): 54 (Jun 4, 2025)
- National Bureau of Economic Research, (2025)
- Computers in Human Behavior Reports, (2025)
- Nature Communications, 16 (1): 4627 (May 19, 2025)
- Journal of China Computer-Assisted Language Learning, 4 (2): 300–325 (March 2023)
- Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, New York, NY, USA, Association for Computing Machinery, (2025)
- (2024)
- (2025)
- ICIS, (2021)
- ECIS 2022 Research Papers, 18, (2022)
- Proceedings of the 26th International Academic Mindtrek Conference, page 67–82. New York, NY, USA, Association for Computing Machinery, (2023)
- Interactive Learning Environments, 32 (10): 6928-6948 (2024)
