Fairfax, VA – George Mason is bridging research and practice on AI for education. On October 8, 2024, leading educators, policymakers, and AI experts gathered at George Mason University for the “AI and Data-Driven Decision-Making for Education Policy and Equity” convening. The event, held at Merten Hall on GMU’s Fairfax campus, focused on the rapidly growing role of AI in education and its potential to reshape school systems, streamline administrative tasks, promote data-driven decision-making, and prepare teachers and students for an AI-enabled learning environments.
At 9am, the fully packed Merten Hall Room 1201 was welcomed by Mason’s professor of education, Anne Holton, who together with Dean of College of Education and Human Development, Ingrid Guerra- López, and Mason’s inaugural Chief AI Officer, Amarda Shehu, opened up the event with inspiring open remarks. The event followed with a wide range of expert presentations and panel discussions. Roberto J. Rodriguez, Assistant Secretary for the Office of Policy Planning and Development at the U.S. Department of Education, provided insights on how federal education policy is responding to the rise of AI. David Myers, Deputy Superintendent and CIO of the Virginia Department of Education, shared their perspectives on how AI can be responsibly implemented to address specific challenges in education.
Throughout the day, panelists and experts provided key insights for school and district leaders, underscoring the importance of thoughtful AI integration. School leaders are increasingly adopting AI tools to reduce administrative burdens and enhance classroom efficiency. However, speakers cautioned that the implementation of these tools must prioritize student privacy and compliance with existing data governance policies, such as FERPA. Districts were encouraged to evaluate their current data infrastructure, ensure that AI tools are compatible with privacy regulations, and carefully pilot these technologies before implementing them on a larger scale.
The event also highlighted the importance of providing teachers with professional development to navigate the integration of AI in their work. This includes training on the safety and privacy aspects of AI tools, particularly when compared to widely available, free alternatives, and on how AI can be used to enhance teaching and learning. GMU faculty showcased promising research on the ways AI can enrich classrooms, such as generating differentiated learning materials and serving as virtual collaborators for students in subjects like mathematics. Still, attendees were reminded that while AI offers exciting opportunities, its integration must be done thoughtfully to avoid unintended consequences, particularly with regard to data privacy and educational equity.
One of the key concerns discussed was the potential for AI algorithms to perpetuate societal biases present in the data they are trained on. Several experts stressed that AI literacy curricula must address these limitations, ensuring that both students and teachers are aware of the challenges associated with AI-generated materials, including biased content and harmful stereotypes. This is a crucial aspect of preparing students to critically engage with AI, rather than accepting its outputs at face value.
Participants explored case studies where AI is already being used to solve problems in school systems, such as improving transportation logistics and enhancing lesson planning. The event concluded with a discussion on fostering collaboration between school districts and researchers, encouraging knowledge sharing and the development of AI strategies that can be scaled across different educational contexts. As a result of this convening, a community of practice will carry out the much-needed ongoing conversations.
The convening, organized by the AI and Data-Informed Education Policy Initiative (AIEP) at George Mason University, exemplified the university’s commitment to transdisciplinary collaboration and evidence-based policy development. AIEP, in partnership with EdPolicyForward and the Center for Advancing Human-Machine Partnership (CAHMP), leverages AI and advanced data analytics to address pressing challenges in education policy and equity.
