Higher Education’s Role in Supporting K–12 AI Literacy

“On the technical side, students build a strong data foundation by learning Python and progressing from basic coding concepts into working with structured data sets using tools like Pandas,” says Caryn Preston, assistant director of the Office of Youth Experiences for USF. “They also examine the ethical challenges associated with AI, including hallucinations and deepfakes. There’s a strong emphasis on collaboration, problem-solving and communication.”

USF’s newest college, the Bellini College of Artificial Intelligence, Cybersecurity and Computing (established in March 2025), plays a lead role in shaping the curriculum, delivering instruction and offering mentorship to participating students. Working with the Office of Youth Experiences staff, Bellini College faculty help develop and gamify the program’s curriculum so it’s more fun and engaging for high school students. Students benefit from the faculty’s direct participation.

“Students interact with experts in the field, researchers who are doing the work of discovering new technologies and working with cutting-edge tools,” Preston says. “They also get the unique experience of leaving the camp with connections to experts in the field. Knowing a faculty member can help them with future career exploration.”

Key to the success of USF’s summer program is its ongoing relationships with the local community, including the school districts of surrounding Hillsborough County and nonprofit organizations. These local partnerships help ensure that even financially challenged students can participate. They also help surface exactly how K–12 educators are teaching with AI and identifying where USF’s program can focus its AI literacy improvement efforts.

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“It’s helpful to know from educators in the classroom where the gaps are in AI education,” Preston says. “They really guide us on where to focus our curriculum. We hire many teachers over the summer, and they tell us what concepts they taught during the school year and where we can level up. This really extends the students’ learning in a more meaningful way.”

Building an Understanding of AI Literacy

While higher education institutions are actively leading AI research and policy development efforts, they are often in the process of figuring out governance and how to accommodate the technology themselves on their own campuses. This presents a unique challenge for universities with programs focused on K–12 AI literacy.

“The rapid rate of change with AI is an issue,” says Jenay Robert, senior researcher for EDUCAUSE. “As a community, higher education has not quite reached a common understanding or a shared set of goals around AI literacy. Not having clarity on that target makes it hard for people to collectively work toward something.”

An additional challenge to advancing AI literacy is the widespread impact of the technology.

“AI touches so many different areas of an educational organization,” Robert says. “We have to think about data privacy and security; education regulations; and laws that are specific to education, pedagogical expertise and subject matter expertise. And the technology itself comes with a whole host of its own types of expertise that we need to be aware of.”

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AI continues to evolve at a rapid pace, making it difficult to plan out effective strategies for guiding both K–12 teachers and students on what they need to know. With so much in flux, Robert suggests, universities should focus on a simple, uncomplicated approach to AI.

“What we’ve seen in our research and in the work we’ve done with our members is that successful AI literacy initiatives rely on some very basic principles,” she says. “This includes the ethical use of AI, understanding what makes AI trustworthy or not and being able to spot where AI is being leveraged when it’s not always transparent. These basic principles are unlikely to change significantly in the near term.” 

Purdue University’s AI in P–12 Education Expands AI Literacy

Purdue University’s College of Education responded to the meteoric arrival of ChatGPT in late 2022 by establishing its AI Working Group in 2023.

This group, composed of interdisciplinary researchers and faculty with backgrounds that bridge AI, data science and education, helps guide the college in training its students in the use of AI tools. In addition, it provides training and professional development to school-based professionals and engages in wide-ranging research that leverages AI tools to collect and analyze data to improve teaching and learning.

The AI Working Group established the Purdue AI in P-12 Education Conference in 2024.

“We had our second conference in November 2025 and are reaching hundreds of educators each year, bringing them together to have important conversations and share their own successes,” says William R. Watson, chair of the College of Education AI and Data Science Working Group at Purdue and organizer of the conference.

“It’s really valuable to establish a time and place each year where educators can come together and learn from each other,” he says. “Our faculty and graduate students share implications from their research, and our teacher presenters bring insights from their experiences using AI to support their teaching and impact their classrooms.”

Conferences such as the Purdue AI in P–12 Education Conference help expand AI literacy among the K–12 educators and administrators tasked with implementing the technology in their schools and classrooms. Recent research on AI for education highlights how important an understanding of the technology is to maximize its value in the classroom.

“AI is not a guarantee of learning but is instead reliant on how it is used to maximize learning,” Watson says. “When used soundly and ethically, AI is a tool that helps teachers and students transform learning, making it personalized and focused on critical thinking and problem-solving. It’s crucial that we help educators understand how the technology simultaneously equips students to learn both more and less than ever before. That is entirely based on how the tools are implemented.”

Stanford’s AI Hub for Education Is a Home for AI Research

With its vast research resources that span both AI technology and educational pedagogy, higher education has a unique role to play in improving AI literacy among K–12 teachers and students. Stanford University exemplifies this role with its AI Hub for Education, a research-driven initiative that partners with school districts, policymakers and platform developers to leverage available data and research the technology’s effects on educational practices.

K–12 administrators and instructors can go to the hub to access the latest research available to help guide AI policymaking and classroom use.

“Our flagship tool is our Research Study Repository, which strives to include all of the research related to AI and K–12 that exists,” says Chris Agnew, managing director of the hub. “It’s searchable and queryable and updated monthly. We’ve also started sharing early insights and research briefs based on real data that provide directional summaries into where practitioners are finding value and where they are not.”

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One recent insight shared through the AI Hub for Education highlights the importance of AI implementation across the curriculum versus via a single, dedicated technology class.

“The Organisation for Economic Co-operation and Development and the European Commission released AI literacy guidance last year, providing one of the first frameworks for moving AI literacy from a one-and-done class to incorporating it throughout the curriculum,” Agnew says.

The AI Hub for Education fills an important role for K–12 educators, who often don’t have the time or resources for in-depth professional development to help inform their decision-making with AI. The success of Stanford’s hub shows that universities can serve as neutral arbiters of research data and best practices, providing a valuable alternative resource for guidance on using these tools.

“Much of the innovation right now is happening in the private sector, partially because large language models are really expensive,” Agnew says. “K–12 districts don’t have the expertise or bandwidth to do their own research. So, higher education fits right in there as a research partner to support districts and these AI products, advocating for how to best improve learning.”