As artificial intelligence rapidly reshapes classrooms and workplaces, a university-led research team is working to ensure teachers and their students know how to use these tools responsibly and effectively.
Fred Martin, PhD, a UT San Antonio professor of computer science, and a cross-institutional team received a $300,000 grant from the National Science Foundation to lead Building Capacity for Teacher and Student AI Fluency in Middle Schools in Texas and New York. The project brings together faculty members from UT San Antonio, the University of the Incarnate Word and the University at Albany (SUNY), in partnership with Northside ISD in San Antonio and Schenectady City Schools in New York.
“We’re directly working with teachers as well as technology coaches and instructional technology specialists,” Martin said. “The team is helping unpack how AI works and supporting teachers as they decide how and when they want students to use it.”
Over the next two years, the research team will collaborate with 60 educators across seven middle schools to develop classroom-ready tools and lessons connected to core subject areas, including English language arts, science, history and math. Alongside curriculum development, researchers will study how teachers translate their growing understanding of AI into classroom practice and how those choices shape student learning.
Martin is a recognized leader in shaping how AI, data science and computational thinking are introduced to K-12 learners. His work focuses on designing innovative, learner-centered technologies that ensure complex computing concepts are accessible at an early age. Martin and his students have created robotics construction kits, a collaborative data-visualization tool and a virtual reality programming environment aimed at helping young learners actively explore how computing works.
For Julia Salazar, an eight-grade ELA-Academics and Pre-AP teacher at Dr. Hector P. Garcia Middle School, she immediately realized the potential of AI tools like ChatGPT when she first began using the platform in 2022. Not only did she see the use within her own profession as a teacher but the possibilities the tool could provide her students.
Salazar has implemented Class Companion, an AI tutor tool, with her Advanced ELA students when they compose essays. The tool allows streamlined feedback and suggestions on their writing, helping amplify Salazar’s teaching.
Martin emphasizes that AI has been shaping everyday life for decades. Technologies such as GPS navigation, image recognition and other machine learning systems that sort information into categories all rely on the same foundational concepts.
“AI has existed for about 50 years,” Martin said. “We want teachers to have a set of ideas to work with — from how machines categorize information to how language processing works — so they can introduce these concepts in meaningful ways. I’m very sensitive to that balance. There are real challenges in making sure AI supports learning rather than interferes with it.”
The project’s strength lies in its collaborative, interdisciplinary team. Principle investigators at the University of Albany Lijun Ni, PhD, an associate professor in computing education, and the University of the Incarnate Word (UIW) Lucretia M. Fraga, PhD, an associate professor of Instructional Technology, contribute complimentary expertise in computing and education research, helping shape curriculum that connects technical concepts with classroom practice. Ni’s work focuses on advancing computer science and AI education in K-12 settings through teacher professional development and research-practice partnerships. Fraga’s work focuses on integrating AI and emerging technologies into teacher preparation and instructional design, with an emphasis on ethical, practical and classroom-ready applications.
At UT San Antonio, postdoctoral fellow Deepti Tagare, PhD, brings deep experience in computer science education and instructional design, particularly the integration of computational thinking and AI literacy in K–12 classrooms. Her work centers on teacher readiness — ensuring educators feel confident and prepared to introduce these emerging concepts. Also from UT San Antonio postdoctoral fellow Ismaila Sanusi, PhD, specializes in computer science education, with a focus on making artificial intelligence and machine learning more accessible for young learners. His work spans educational technology, K–12 technology education, human-computer interaction, and the use of information and communication technology in learning environments.
