Fred G. Martin

Summer '25 Office Hours

Hi, everyone! I started at UT San Antonio on August 1, 2023 as professor and chair of computer science. Beginning June 1, 2025, I am Interim Dean of our new College of AI, Cyber, and Computing, which will launch on September 1, 2025.

Dean’s Welcome. It is my privilege to serve the UT San Antonio community as your interim dean. I strive to support all of us—students, staff, and faculty—in pursuing our professional successes. I wish to foster an environment where all are respected and valued members of our community.

Please see information about the degree programs which will be stewarded by our new college and some of your questions answered here. Please email me to share any questions, ideas, and suggestions!

Future and prospective CS majors (and parents and other family members): please see my FAQs about our computer science undergraduate and graduate programs.

My Research. I create novel technologies to empower young learners in discovering computing, artificial intelligence, and data science. My students and I have designed robotics construction kits, a collaborative data visualization platform, and a virtual reality programming environment.

I work with K–12 teachers and school districts to bring these materials to their students. I collaborate with faculty in computer science, education, and psychology to create new technologies and curricula, and to study how people learn when using them.

My team is called the Engaging Computing Group—see our people, projects, and publications.

My Teaching. Since Spring 2024, I have been teaching CS 4953/5463 Developing AI Tools for K-12. Beginning in Fall 2024 I am co-teaching it with Drs. Ismaila Sanusi and Deepti Tagare. Students in our graduate programs, including the MS in AI, may take the graduate section as an elective.

Before UTSA, I was at the University of Massachusetts Lowell. I started in 2002 as an asst. prof. of computer science. After tenure, I did a lot of administrative service, including being an associate dean. Here’s my web page there.

selected publications

* = student under my supervision

Introducing Children to AI and ML with Five Software Exhibits

Saniya Vahedian Movahed*, James Dimino*, Andrew Farrell*, and 10 more authors

In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024

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Artificial intelligence (AI) and machine learning (ML) have a deepening impact in our world. For empowered citizenship and career readiness, elementary and middle school students need to understand these technologies. To provide engaging introductory experiences, we created five original interactive software exhibits introducing children to hands-on activities in AI and ML. The exhibits were tested by 125 elementary and middle school students (aged 7 to 14). Four themes emerged: Students recognized that AI and ML systems can process data from cameras (perception); they saw that these systems responded to their training input (trust); they appreciated the practical import of AI/ML systems (affective and cognitive attitudes); and students were introduced to models and modes (specialization). This paper presents our goals in creating the exhibits and results from our initial testing with children. Our work contributes to the literature on formal and informal activities for introducing AI and ML to young learners.
Envisioning AI for K-12: What Should Every Child Know about AI?

David Touretzky, Christina Gardner-McCune, Fred Martin, and 1 more author

Proceedings of the AAAI Conference on Artificial Intelligence, Jul 2019

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The ubiquity of AI in society means the time is ripe to consider what educated 21st century digital citizens should know about this subject. In May 2018, the Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) formed a joint working group to develop national guidelines for teaching AI to K-12 students. Inspired by CSTA’s national standards for K-12 computing education, the AI for K-12 guidelines will define what students in each grade band should know about artificial intelligence, machine learning, and robotics. The AI for K-12 working group is also creating an online resource directory where teachers can find AI- related videos, demos, software, and activity descriptions they can incorporate into their lesson plans. This blue sky talk invites the AI research community to reflect on the big ideas in AI that every K-12 student should know, and how we should communicate with the public about advances in AI and their future impact on society. It is a call to action for more AI researchers to become AI educators, creating resources that help teachers and students understand our work.
Computational Thinking for Youth in Practice

Irene Lee, Fred Martin, Jill Denner, and 5 more authors

ACM Inroads, Feb 2011

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Computational thinking (CT) has been described as the use of abstraction, automation, and analysis in problem-solving [3]. We examine how these ways of thinking take shape for middle and high school youth in a set of NSF-supported programs. We discuss opportunities and challenges in both in-school and after-school contexts. Based on these observations, we present a "use-modify-create" framework, representing three phases of students’ cognitive and practical activity in computational thinking. We recommend continued investment in the development of CT-rich learning environments, in educators who can facilitate their use, and in research on the broader value of computational thinking.