Ethics-Focused AI Literacy Course Beats National Completion Rates

Aleshia Hayes built her career at the intersection of computer science, game development and education. Now her work is helping shape how universities teach AI to broad campus audiences, emphasizing how to use it responsibly.

Hayes, clinical associate professor at SMU Guildhall, co-authored the chapter "AI Fundamentals: Building AI Literacy Through a Microlearning Mircrocredential for the Broader Campus Community" in the newly published volume Mapping the STEM Microcredential Landscape, Volume II, which examines the design and outcome of "Demystifying Artificial Intelligence," a free online course she designed and built while on the faculty at the University of North Texas.

The course drew more than 2,000 members of the UNT campus community, including students, faculty and staff, and achieved a 75% completion rate between June 2024 and June 2025. That figure far exceeds the 25% to 67% range typical of massive open online courses. Eighty-six percent of learners who completed an exit survey said they would recommend the course to a friend or colleague.

"A focus of my work is making complex things simple for different audiences," Hayes said. "I was really excited about taking something that mattered to the campus community and making it accessible, whether you’re a computer science professor or someone who had never thought about how AI works."

Starting with the Basics of AI

The course was structured as a series of short, self-contained modules completable in three to five hours on any internet-connected device. Its nine learning objectives ranged from defining artificial intelligence and identifying different types of AI to understanding how data powers these systems and applying ethical frameworks to evaluate them.

Hayes said building the course took far more time than she anticipated, in part because she was determined to trace AI to its roots. Artificial intelligence is not a recent invention, she noted. The concept of simulating intelligence dates back decades, with non-player characters in video games serving as an early and familiar example.

"We’ve been working on artificial intelligence for as long as we’ve had computers," Hayes said. "Even in the early game, Pac-Man, the ghosts are AI-driven. I wanted people to understand that this isn’t magic that arrived overnight."

The course also covered how AI systems are trained on existing data, how sensors inform AI systems, and specialized fields such as computer vision, machine learning and neural networks, as well as the real-world ethical implications of AI use, including algorithmic bias, data privacy, environmental impacts, and accountability.

Aleshia Hayes, clinical associate professor at SMU Guildhall. 

The Ethics Question of AI

For Hayes, the ethics component was not an afterthought, but a central focus for the course. As AI tools show up in more classrooms and workplaces, she said universities have an obligation to prepare students not just to use AI, but to use it thoughtfully.

"We should not just be teaching folks how to use AI tools. We need to also be teaching how to be considerate of the ethical implications and tradeoffs when using these different tools that are emerging and changing regularly," she said. "Every day online there are new applications of AI and new AI tools, and people are asking, what does my future look like? And the answer is: your future is going to be shaped by tools and our capacity to implement them ethically and effectively."

That view shapes how Hayes approaches her work at SMU Guildhall, where game development students are training for an industry where creativity and human connection are skills that no algorithm can replace.

Educators and the Rise of AI

Hayes said the rise of generative AI has pushed educators to reconsider how they measure student learning. Rather than zeroing in on whether AI was used to complete an assignment, she favors multiple forms of assessment that require students to show they "know" and understand and can apply the material. She also points to the depth of engagement in the UNT course as a sign that people want to wrestle with the ethical questions AI raises.

The course's final discussion prompt asked learners to reflect on the societal impacts and ethical challenges posed by AI and whether some concerns are overblown. Responses had no minimum word count and were graded on complete/incomplete, but ran far longer than expected, with many responses that were paragraphs in length.

Hayes and her co-authors suggest the course offers a model university communities can follow to build AI literacy across a wide range of learners, from first-year undergraduates to senior faculty. The course applied a universal design for learning approach, keeping content accessible to beginners while still offering enough depth for more technical audiences. Those who completed the course received a digital badge that could be added to their resume or LinkedIn profile.

Hayes said she hopes the course, and the research behind it, continues pushing higher education toward a more intentional relationship with AI.

"If we use AI correctly, in a way that is ethical, then it will be doing the stuff that humans don’t want to do or don’t thrive at, and we’ll be able to really flourish in the things we’re good at," she said.

The chapter was co-authored with Brady Lund and Benjamin Brand of the University of North Texas.