A one-credit AI literacy course designed for a broad university audience successfully improved participants' AI literacy and understanding across multiple dimensions.

Title and Authors: "The Essentials of AI for Life and Society: An AI Literacy Course for the University Community" by Joydeep Biswas, Don Fussell, Peter Stone, Kristin Patterson, Kristen Procko, Lea Sabatini, and Zifan Xu

Published On: January 13, 2025 Published By: Association for the Advancement of Artificial Intelligence (AAAI)

Objective: The main goal was to develop and implement a broadly accessible one-credit course about AI for non-technical audiences at The University of Texas at Austin, in response to increased public interest in AI following the widespread availability of large language model-based chat tools.

Methods:

• Developed a 14-week seminar-style course with interdisciplinary speakers
• Course included lectures on AI fundamentals and societal implications
• Open to university students, faculty, staff, and community members
• Collected feedback through weekly reflections and a final survey
• Used retrospective pre-post survey questions to evaluate AI literacy gains
• Course requirements included attendance, real-time quizzes, and weekly reflections
• Lectures were delivered online with recordings available afterward

Key Findings:

• High engagement with 788 total enrollments (132 undergraduates, 631 university auditors, 25 external participants)
• 81% of respondents found the course "very interesting" or "somewhat interesting"
• 73% of respondents indicated they would recommend the course to others
• Students showed significant improvements across all ten measures of AI literacy
• Course received above-average ratings compared to other College of Natural Sciences courses
• Participants particularly valued the variety of speakers and broad overview of AI
• Reading materials were found challenging by the non-technical audience

Implications:

• Demonstrates the feasibility of delivering AI literacy education to diverse audiences
• Provides a model for other institutions developing similar courses
• Shows the importance of institutional support and interdisciplinary collaboration
• Highlights the need for carefully calibrated content for non-technical audiences
• Supports the value of combining technical and societal perspectives in AI education

Limitations:

• Difficulty in satisfying diverse expectations of both students and auditors
• Challenge in maintaining engagement in a one-credit format
• Some technical readings were too advanced for the target audience
• Limited interactivity and community building in the online format
• Varying levels of engagement between credit students and auditors
• Attendance dropped from 387 to 170 participants over the semester

Future Directions:

• Development of a three-credit version of the course
• Revision of reading materials to be more accessible
• Integration of more interactive elements and student discussions
• Addition of hands-on assignments with AI tools
• Focus on building student community through collaborative activities
• Inclusion of more current news articles and real-world examples
• Implementation of collaborative annotation tools for discussions
• Development of non-programming assignments to familiarize students with AI technologies
• Integration of writing assignments focused on ethical implications
• Exclusive focus on enrolled students rather than mixing with auditors

The study provides valuable insights for institutions looking to develop AI literacy programs for broad audiences, emphasizing the importance of balancing technical content with accessibility and the need for carefully structured learning experiences that engage diverse learners.