An official website of the United States government
We describe the development of a one-credit course to promote AI literacy at the University of Texas at Austin. In response to a call for the rapid deployment of class that would serve a broad audience in Fall of 2023, we designed a 14-week seminar-style course that incorporated an interdisciplinary group of speakers who lectured on topics ranging from the fundamentals of AI to societal concerns including disinformation and employment. University students, faculty, and staff, and even community members outside of the University were invited to enroll in this online offering: The Essentials of AI for Life and Society. We collected feedback from course participants through weekly reflections and a final survey. Satisfyingly, we found that attendees reported gains in their AI literacy. We sought critical feedback through quantitative and qualitative analysis, which uncovered challenges in designing a course for this general audience. We utilized the course feedback to design a three-credit version of the course that is being offered in Fall of 2024. The lessons we learned and our plans for this new iteration may serve as a guide to instructors designing AI courses for a broad audience.
more »
« less
This content will become publicly available on January 13, 2026
The Essentials of AI for Life and Society: An AI Literacy Course for the University Community
We describe the development of a one-credit course to promote AI literacy at The University of Texas at Austin. In response to a call for the rapid deployment of class to serve a broad audience in Fall of 2023, we designed a 14-week seminar-style course that incorporated an interdisciplinary group of speakers who lectured on topics ranging from the fundamentals of AI to societal concerns including disinformation and employment. University students, faculty, and staff, and even community members outside of the University, were invited to enroll in this online offering: The Essentials of AI for Life and Society. We collected feedback from course participants through weekly reflections and a final survey. Satisfyingly, we found that attendees reported gains in their AI literacy. We sought critical feedback through quantitative and qualitative analysis, which uncovered challenges in designing a course for this general audience. We utilized the course feedback to design a three-credit version of the course that is being offered in Fall of 2024. The lessons we learned and our plans for this new iteration may serve as a guide to instructors designing AI courses for a broad audience.
more »
« less
- Award ID(s):
- 2505865
- PAR ID:
- 10631157
- Publisher / Repository:
- https://doi.org/10.48550/arXiv.2501.07392
- Date Published:
- ISSN:
- 2501.07392
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract As generative artificial intelligence (AI) becomes increasingly integrated into society and education, more institutions are implementing AI usage policies and offering introductory AI courses. These courses, however, should not replicate the technical focus typically found in introductory computer science (CS) courses like CS1 and CS2. In this paper, we use an adjustable, interdisciplinary socio‐technical AI literacy framework to design and present an introductory AI literacy course. We present a refined version of this framework informed by the teaching of a 1‐credit general education AI literacy course (primarily for freshmen and first‐year students from various majors), a 3‐credit course for CS majors at all levels, and a summer camp for high school students. Drawing from these teaching experiences and the evolving research landscape, we propose an introductory AI literacy course design framework structured around four cross‐cutting pillars. These pillars encompass (1) understanding the scope and technical dimensions of AI technologies, (2) learning how to interact with (generative) AI technologies, (3) applying principles of critical, ethical, and responsible AI usage, and (4) analyzing implications of AI on society. We posit that achieving AI literacy is essential for all students, those pursuing AI‐related careers, and those following other educational or professional paths. This introductory course, positioned at the beginning of a program, creates a foundation for ongoing and advanced AI education. The course design approach is presented as a series of modules and subtopics under each pillar. We emphasize the importance of thoughtful instructional design, including pedagogy, expected learning outcomes, and assessment strategies. This approach not only integrates social and technical learning but also democratizes AI education across diverse student populations and equips all learners with the socio‐technical, multidisciplinary perspectives necessary to navigate and shape the ethical future of AI.more » « less
-
Responsible AI (RAI) is the science and practice of ensuring the design, development, use, and oversight of AI are socially sustainable---benefiting diverse stakeholders while controlling the risks. Achieving this goal requires active engagement and participation from the broader public. This paper introduces We are AI: Taking Control of Technology, a public education course that brings the topics of AI and RAI to the general audience in a peer-learning setting. We outline the goals behind the course's development, discuss the multi-year iterative process that shaped its creation, and summarize its content. We also discuss two offerings of We are AI to an active and engaged group of librarians and professional staff at New York University, highlighting successes and areas for improvement. The course materials, including a multilingual comic book series by the same name, are publicly available and can be used independently. By sharing our experience in creating and teaching We are AI, we aim to introduce these resources to the community of AI educators, researchers, and practitioners, supporting their public education efforts.more » « less
-
As artificial intelligence (AI) profoundly reshapes our personal and professional lives, there are growing calls to support pre-college aged youth as they develop capacity to engage critically and productively with AI. While efforts to introduce AI concepts to pre-college aged youth have largely focused on older teens, there is growing recognition of the importance of developing AI literacy among younger children. Today’s youth already encounter and use AI regularly, but they might not yet be aware of its role, limitations, risks, or purpose in a particular encounter, and may not be positioned to question whether it should be doing what it’s doing. In response to this critical moment to develop AI learning experiences that can support children at this age, researchers and learning designers at the University of California’s Lawrence Hall of Science, in collaboration with AI developers at the University of Southern California’s Institute for Creative Technologies, have been iteratively developing and studying a series of interactive learning experiences for public science centers and similar out-of-school settings. The project is funded through a grant by the National Science Foundation and the resulting exhibit, The Virtually Human Experience (VHX), represents one of the first interactive museum exhibits in the United States designed explicitly to support young children and their families in developing understanding of AI. The coordinated experiences in VHX include both digital (computer-based) and non-digital (“unplugged”) activities designed to engage children (ages 7-12) and their families in learning about AI. In this paper, we describe emerging insights from a series of case studies that track small groups of museum visitors (e.g. a parent and two children) as they interact with the exhibit. The case studies reveal opportunities and challenges associated with designing AI learning experiences for young children in a free-choice environment like a public science center. In particular, we focus on three themes emerging from our analyses of case data: 1) relationships between design elements and collaborative discourse within intergenerational groups (i.e., families and other adult-child pairings); 2) relationships between design elements and impromptu visitor experimentation within the exhibit space; and 3) challenges in designing activities with a low threshold for initial engagement such that even the youngest visitors can engage meaningfully with the activity. Findings from this study are directly relevant to support researchers and learning designers engaged in rapidly expanding efforts to develop AI learning opportunities for youth, and are likely to be of interest to a broad range of researchers, designers, and practitioners as society encounters this transformative technology and its applications become increasingly integral to how we live and work.more » « less
-
Fostering public AI literacy has been a growing area of interest at CHI for several years, and a substantial community is forming around issues such as teaching children how to build and program AI systems, designing learning experiences to broaden public understanding of AI, developing explainable AI systems, understanding how novices make sense of AI, and exploring the relationship between public policy, ethics, and AI literacy. Previous workshops related to AI literacy have been held at other conferences (e.g., SIGCSE, AAAI) that have been mostly focused on bringing together researchers and educators interested in AI education in K-12 classroom environments, an important subfield of this area. Our workshop seeks to cast a wider net that encompasses both HCI research related to introducing AI in K-12 education and also HCI research that is concerned with issues of AI literacy more broadly, including adult education, interactions with AI in the workplace, understanding how users make sense of and learn about AI systems, research on developing explainable AI (XAI) for non-expert users, and public policy issues related to AI literacy.more » « less
