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The Essentials of AI for Life and Society: An AI Literacy Course for the University Community
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Describes the design, delivery, and retrospective pre-post evaluation of a rapidly deployed 14-week AI literacy course for the broad UT Austin community, and the redesign into a 3-credit version.
Problem
Providing AI literacy education to a broad, non-technical university audience (students, staff, faculty, community members) amid rising public interest in AI after the release of LLM chat tools.
Approach
A one-credit, interdisciplinary, guest-lecture-based online course that covers both technical AI fundamentals and societal/ethical implications for non-technical learners, with feedback from weekly reflections and retrospective pre-post surveys used to guide a redesigned 3-credit, student-only version.
Key results
- Retrospective pre-post survey (n=151) showed significant AI literacy gains on all ten items, with increases from +0.97 to +1.37 on a 5-point scale (p < 0.01).
- Course Evaluation Survey ratings were 4.23 for the overall course and 4.33 for the instructor, versus 4.00 and 4.20 for College of Natural Sciences courses that term.
- 788 people signed up (132 undergraduates for credit, 631 university auditors, 25 external), and 51% of survey respondents found the readings difficult.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: define AI | Likert rating: +1.27 | Helped |
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: AI vocabulary | Likert rating: +1.36 | Helped |
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: list five AI examples | Likert rating: +1.37 | Helped |
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: AI in daily life | Likert rating: +0.97 | Helped |
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: apply AI to future professional work | Likert rating: +1.24 | Helped |
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: weigh in on AI deployment | Likert rating: +1.29 | Helped |
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: evaluate AI news stories | Likert rating: +1.19 | Helped |
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: differentiate AI science from science fiction | Likert rating: +1.03 | Helped |
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: technical AI literacy | Likert rating: +1.36 | Helped |
| Take the 14-week AI literacy course | Course participants · Retrospective pre-post survey: societal implications of AI | Likert rating: +1.28 | Helped |
Surprising findings
- Over half of survey respondents (51%) rated the readings as difficult, while only 30% rated the lecture material as difficult.
- Auditors reported less engagement than students, with 63% of auditors versus 87% of students engaging with more than half the material.
Limitations
- Retrospective pre-post self-report ratings without a control group or external baseline.
- Survey response rates were modest (145 respondents for the final survey) and skewed toward undergraduates.
- Readings selected by guest speakers were often too technical for the non-technical audience.
Experimental setup
Datasets: weekly student reflections final course survey responses
Metrics: retrospective pre-post Likert ratings course engagement ratings Course Evaluation Survey ratings thematic coding of open-ended responses
Baselines: CPSC 170 AI For Future Presidents
Builds on: AI100 study
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