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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.
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This content will become publicly available on July 14, 2026
Problematizing AI Literacy Access- Understanding Student AI Literacy from Student Voices
Domestic undergraduate computer science students formally learn about machine learning and artificial intelligence in upper-level undergraduate computing programs, yet they must navigate the lure of ChatGPT and other generative Artificial Intelligence tools that have been found to be somewhat accurate at completing early coding assignments. As AI tools proliferate, messaging about their use in academic settings are varied, and access to AI literacy is unknown. Through an investigation of interviews with Pell grant-eligible college students at open-access colleges, we address the following research questions: How do low-income undergraduate interview participants describe their uses of and attitudes regarding generative AI tool use for academic purposes? and What elements of AI digital literacy appear to be accessible to interview participants, based on their descriptive statements?
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- Award ID(s):
- 2129795
- PAR ID:
- 10623832
- Publisher / Repository:
- ACM Proceedings of the 2025 Conference on Research on Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT '25)
- Date Published:
- ISBN:
- 9798400706264
- Page Range / eLocation ID:
- 339-342
- Subject(s) / Keyword(s):
- AI tool use Pell-Grant eligible students digital divide generative AI literacy qualitative interview
- Format(s):
- Medium: X
- Location:
- Newark, NJ, USA
- Sponsoring Org:
- National Science Foundation
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