Leveraging Undergraduate Perspectives to Redefine AI Literacy

Artificial intelligence (AI) represents the future of the workforce, but existing curricula inadequately prepare students to comprehend and use these new technologies. Despite the push for educators to teach AI literacy, there is a distinct lack of research exploring student perspectives on the topic. Utilizing an explanatory sequential mixed methods research design, we first administered an AI literacy survey to undergraduate students in a computing major to learn how they think about AI, and then conducted focus group interviews after further refining our research questions. There was a discrepancy between undergraduate competence with AI applications and underlying AI principles, which were conflated on the survey and positively influenced overall knowledge. Participant confidence in AI's capability as a learning tool was infrequently limited by perception of personal ability, but rather by beliefs about limitations in AI tool efficacy. Participants believed that students pursuing any field would benefit from AI literacy and that AI literacy education, if implemented effectively, could mitigate concerns with AI pervasion in the workplace. A combination of surveys and assessments will be beneficial when centering students in AI curricula, the former establishing a student's AI confidence and the latter competence.

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Publication Details

Published
2025-02-12
DOI
https://doi.org/10.1145/3641554.3701916
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69
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article

Leveraging Undergraduate Perspectives to Redefine AI Literacy

Kristina Kramarczuk, Jhone Ebert
1 citations
Online Learning and Analytics
1.69
article

Leveraging Undergraduate Perspectives to Redefine AI Literacy

Kristina Kramarczuk, Jhone Ebert
article en
1 citations

Abstract

Artificial intelligence (AI) represents the future of the workforce, but existing curricula inadequately prepare students to comprehend and use these new technologies. Despite the push for educators to teach AI literacy, there is a distinct lack of research exploring student perspectives on the topic. Utilizing an explanatory sequential mixed methods research design, we first administered an AI literacy survey to undergraduate students in a computing major to learn how they think about AI, and then conducted focus group interviews after further refining our research questions. There was a discrepancy between undergraduate competence with AI applications and underlying AI principles, which were conflated on the survey and positively influenced overall knowledge. Participant confidence in AI's capability as a learning tool was infrequently limited by perception of personal ability, but rather by beliefs about limitations in AI tool efficacy. Participants believed that students pursuing any field would benefit from AI literacy and that AI literacy education, if implemented effectively, could mitigate concerns with AI pervasion in the workplace. A combination of surveys and assessments will be beneficial when centering students in AI curricula, the former establishing a student's AI confidence and the latter competence.

University of Maryland, College Park (US)
Quality Education
Openalex Percentile: Top 15%
Online Learning and Analytics
1.69
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Leveraging Undergraduate Perspectives to Redefine AI Literacy — Kristina Kramarczuk, Jhone Ebert · (2025) | TGRS Research Map | TGRS