Leveraging Undergraduate Perspectives to Redefine AI Literacy

被引:0
|
作者
Ebert, Jack [1 ]
Kramarczuk, Kristina [1 ]
机构
[1] Univ Maryland, College Pk, MD 20742 USA
来源
PROCEEDINGS OF THE 56TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE TS 2025, VOL 2 | 2025年
关键词
Artificial intelligence; Generative AI; AI Literacy; CONFIDENCE;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:290 / 296
页数:7
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