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Article

Assessing the Impact of Prior Coding and Artificial Intelligence Learning on Non-Computing Majors’ Perception of AI in a University Context

1
College of Liberal Arts, Kongju National University, Cheonan 31080, Republic of Korea
2
Department of Education, Chonnam National University, Gwangju 61187, Republic of Korea
*
Author to whom correspondence should be addressed.
Information 2025, 16(4), 277; https://doi.org/10.3390/info16040277
Submission received: 5 March 2025 / Revised: 23 March 2025 / Accepted: 27 March 2025 / Published: 29 March 2025

Abstract

Artificial intelligence (AI) has emerged as a critical subject in global educational contexts, not only within computing majors but also across all academic disciplines. This shift mirrors the rise of digital literacy in the late 20th century, positioning AI literacy as a needed skill for future generations. Despite its importance, there is ongoing debate about what exactly AI literacy entails and the skills it requires. While previous research has explored how computational thinking and varying educational levels affect AI literacy, there is a gap in related research on the impact of coding experience and the age at which students first learn about AI, especially for university students in non-computer-based majors. This exploratory study revealed that South Korean university students with prior coding experience consistently demonstrated significantly greater AI literacy than did those without prior coding experience. However, the age when students first learn about AI does not seem to play a major role in their overall perception of AI. These results suggest that the idea that coding experience might not be necessary for AI literacy needs additional investigation. However, further research is needed to fully understand the factors that contribute to AI literacy in non-computer-based university majors.
Keywords: artificial intelligence; AI; block-coding; text-coding; university students artificial intelligence; AI; block-coding; text-coding; university students

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MDPI and ACS Style

Lee, Y.-J.; Davis, R.O. Assessing the Impact of Prior Coding and Artificial Intelligence Learning on Non-Computing Majors’ Perception of AI in a University Context. Information 2025, 16, 277. https://doi.org/10.3390/info16040277

AMA Style

Lee Y-J, Davis RO. Assessing the Impact of Prior Coding and Artificial Intelligence Learning on Non-Computing Majors’ Perception of AI in a University Context. Information. 2025; 16(4):277. https://doi.org/10.3390/info16040277

Chicago/Turabian Style

Lee, Yong-Jik, and Robert O. Davis. 2025. "Assessing the Impact of Prior Coding and Artificial Intelligence Learning on Non-Computing Majors’ Perception of AI in a University Context" Information 16, no. 4: 277. https://doi.org/10.3390/info16040277

APA Style

Lee, Y.-J., & Davis, R. O. (2025). Assessing the Impact of Prior Coding and Artificial Intelligence Learning on Non-Computing Majors’ Perception of AI in a University Context. Information, 16(4), 277. https://doi.org/10.3390/info16040277

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