Work

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

Year: 2025

Type: article

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.

Source: Information

DOI: 10.3390/info16040277

Authors: Yong-Jik Lee, Robert O. Davis

Institutions: Kongju National University, Chonnam National University

Language: English

Topic: Digital literacy in education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $1,930