Exploratory research on understanding university students’ artificial intelligence literacy in a Korean university
Yong-Jik Lee 1,
JongHyun Oh 1 * ,
Changwoo Hong 1 More Detail
1 Chonnam National University, Gwangju, SOUTH KOREA
* Corresponding Author
Online Journal of Communication and Media Technologies, Volume 14, Issue 3, Article No: e202440.
https://doi.org/10.30935/ojcmt/14711
OPEN ACCESS 1462 Views 1033 Downloads Published online: 11 Jun 2024
ABSTRACT
This study explored university students’ perceptions of artificial intelligence (AI) literacy and AI education. Specifically, the authors sought to understand the level of AI literacy among university students, the extent of their prior exposure to AI education, and the factors that affect their AI education. The study was conducted through an online survey distributed among 300 university students at a Korean university. The study findings indicate that most university students are interested in learning AI. Moreover, the results showed that students with prior experience with software (SW) education showed superior knowledge, a better grasp of AI concepts, and more confidence in using AI technologies, especially in computer coding skills. On the other hand, students with less exposure to prior AI education expressed a need for more learning opportunities and sufficient knowledge of computer coding skills. In addition, we found that students who had received SW education during their K-12 schooling showed better math skills than those who had only received short-term training in university. These findings underscore the importance of addressing the educational barriers that impede university students’ ability to harness this interest effectively. In conclusion, our study provides valuable insights into university students’ perceptions regarding AI literacy and the factors that affect their AI education.
CITATION
Lee, Y.-J., Oh, J., & Hong, C. (2024). Exploratory research on understanding university students’ artificial intelligence literacy in a Korean university.
Online Journal of Communication and Media Technologies, 14(3), e202440.
https://doi.org/10.30935/ojcmt/14711
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