AI Literacy and Intention to Use Text-Based GenAI for Learning: The Case of Business Students in Korea
With the increasing use of large-scale language model-based AI tools in modern learning environments, it is important to understand students’ motivations, experiences, and contextual influences. These tools offer new support dimensions for learners, enhancing academic achievement and providing valua...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-07-01
|
| Series: | Informatics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9709/11/3/54 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850260814117732352 |
|---|---|
| author | Moonkyoung Jang |
| author_facet | Moonkyoung Jang |
| author_sort | Moonkyoung Jang |
| collection | DOAJ |
| description | With the increasing use of large-scale language model-based AI tools in modern learning environments, it is important to understand students’ motivations, experiences, and contextual influences. These tools offer new support dimensions for learners, enhancing academic achievement and providing valuable resources, but their use also raises ethical and social issues. In this context, this study aims to systematically identify factors influencing the usage intentions of text-based GenAI tools among undergraduates. By modifying the core variables of the Unified Theory of Acceptance and Use of Technology (UTAUT) with AI literacy, a survey was designed to measure GenAI users’ intentions to collect participants’ opinions. The survey, conducted among business students at a university in South Korea, gathered 239 responses during March and April 2024. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software (Ver. 4.0.9.6). The findings reveal that performance expectancy significantly affects the intention to use GenAI, while effort expectancy does not. In addition, AI literacy and social influence significantly influence performance, effort expectancy, and the intention to use GenAI. This study provides insights into determinants affecting GenAI usage intentions, aiding the development of effective educational strategies and policies to support ethical and beneficial AI use in academic settings. |
| format | Article |
| id | doaj-art-d172693f65444591a3e5ad2eb747f85d |
| institution | OA Journals |
| issn | 2227-9709 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Informatics |
| spelling | doaj-art-d172693f65444591a3e5ad2eb747f85d2025-08-20T01:55:33ZengMDPI AGInformatics2227-97092024-07-011135410.3390/informatics11030054AI Literacy and Intention to Use Text-Based GenAI for Learning: The Case of Business Students in KoreaMoonkyoung Jang0College of Business, Gachon University, 1342 Seongnam-daero, Soojeong-gu, Seongnam 13120, Republic of KoreaWith the increasing use of large-scale language model-based AI tools in modern learning environments, it is important to understand students’ motivations, experiences, and contextual influences. These tools offer new support dimensions for learners, enhancing academic achievement and providing valuable resources, but their use also raises ethical and social issues. In this context, this study aims to systematically identify factors influencing the usage intentions of text-based GenAI tools among undergraduates. By modifying the core variables of the Unified Theory of Acceptance and Use of Technology (UTAUT) with AI literacy, a survey was designed to measure GenAI users’ intentions to collect participants’ opinions. The survey, conducted among business students at a university in South Korea, gathered 239 responses during March and April 2024. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software (Ver. 4.0.9.6). The findings reveal that performance expectancy significantly affects the intention to use GenAI, while effort expectancy does not. In addition, AI literacy and social influence significantly influence performance, effort expectancy, and the intention to use GenAI. This study provides insights into determinants affecting GenAI usage intentions, aiding the development of effective educational strategies and policies to support ethical and beneficial AI use in academic settings.https://www.mdpi.com/2227-9709/11/3/54Generative AIlarge-scale language modelChatGPTundergraduatesUTAUTAI literacy |
| spellingShingle | Moonkyoung Jang AI Literacy and Intention to Use Text-Based GenAI for Learning: The Case of Business Students in Korea Informatics Generative AI large-scale language model ChatGPT undergraduates UTAUT AI literacy |
| title | AI Literacy and Intention to Use Text-Based GenAI for Learning: The Case of Business Students in Korea |
| title_full | AI Literacy and Intention to Use Text-Based GenAI for Learning: The Case of Business Students in Korea |
| title_fullStr | AI Literacy and Intention to Use Text-Based GenAI for Learning: The Case of Business Students in Korea |
| title_full_unstemmed | AI Literacy and Intention to Use Text-Based GenAI for Learning: The Case of Business Students in Korea |
| title_short | AI Literacy and Intention to Use Text-Based GenAI for Learning: The Case of Business Students in Korea |
| title_sort | ai literacy and intention to use text based genai for learning the case of business students in korea |
| topic | Generative AI large-scale language model ChatGPT undergraduates UTAUT AI literacy |
| url | https://www.mdpi.com/2227-9709/11/3/54 |
| work_keys_str_mv | AT moonkyoungjang ailiteracyandintentiontousetextbasedgenaiforlearningthecaseofbusinessstudentsinkorea |