Utilization of Generative Artificial Intelligence Technologies as Learning Tools among University Students: A Cross-Sectional Study

Artificial intelligence (AI) technologies have the potential to revolutionize the higher-education landscape by offering personalized and adaptive learning experiences. This study aimed to investigate the utilization of AI technologies as a learning tool among university students and identify the factors influencing it. This study utilized a cross-sectional design and collected data through a self-administered questionnaire developed based on the technology acceptance model and Theory of Planned Behavior (TPB). Data from 581 respondents were analyzed using SPSS version 29, employing descriptive statistics and multivariate hierarchical multiple linear regression analysis. The study found that AI technologies were widely utilized by students for various academic tasks, with clarifying understanding (76.1%), paraphrasing (71.6%), and academic translations (71%) being the most common. ChatGPT (91.4%), QuillBot (82.8%), and Grammarly (79.7%) emerged as the most popular AI tools among the participants. A hierarchica1l multiple regression analysis revealed that motivation (β = .17, p = .002), subjective norms (β = .14, p < .001), and intention to use (β = .49, p < .001) were significant predictors of AI technology use among students. This study highlights the widespread adoption of AI technologies for academic tasks among university students. Higher education institutions foster an environment that enhances students’ motivation, addresses subjective norms, and cultivates a positive intention towards AI technology adoption to facilitate its effective integration into the learning process.

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Publication Details

Journal
International Journal of Online and Biomedical Engineering (iJOE)
Published
2025-06-03
DOI
https://doi.org/10.3991/ijoe.v21i07.54227
Citations
1
Primary Topic
Technology-Enhanced Education Studies
Type
article
Field-Weighted Citation Impact
8.93
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article

Utilization of Generative Artificial Intelligence Technologies as Learning Tools among University Students: A Cross-Sectional Study

Cheng-Yu Chung, See Hua, Md Mizanur Rahman, Angellisa Shanana et al.
1 citations
International Journal of Online and Biomedical Engineering (iJOE)
Technology-Enhanced Education Studies
8.93
article

Utilization of Generative Artificial Intelligence Technologies as Learning Tools among University Students: A Cross-Sectional Study

Cheng-Yu Chung, See Hua, Md Mizanur Rahman, Angellisa Shanana, Thiviyashree, Elleyajasmin
article en
1 citations

Abstract

Artificial intelligence (AI) technologies have the potential to revolutionize the higher-education landscape by offering personalized and adaptive learning experiences. This study aimed to investigate the utilization of AI technologies as a learning tool among university students and identify the factors influencing it. This study utilized a cross-sectional design and collected data through a self-administered questionnaire developed based on the technology acceptance model and Theory of Planned Behavior (TPB). Data from 581 respondents were analyzed using SPSS version 29, employing descriptive statistics and multivariate hierarchical multiple linear regression analysis. The study found that AI technologies were widely utilized by students for various academic tasks, with clarifying understanding (76.1%), paraphrasing (71.6%), and academic translations (71%) being the most common. ChatGPT (91.4%), QuillBot (82.8%), and Grammarly (79.7%) emerged as the most popular AI tools among the participants. A hierarchica1l multiple regression analysis revealed that motivation (β = .17, p = .002), subjective norms (β = .14, p < .001), and intention to use (β = .49, p < .001) were significant predictors of AI technology use among students. This study highlights the widespread adoption of AI technologies for academic tasks among university students. Higher education institutions foster an environment that enhances students’ motivation, addresses subjective norms, and cultivates a positive intention towards AI technology adoption to facilitate its effective integration into the learning process.

International Journal of Online and Biomedical Engineering (iJOE)Vol. 21(07)
Universiti Malaysia Sarawak (MY)
Openalex Percentile: Top 4%
Technology-Enhanced Education Studies
8.93
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