Exploring Generative AI Usage Patterns in Universities: Analysis and Guidelines for Sustainable Practices
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| Title: | Exploring Generative AI Usage Patterns in Universities: Analysis and Guidelines for Sustainable Practices |
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| Language: | English |
| Authors: | Nabil Hasan Al-Kumaim (ORCID |
| Source: | International Journal of Technology in Education. 2025 8(2):332-361. |
| Availability: | International Society for Technology, Education, and Science. ISTES Organization, Monument, CO 80132. e-mail: istesorganization@gmail.com; e-mail: ijteoffice@gmail.com; Web site: https://www.ijte.net/index.php/ijte/about |
| Peer Reviewed: | Y |
| Page Count: | 31 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Foreign Countries, Artificial Intelligence, Communication Skills, Interpersonal Competence, Academic Achievement, Anxiety, Learner Engagement, Ethics, College Students, Student Characteristics, Technology Uses in Education |
| Geographic Terms: | Malaysia |
| ISSN: | 2689-2758 |
| Abstract: | Generative artificial intelligence (GenAI) is driving a technological revolution, significantly impacting education, with universities as primary beneficiaries. This study explores the varied use of GenAI among university users in Malaysia, examining its challenges and effects across different demographic groups. A mixed-methods approach, including literature review content analysis, and a survey of 290 respondents, was used, analyzed with tools such as SPSS 27, and NVivo. The findings show widespread GenAI use, particularly among younger users (under 25), as revealed by one-way ANOVA testing, which rejected the null hypothesis that age does not affect engagement. No significant gender differences were found, though users with a bachelor's degree were more engaged than those with higher degrees. The study also found no strong link between the duration of AI experience or weekly usage hours and engagement, although a trend suggests increased usage leads to higher engagement. The study highlights six negative impacts of excessive GenAI use, including weakened interpersonal communication skills, potential declines in academic performance, increased stress from dependency on technology, the undermining of traditional educational methods, encouragement of academic dishonesty, and loss of learning motivation and engagement. To address these issues, the research introduces practical guidelines and recommendations including promoting self-regulation, establishing GenAI policy frameworks, and enhancing AI literacy and community engagement. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1472500 |
| Database: | ERIC |
| Abstract: | Generative artificial intelligence (GenAI) is driving a technological revolution, significantly impacting education, with universities as primary beneficiaries. This study explores the varied use of GenAI among university users in Malaysia, examining its challenges and effects across different demographic groups. A mixed-methods approach, including literature review content analysis, and a survey of 290 respondents, was used, analyzed with tools such as SPSS 27, and NVivo. The findings show widespread GenAI use, particularly among younger users (under 25), as revealed by one-way ANOVA testing, which rejected the null hypothesis that age does not affect engagement. No significant gender differences were found, though users with a bachelor's degree were more engaged than those with higher degrees. The study also found no strong link between the duration of AI experience or weekly usage hours and engagement, although a trend suggests increased usage leads to higher engagement. The study highlights six negative impacts of excessive GenAI use, including weakened interpersonal communication skills, potential declines in academic performance, increased stress from dependency on technology, the undermining of traditional educational methods, encouragement of academic dishonesty, and loss of learning motivation and engagement. To address these issues, the research introduces practical guidelines and recommendations including promoting self-regulation, establishing GenAI policy frameworks, and enhancing AI literacy and community engagement. |
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| ISSN: | 2689-2758 |
