Technology Acceptance and Its Impact on Student Dependency in Assignment Completion at Politeknik Kota Bharu
Keywords:
Technology Acceptance Model (TAM), Academic Over-reliance, AI LiteracyAbstract
This study aims to assess the impact of perceived ease of use, perceived usefulness, and use of artificial intelligence (AI) tools on students’ reliance in completing academic assignments among diploma students at Malaysian Polytechnics. Based on the Technology Acceptance Model (TAM) by Davis (1989), this study examines the extent to which students accept and use AI tools such as ChatGPT, Grammarly, and QuillBot in the context of daily learning. This study uses a quantitative approach with an online questionnaire distributed to polytechnic students, and the data is analyzed using descriptive statistics and regression analysis to identify the relationship between variables. The findings show that perceptions of ease of use and usefulness of AI have a significant relationship with the level of students’ use and reliance. Over-reliance is detected when students use AI not only as a learning aid, but also as a shortcut in completing assignments, thus affecting critical thinking and academic autonomy. This study concludes that although AI benefits students in terms of understanding and productivity, the level of reliance needs to be monitored ethically and systematically. Therefore, the study recommends that higher education institutions develop clear AI usage policies, increase ethical awareness among students, and include AI literacy in the curriculum as an effort to balance effective technology use and self-directed learning.
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The content of The International Journal of Technical Vocational and Engineering Technology (IJTVET) is licensed under a Creative Commons Attribution 4.0 International license (CC BY NC ND 4.0). Authors transfer the ownership of their articles' copyright and publication right to the International Journal of Technical Vocational and Engineering Technology (IJTVET). Permission is granted to the Malaysian Technical Doctorate Association (MTDA) to publish the submitted articles. The authors also permit any third party to freely share the article as long as the original authors and citation information are properly cited.













