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A Comparative Analysis of Student Awareness, Trust, Usage, and Ethical Concerns Regarding AI Tools Across Academic Levels
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 59 |
| Year of Publication: 2025 |
| Authors: P. Rajesh Kumar, Nantha Kumar Subramaniam, Safiah Md Yusof |
10.5120/ijca2025925993
|
P. Rajesh Kumar, Nantha Kumar Subramaniam, Safiah Md Yusof . A Comparative Analysis of Student Awareness, Trust, Usage, and Ethical Concerns Regarding AI Tools Across Academic Levels. International Journal of Computer Applications. 187, 59 ( Nov 2025), 16-20. DOI=10.5120/ijca2025925993
Abstract
The integration of generative Artificial Intelligence (AI) tools into higher education presents a dual challenge: while offering powerful support for academic tasks, it raises significant concerns about academic integrity. This study provides a comparative analysis of students' awareness, trust, usage patterns, and ethical concerns (ATEU) regarding AI tools for assignment completion across different academic levels. Adopting a quantitative approach, this research utilized a structured survey administered to 508 students at Open University Malaysia, encompassing Diploma (D), Undergraduate (UG), and Postgraduate (PG) programs. Data was collected on the four key dimensions—Awareness, Usage, Trust, and Ethical Concerns—and analyzed using non-parametric statistical tests. The findings reveal statistically significant differences across the academic cohorts. Postgraduate students demonstrated markedly higher levels of AI awareness, greater trust in AI-generated outputs, and more pronounced ethical concerns compared to their undergraduate and diploma counterparts (p < 0.05). Conversely, AI usage patterns for assignment completion showed no significant variation among the groups, suggesting that while adoption is widespread, the depth of understanding and critical perspective differs. The results indicate that the research-intensive nature of postgraduate studies likely cultivates a more sophisticated engagement with AI, fostering both confidence and critical reflection. This study underscores the necessity for higher education institutions to move beyond uniform policies and develop tailored, level-specific AI literacy programs. Interventions should focus on building foundational awareness at the diploma level while addressing nuanced ethical considerations and critical evaluation skills for advanced learners. Such data-driven insights are crucial for creating institutional guidelines that promote the responsible and ethical integration of AI into academic practice.
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