AI acts primarily as an amplifying tool rather than an independent driver of academicbehavior, reflecting pre-existing attitudes toward learning and ethics, suggesting pre-existing attitudes toward learning and ethics are reflected.
Abstract
The rapid advancement of Artificial Intelligence (AI) has led to its widespread adoption in highereducation. A growing body of research has examined its educational implications, includingeffects on learning and academic integrity. Building on this literature, this paper investigateshow students’ orientations toward learning, effort, and ethics relate to their use of AI inacademic contexts. The study was conducted on a sample of 115 undergraduate and graduatebusiness students using a structured questionnaire. Data were analyzed using Chi-squaretests and Cramer’s V coefficients. The results reveal significant relationships betweenstudents’ orientations and AI use. Students who prioritize efficiency, minimal effort, and finaloutcomes are more likely to use AI frequently, trust its outputs without verification, and rely onit for assignments. Likewise, students with more tolerant attitudes toward unethical academicbehavior are more likely to use AI as a shortcut in academic tasks. In contrast, students whovalue the learning process, theoretical knowledge, and academic integrity are more likely tocritically evaluate AI-generated content and consult additional sources. The findings suggestthat AI acts primarily as an amplifying tool rather than an independent driver of academicbehavior, reflecting pre-existing attitudes toward learning and ethics.
It is recommended to develop a context-specific national policy framework that provides reasonable and balanced governance and regulation over the development, implementation and use of AI technologies within the Philippines' system of higher education.
Ramil Santos· international journal of eng...· 0 citations
The findings show that AI is increasingly seen as a transformative academic tool, especially for research, language learning, writing support and problem‐solving, and despite widespread AI adoption, the study identifies significant gaps in institutional infrastructure and the absence of systematic training programmes.
M. Doğan, B. Kashkhynbay, Zhaniyat Baltabayeva· European Journal of Educatio...· 0 citations
The findings indicate that faculty most frequently use AI in research and course preparation, and less commonly in teaching and assessment, and differences in faculty's beliefs are associated with the frequency and domains of AI use, professional development and institutional support.
It is suggested that AI technologies have considerable potential to enrich higher education; however, their successful implementation requires careful attention to ethical, technological, and pedagogical considerations to ensure that educational benefits are achieved while minimizing associated risks.
H. U. C. P. Hewawasam, D. Saparamadu· Sabaragamuwa University Jour...· 0 citations
Results indicate a significant level of AI usage among students, primarily for content management and academic support and the importance of integrating ethical considerations and promoting digital literacy in AI-enabled learning environments.
Christina Costa, Martha Almendarez Langland, Jason Roberson et al.· The Journal of Scholarship o...· 0 citations
Investigating the extent to which university students can use AI, how they use it, and the associated challenges and opportunities while using it reveals that students need explicit support on what AI is and how to use it in an ethical way.
Insaf Khoudri, Rachid Houmaida· Journal of Multidisciplinary...· 0 citations
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
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