Artificial Intelligence (AI), particularly Generative Artificial Intelligence (GenAI), is rapidly reshaping higher education by transforming academic research, teaching practices, learning processes, and institutional approaches to technology adoption. However, the rapid expansion of AI also raises concerns regarding academic integrity, privacy, data ownership, algorithmic bias, misinformation, and responsible use. This systematic literature review (SLR) synthesises recent evidence on the role of AI in higher education, with particular attention to four dimensions: AI adoption, AI-assisted academic research, AI ethics, and AI-enabled teaching and learning. Following the PRISMA framework, studies were identified through Scopus and Web of Science and assessed using predefined inclusion, exclusion, and quality appraisal criteria. From the initial 260 records, the screening and eligibility processes resulted in 20 studies being included in the final qualitative synthesis. The findings reveal that AI-assisted academic research represents the most prominent research area (35%), followed by AI-enabled teaching and learning (25%), AI adoption (20%), and AI ethics (20%). The reviewed studies demonstrate that AI supports literature reviews, academic writing, text revision, data analysis, referencing, personalised learning, feedback, student engagement, and research productivity. At the same time, effective implementation requires AI literacy, critical judgement, ethical awareness, institutional guidance, and appropriate training. The review identifies a significant need for integrated and longitudinal research examining AI adoption, ethical practice, learning outcomes, critical thinking, research quality, and student engagement across diverse disciplines and contexts. The study concludes that AI should function as a supportive technology that complements human judgement rather than replacing academic responsibility, providing implications for universities, educators, researchers, students, and policymakers.
Noor Hanim binti Rahmat· International journal of res...· 0 citations
Growing use of generative AI technologies like ChatGPT has changed online learning and increased student motivation. This study explores online learning motivation and ChatGPT using Self-Determination Theory (SDT) to examine competence, autonomy, and relatedness in online learners. 189 academics from various fields participated in a quantitative survey. A five-point Likert scale-based 52-item questionnaire was derived from Ryan and Deci (2000), Fowler (2018), and Youssef et al. (2024). Competence, autonomy, and relatedness were not gender-specific across academic groupings. In the descriptive study, students rated the AI system's function in critical thinking, academic accomplishment, engagement, and learning motivation positively. The greatest competency item was students' practice of cross-checking ChatGPT knowledge with independent study (M = 4.06), whereas the most autonomous item was achieving good grades (M = 4.59). Relatedness was strong in social engagement and teacher support. They liked class discussions (M = 4.00) and found course materials meaningful (M = 4.28). Positive correlations were found between competence, autonomy (r =.550, p <.001), and competence and relatedness (r =.551, p <.001). The results support the Self-Determination Theory as a valid framework for online learning motivation and show that ChatGPT can promote learners' competence, autonomy, and relatedness if responsibly integrated into online learning settings. The work has major theoretical, pedagogical, and practical consequences for higher education AI-assisted learning.
E. S. Mohandas, Aini Faridah Azizul Hassan, Nor Azyyati Md Saad et al.· International journal of res...· 0 citations
The findings revealed that the students relied on metacognitive and cognitive writing strategies and reflected their high resilience and effort regulation despite showing a lower consistency in regular writing practice, which offers a foundation for more focused instructional interventions in higher education.
Nurul Syafieqah Jaafar, N. Rosly, Najwa Zulkifli et al.· International journal of res...· 0 citations