Generative Artificial Intelligence in Higher Education: A Systematic Review of Applications, Benefits, and Risks
DOI:
https://doi.org/10.61424/9jfcar87Keywords:
Generative artificial intelligence, higher education, large language models, teaching and learning, academic integrity, AI ethics, educational technologyAbstract
Generative Artificial Intelligence (GenAI) is increasingly transforming higher education by introducing new approaches to teaching, learning, assessment, academic research, and institutional administration. This systematic review examines the applications, benefits, and risks associated with the integration of GenAI in higher education. The review synthesizes recent scholarly literature on generative AI technologies, including large language models, AI-based writing assistants, conversational systems, automated content-generation tools, and multimodal generative applications. The findings indicate that GenAI can support personalized learning, academic writing, instructional material development, feedback provision, research assistance, language learning, and administrative decision-making. Its potential benefits include improved learning support, increased productivity, enhanced accessibility, and opportunities for more adaptive and student-centred educational practices. However, the review also identifies significant risks involving academic integrity, inaccurate or fabricated information, algorithmic bias, privacy and data protection, overreliance on automated systems, unequal access to AI technologies, and uncertainty regarding appropriate assessment practices. The evidence further suggests that the educational value of GenAI depends substantially on digital literacy, institutional policies, pedagogical design, and responsible human oversight. Rather than functioning as a replacement for educators or learners, GenAI is most effectively positioned as a complementary technology integrated within transparent, ethical, and pedagogically grounded practices. The review concludes that higher education institutions require comprehensive governance frameworks, AI literacy initiatives, assessment reforms, and continuous evaluation mechanisms to maximize the educational benefits of GenAI while mitigating its academic, ethical, and social risks.
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