Abstract
Purpose: The study aims to summarize current discussions among educational stakeholders regarding the potential benefits and threats posed by Artificial Intelligence. Methodology: In conducting comprehensive and systematic review, the study utilized the PRISMA flowchart and included only articles published between January 2020 and July 2024. The focus was strictly on peer-reviewed articles, with conference papers, dissertations, and other types of papers excluded. Data was sourced exclusively from EBSCOhost and Google Scholar. Additionally, only articles centered on the higher education industry were considered. Findings: The findings of this study reveal ongoing debates among educational stakeholders regarding the threats and benefits of AI models. It explains how AI is transforming academic environments by offering personalized learning experiences, enhancing learning outcomes, and increasing student engagement. However, concerns about data privacy have also emerged. To eliminate these concerns, the study recommends the introduction of consent forms that give users the option to allow or deny the use of their data for AI training. Unique Contribution to Theory, Practice and Policy: The study contributes to the ongoing debates by grounding its analysis in Sociotechnical Systems Theory (STS), emphasizing the need for a human-centered approach in AI adoption. This offers a holistic perspective on how educational institutions can implement AI effectively while addressing stakeholder concerns about privacy and control over data, making it a valuable resource for both academic and policy discussions surrounding AI in education.
Published Version
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