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August 10, 2025Information Management and Business Review0 citationsOpen Access

Trends in Artificial Intelligence and Educational Technology: A Systematic Analysis

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MHMohd Faireez Bin Mohd HanafiahNZNoor Zalina ZainalEKErne Suzila Kassim

Key Points

  • AI enhances student engagement and academic achievement through adaptive learning technologies, including chatbots and intelligent tutors.
  • The systematic literature review identified emerging advancements in educational technology, such as contrastive learning and adversarial techniques.
  • Research findings highlight the shift from general technology applications to focused studies on AI's role in education post-COVID-19.
  • Responsible AI integration in education raises ethical concerns, including algorithmic discrimination and data security; future research must address these issues.

Abstract

The faster evolution of artificial intelligence (AI) is changing the field of education by making teaching and learning more personalized, adaptive, and data-driven. As AI gets further integrated into educational technologies (EdTech), student engagement is enhanced by chatbots, VR/AR, intelligent tutors, and ML algorithms, boosting academic achievement and the development of reasoning skills. This change was faster during the COVID-19 pandemic because of the greater emphasis on the role of technology in education, its possibilities, and shortcomings. At the same time, there is increased use of AI-powered technologies in education, and the more prominent ethical issues these technologies pose are algorithmic discrimination, data security, and the implications of systems’ autonomy in making judgments. This research examines the effects of Artificial Intelligence (AI) on Education within the years 2021 - 2025, utilizing a systematic literature review (SLR) and bibliometric analysis through the VOSviewer software. Results delineate dominant research clusters and depict a shift from examining general applications of technology to more nuanced, emerging advancements like contrastive learning and adversarial techniques. The research draws attention to implementing AI in education responsibly while outlining further steps in research and policymaking to ensure educational AI is used to its fullest potential while protecting academic accessibility and institutional neutrality.

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Cite This Study

Hanafiah et al. (2025) studied this question.

synapsesocial.com/papers/68af5407ad7bf08b1eadaea2https://doi.org/10.22610/imbr.v17i2(i)s.4600
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