Integrating Adaptive Artificial Intelligence in Secondary Education

Zia Yewon Lee
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Zia Yewon Lee: US International School, Seoul, Republic of Korea

Technium Social Sciences Journal, 2026, vol. 86, issue 1, 49-53

Abstract: This paper examines the role of artificial intelligence (AI) platforms in secondary education, as well addressing the limitations of a one-size-fits-all method of instruction. Post-pandemic, learning gaps continue to grow and classrooms and growing more diverse in addressing academic needs of students. Therefore, it is becoming more important to note students’ individual needs for learning. Drawing on recent research, this paper argues that AI systems improve academics by offering individualized instruction, real-time feedback, and self-paced learning methods while enabling teachers to monitor progress with real-time data. This paper further explores how this technology can reduce teacher workload, allowing them to devote more time to support students. Although there are still concerns about relying too heavily on technology, the increasing number in screen time, and cost of implementing this technology, current evidence suggests that adaptive AI is most effective when used to help rather than replace teachers. This paper concludes that AI should be viewed as a long-term investment in education that supports learning outcomes and reduces teacher burnout.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:tec:journl:ojs:13779

DOI: 10.47577/tssj.v86i1.13779

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