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Gemini AI Feasibility Study Can Improve Interactive Learning in the Classroom

Aug 2026 · bit-Tech · Vol 9, pp. 3849 · 0 citations

TL;DR

To ensure a responsible transition to AI-assisted education, this study recommends a phased strategy: upgrading IT infrastructure, providing regular AI literacy training for educators, and establishing structured faculty supervision protocols to mitigate student dependency.

Abstract

This study evaluates the feasibility of integrating Gemini AI to counteract declining student motivation driven by conventional teaching methodologies at Pamulang University, South Tangerang. Utilizing an integrated SWOT and TELOS (Technical, Economic, Legal, Operational, and Schedule) framework, the research analyzes empirical survey data from Information Systems students. The findings reveal that 97.6% of respondents belong to Generation Z, a demographic natively receptive to digital tools. Furthermore, 78.6% had independently adopted Gemini AI for academic purposes prior to institutional intervention, while 87.8% agree that diverse digital materials significantly enhance classroom interaction. The SWOT analysis highlights critical internal strengths, including heightened motivation and broader knowledge access, alongside interactive learning environments. Conversely, a severe internal weakness is the university's infrastructure, with 54.8% of students reporting unstable internet connectivity. While high independent adoption presents a strong external opportunity, the primary external threat stems from an overreliance on AI that could compromise critical thinking and analytical problem-solving skills. From a TELOS perspective, implementing Gemini AI is both economically and legally viable, aligning with Indonesian frameworks such as the Ministry of Communication Circular No. 9/2023 and Law No. 27/2022 on Personal Data Protection. Nevertheless, the institution's technical readiness falls below the required threshold and demands substantial enhancement. To ensure a responsible transition to AI-assisted education, this study recommends a phased strategy: upgrading IT infrastructure, providing regular AI literacy training for educators, and establishing structured faculty supervision protocols to mitigate student dependency.

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