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The economic potential of using the AI-based ASES-EdTech platform to improve the professionalism of elementary school teachers in rural areas of Indonesia

Author

Listed:
  • Evi Susilawati

  • Sapta Kesuma

  • Dedi Leman

  • Yusrita Yusrita

  • Ahmad Fauzan

  • Habil Habil

  • Dea Viona

  • Cut Aqila Hummairah

Abstract

The integration of Artificial Intelligence (AI) in education serves as a catalyst for economic transformation, particularly in rural Indonesia, where teacher professionalism remains a key challenge due to limited access and implementation costs. This study examines the economic potential of the AI-based Automated Short Essay Scoring–Education Technology (ASES-EdTech) platform in enhancing the professionalism of elementary school teachers in Gomo District, South Nias Regency, Indonesia. Employing a quantitative approach with Structural Equation Modeling using Partial Least Squares (SEM-PLS), data were collected from 88 elementary school teachers, including 19 core implementers from SDN 071223 selected through purposive sampling. The findings reveal that the implementation intensity of the ASES-EdTech platform positively influences the economic potential of teacher professional development (β = 0.742, t = 8.356, p < 0.001), explaining 55.1% of the variance (R² = 0.551). The platform demonstrated strong cost-effectiveness, with a projected return on investment ratio of 3.23:1 over 24 months, increasing teacher productivity by 58.3%, reducing operational costs by IDR 928,000 per teacher annually, and contributing IDR 136.8 million to the local economy. These results underscore AI’s strategic role in advancing educational equity and economic sustainability in rural Indonesia.

Suggested Citation

  • Evi Susilawati & Sapta Kesuma & Dedi Leman & Yusrita Yusrita & Ahmad Fauzan & Habil Habil & Dea Viona & Cut Aqila Hummairah, 2025. "The economic potential of using the AI-based ASES-EdTech platform to improve the professionalism of elementary school teachers in rural areas of Indonesia," Edelweiss Applied Science and Technology, Learning Gate, vol. 9(11), pages 827-838.
  • Handle: RePEc:ajp:edwast:v:9:y:2025:i:11:p:827-838:id:11009
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