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Adnyana, I Putu Iwan Krisna
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Teacher’s Readiness Toward Artificial Intelligence in The School of North Bali Purnama, M. Rokhman; Adnyana, I Putu Iwan Krisna; Sogen, Afrianto T.L; Indrawan, Gede; Santosa, Made Hery
Jurnal Paedagogy Vol 12, No 1 (2025): Jurnal Paedagogy (January 2025)
Publisher : Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jp.v12i1.13707

Abstract

This study aims to analyze teachers' readiness to integrate artificial intelligence into education for the digital revolution. In this study, teachers were randomly selected with a total of 73 teachers from various subjects. This research used a quantitative method of using questionnaires for data collection. The data analysis technique in this research uses descriptive quantitative.  Based on the research findings, technical ability, institutional support, adequate technological infrastructure, and school facilities affected teachers' readiness to use various types of artificial intelligence. Urban teachers were more ready than rural teachers, largely because urban teachers have more access to training materials and technology than rural teachers. In the future, in enabling AI to be used effectively to improve learning standards, government support needs to conduct specialized AI training at various school levels from urban to rural areas, in particular, stronger institutional support, and better school infrastructure and facilities to enhance teachers' readiness to face the digital revolution in education.
Teacher’s Readiness Toward Artificial Intelligence in The School of North Bali Purnama, M. Rokhman; Adnyana, I Putu Iwan Krisna; Sogen, Afrianto T.L; Indrawan, Gede; Santosa, Made Hery
Jurnal Paedagogy Vol. 12 No. 1 (2025): January
Publisher : Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jp.v12i1.13707

Abstract

This study aims to analyze teachers' readiness to integrate artificial intelligence into education for the digital revolution. In this study, teachers were randomly selected with a total of 73 teachers from various subjects. This research used a quantitative method of using questionnaires for data collection. The data analysis technique in this research uses descriptive quantitative.  Based on the research findings, technical ability, institutional support, adequate technological infrastructure, and school facilities affected teachers' readiness to use various types of artificial intelligence. Urban teachers were more ready than rural teachers, largely because urban teachers have more access to training materials and technology than rural teachers. In the future, in enabling AI to be used effectively to improve learning standards, government support needs to conduct specialized AI training at various school levels from urban to rural areas, in particular, stronger institutional support, and better school infrastructure and facilities to enhance teachers' readiness to face the digital revolution in education.