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All Journal Journal of Education and Learning (EduLearn) Journal of Educational Research and Evaluation Journal of Education Technology Jurnal EDUTECH Undiksha JTP - Jurnal Teknologi Pendidikan Journal of Environment and Sustainability Education Conference Proceedings International Conference on Education Innovation and Social Science Journal on Smart Learning Technologies
Qodr, Taufiq Subhanul
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Humanities Chemistry Computer Science & IT Education Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Physics Public Health Social Sciences Other

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Enhancing Junior High School Teaching Performance Through AI-Supported Deep Learning Approaches Cahyono, Budi; Sukmawati, Fatma; Santosa, Eka Budhi; Prihatin, Relly; Suparmi; Qodr, Taufiq Subhanul
JTP - Jurnal Teknologi Pendidikan Vol. 27 No. 3 (2025): Jurnal Teknologi Pendidikan
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jtp.v27i3.61743

Abstract

supported deep learning approaches in improving the teaching performance of junior high school teachers. With the increasing demand for 21st-century teaching competencies, there is a need for innovative instructional strategies that enhance teacher effectiveness and engagement. A quantitative quasi-experimental method was employed, involving pre-tests and post-tests administered to both control and experimental groups. The study involved 64 junior high school teachers across science and social studies subjects. Teaching performance was assessed using structured observation and evaluation tools covering lesson planning, implementation, and assessment practices. Data analysis was conducted using t-tests and normalized gain (n-gain) scores. The findings demonstrated that the teachers in the experimental group—who utilized AI-supported deep learning approaches—showed significantly greater improvement in teaching performance compared to the control group. The intervention was classified as “effective” in fostering meaningful, interactive, and future-ready instructional practices. The study concludes that integrating AI-supported deep learning strategies can substantially enhance teaching quality. It is recommended that educational institutions incorporate these approaches into ongoing professional development initiatives to better prepare teachers for modern educational demands. The findings demonstrated that the teachers in the experimental group showed significantly greater improvement in teaching performance.
Co-Authors Agus Efendi Akhmad Arif Musadad Ali, Wazir Andrianto, Rico Eko Ariana, Yudi Asrowi Asrowi Budi Cahyono Budiarto, Mochamad Kamil Cahyono, Budi Tri Dewi Ika Sari Fatma Sukmawati, Fatma Khan, Nauroz Laksono Trisnantoro Maulana, Iwan Mulyasari, Dini Wahyu Relly Prihatin Ridhani, Jovita Santosa, Eka Budhi Sri Sumaryati Suharno Suparmi Sutimin, Leo Agung Triana Rejekiningsih dkk Winandari, Anita