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All Journal Jurnal Math Educator Nusantara: Wahana Publikasi Karya Tulis Ilmiah di Bidang Pendidikan Matematika
Abdurrobbil Falaq Dwi Anggoro
Universitas Negeri Semarang
Education Social Sciences

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Enhancing PISA-like mathematical literacy through deep learning assisted by mathos ai for junior high school students Wahyu Widada; Khathibul Umam Zaid Nugroho; Masri Masri; Abdurrobbil Falaq Dwi Anggoro; Dewi Herawaty; Rahmat Jumri; Shadaqnas Dewarif Tri Anggoro
Jurnal Math Educator Nusantara: Wahana Publikasi Karya Tulis Ilmiah di Bidang Pendidikan Matematika Vol 11 No 1 (2025): Jurnal Math Educator Nusantara
Publisher : Program Studi Pendidikan Matematika, Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/jmen.v11i1.25109

Abstract

Based on PISA, Indonesian students' mathematical literacy skills are very low. This study investigates the effectiveness of Mathos AI-assisted deep learning design in improving PISA-like mathematical literacy among junior high school students. Using design research methodology with validation studies approach. Data were collected through pre-test and post-test, classroom observation, interviews, and analysis of student work. The findings revealed significant improvements in students' mathematical literacy, with positive impacts on their motivation and engagement. The integration of Mathos AI facilitates personalized learning and provides valuable insights into students' learning processes. This study contributes to the growing literature on AI-driven educational interventions, which offer practical implications for improving mathematical literacy in real-world classroom settings. The conclusion of this study is that Mathos AI-assisted deep learning is able to improve PISA-like mathematical literacy skills among junior high school students. The integration of AI-based tools in mathematics education can result in improved learning outcomes and student engagement. Further research is needed to explore the long-term effects of AI-based interventions and develop best practices for their implementation.
Co-Authors Dewi Herawaty Khathibul Umam Zaid Nugroho Masri Masri Rahmat Jumri Shadaqnas Dewarif Tri Anggoro Wahyu Widada