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Enhancing TPACK and Statistical Literacy through Generative AI–Based Adaptive Learning: A Mixed-Methods Study Maryati, Iyam; Gumilar, Surya; Rahayu, Ayu Puji; Harun, Makmur
Mosharafa: Jurnal Pendidikan Matematika Vol. 15 No. 1 (2026): January
Publisher : Department of Mathematics Education Program IPI Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/mosharafa.v15i1.3491

Abstract

Penelitian ini mengkaji dampak kerangka pembelajaran adaptif terintegrasi Generative Artificial Intelligence (GenAI; ChatGPT) terhadap peningkatan Technological Pedagogical and Content Knowledge (TPACK) dan literasi statistis calon guru matematika. Kerangka tersebut menerapkan interaksi dialogis berbasis mahasiswa, structured prompting, dan scaffolding dosen untuk mempersonalisasi eksplorasi statistika. Dengan desain kuasi-eksperimen mixed methods, penelitian melibatkan 72 mahasiswa (37 kelompok eksperimen dan 35 kontrol). Data kuantitatif dianalisis menggunakan uji t berpasangan dan ANCOVA, sedangkan data kualitatif dianalisis secara tematik. Hasil menunjukkan kedua kelompok meningkat secara signifikan, namun kelompok eksperimen memiliki skor akhir tersesuaikan yang lebih tinggi. Temuan kualitatif menegaskan peningkatan pemahaman konseptual, kemampuan desain pembelajaran berbasis teknologi, serta refleksi kritis terhadap etika penggunaan AI. Studi ini mendukung integrasi literasi AI dalam kurikulum pendidikan guru. This study examines the impact of a Generative Artificial Intelligence (GenAI; ChatGPT)–integrated adaptive learning framework on improving Technological Pedagogical and Content Knowledge (TPACK) and statistical literacy among prospective mathematics teachers. The framework employed student-driven dialogic interaction, structured prompting, and lecturer-guided scaffolding to personalize statistical exploration. Using a mixed-methods quasi-experimental design, 72 students participated (37 experimental, 35 control). Quantitative data from tests and questionnaires were analyzed using paired t-tests and ANCOVA, while interviews and observations underwent thematic analysis. Results showed significant gains in both groups, but the experimental group achieved higher adjusted posttest scores, indicating superior effectiveness of GenAI-integrated learning. Qualitative findings highlighted improved conceptual understanding, instructional design skills, and critical reflection on ethical AI use. The study supports embedding AI literacy and pedagogically grounded prompting within teacher-education curricula and institutional policy.
QAULAN-BASED COMMUNICATION IN ISLAMIC RELIGIOUS EDUCATION: THE ROLE OF MADRASAH LEADERSHIP AND INSTITUTIONAL CULTURE Aprianto, Iwan; Fauzi, Hairul; Al Faruq, M. Shoffa Saifillah; Harun, Makmur
EDURELIGIA: Jurnal Pendidikan Agama Islam Vol 9, No 3 (2025)
Publisher : Nurul Jadid University, Paiton Probolinggo, East Java

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/edureligia.v9i3.11937

Abstract

This study aimed to implement six Qur'an-based communication principles in Islamic Religious Education (PAI) learning at Madrasah Aliyah in Batanghari Regency, Jambi Province. Using a qualitative multi-site case study design, the research involved participants from each school principal and Islamic Education teacher with diverse accreditation (A, B, C). Data were collected through observation, interviews, and documentation, and analyzed using Miles, Huberman, and Saldaña's interactive model. Findings reveal that the three dimensions (madrasah leadership, institutional culture, and instructional practices work) synergistically to implement qaulan-based communication through integrity, harmony, and pedagogical effectiveness. Together, those created an integrative, humane, and transformative communication environment that strengthens students’ religious character and enhanced the quality of interactions within the madrasah. The implications of this study highlighted the importance of systematically integrating qaulan-based communication into educational policies, leadership practices, and classroom strategies to foster a humane and transformative learning environment.
Adaptive Learning and Generative AI in Mathematics Teacher Education: A Systematic Review Maryati, Iyam; Harun, Makmur; Gumilar, Surya; Rahayu, Ayu Puji
International Journal of Review in Mathematics Education Volume 1 No. 1: March 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/ijrime.15936

Abstract

This study presents a systematic review of the current literature on the integration of adaptive learning and generative AI (GenAI) in developing technological pedagogical content knowledge (TPACK) and statistical literacy of prospective mathematics teachers. By analyzing 76 selected articles published between January 2023 and May 2025, this study uses the PRISMA framework and thematic synthesis with the help of NVivo 12 Plus software. The results of the study indicate that adaptive learning environments supported by GenAI can strengthen learning personalization, provide responsive feedback, and visualize content, which significantly contribute to the development of TPACK, especially in the TPK and TCK domains. In addition, GenAI supports the strengthening of statistical literacy through data-driven instructional tools that foster the ability to interpret, represent, and understand the context of data. This study successfully formulated a conceptual framework for adaptive learning integrated with GenAI that reflects the pedagogical needs and specific content in mathematics education. These findings have important implications for teacher education programs, especially in facilitating professional competencies that are adaptive to technological advances and the demands of ethical and reflective data-driven learning.