Article Per Year (5 Year)
p-Index From 2021 - 2026
1.497
P-Index
This Author published in this journals
All Journal Tadris: Jurnal keguruan dan Ilmu Tarbiyah JURNAL PETIK Mosharafa: Jurnal Pendidikan Matematika Jurnal PkM MIFTEK Research in Physics Education Badranaya: Jurnal Pengabdian kepada Masyarakat
Surya Gumilar, Surya
Pendidikan Guru Sekolah Dasar, Sekolah Tinggi Sebelas April
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 12 Documents
Search

 1   2 
A Systematic Literature Review of Tier Tests as Diagnostic Tools in Specific Areas of Science Anam, Rifat Shafwatul; Gumilar, Surya
Tadris: Jurnal Keguruan dan Ilmu Tarbiyah Vol 9 No 1 (2024): Tadris: Jurnal Keguruan dan Ilmu Tarbiyah
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/tadris.v9i1.17717

Abstract

A tier test is used in science teaching and learning to assess students’ understanding of specific scientific domains. Despite its popularity, limited research has investigated the development of this test. This study aimed to explore the development of tier tests in science education, considering aspects such as representation in selected science education journals, regions, contributors, levels of education, most-cited articles, and specific scientific domains. A systematic literature review was conducted, manually examining 35 articles from selected journals: the International Journal of Science Education (IJSE), the Journal of Research in Science Teaching (JRST), Science Education (SE), the International Journal of Science and Mathematics Education (IJMA), and Research in Science Education (RISE). The findings indicate that some journals published research on tier tests, while others did not. Notably, the dominant scientific domains were biology, chemistry, and physics, which is consistent with findings from other studies focusing on scientific reasoning tests. Finally, the implications of these findings will be discussed.
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.
Co-Authors Abdulloh, Syamsan Adimayuda, Rizal Agustina, Remilda Ali Ismail Amalia, Irma Fitria Anam, Rifat Shafwatul Andriyano, Ariyo Ashel, Hazrati Asyah, Cha Cha Nisya Deni Moh Budiman, Deni Moh Dhaifullah, Dafa Eri Satria Fadzilah, Fahmi M Fitria Amalia, Irma Hakim, Annas Nurul Hana Pertiwi Harun, Makmur Ibnu Hajar Ilham Maulana Intan, Neng Wihelen Sri IYAM MARYATI Jamil, Rivansyah Syaiful Maulana, Adnan Fawwaz Melani, Nisa Murrydan, Kuwatika Nawawi, Irpan Nopharipaldi, Slamet Nur'aeni, Shifa Nurahman, Arip Nurhaliza, Siti Salsa Rahayu, Ayu Puji Rahmah, Alya Siti sari, Lasmita Setiawan, Dzulkifli Putra