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All Journal JRAMathEdu (Journal of Research and Advances in Mathematics Education) JPP (Jurnal Pendidikan dan Pembelajaran)
Nadya Syifa Utami
Universitas Media Nusantara Citra
Mathematics

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Nearpod-assisted PBL enactment within the TPACK framework: Transforming mathematics learning to enhance problem solving skills and digital literacy Hafsah Adha Diana; Nadya Syifa Utami; Fatimah Fatmawati
JRAMathEdu (Journal of Research and Advances in Mathematics Education) Volume 11, Issue 2, April 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jramathedu.v11i2.14386

Abstract

Technology integration in mathematics learning requires a theoretically grounded design rather than simple digital adoption. Within the Technological Pedagogical and Content Knowledge (TPACK) framework, Problem-Based Learning (PBL) represents pedagogical knowledge, and Nearpod represents technological knowledge. This study does not propose a new model; instead, it operationalizes TPACK through a structured instructional enactment that aligns statistical content, PBL inquiry phases, and Nearpod affordances. A quasi-experimental pretest–posttest control group design was employed with twelfth-grade students. Baseline equivalence between the experimental and control groups was confirmed using an independent-samples t-test. Enhancement in mathematical problem-solving was analyzed using gain scores, independent-samples t-tests, and two-way ANOVA. Results revealed a significant difference in scores gained between groups. A significant main effect of the instructional approach and an interaction effect with initial ability were found. Digital literacy also differed significantly between groups. These findings demonstrate that TPACK becomes instructionally meaningful when statistical content is transformed through structured inquiry and technology-mediated representation, although students’ initial mathematics ability moderates’ effectiveness.
Research Evolution of Artificial Intelligence in Mathematics Learning: A Bibliometric Review from 2015 to 2026 Nadya Syifa Utami; Hafsah Adha Diana; Verra Budhi Lestari; Sani Sahara
JPP (Jurnal Pendidikan dan Pembelajaran) Vol. 33 No. 1 (2026)
Publisher : Lembaga Pengembangan Pendidikan dan Pembelajaran, Universitas Negeri Malang in Collaboration with Asosiasi Pendidik dan Pengembang Pendidikan Indonesia (APPI)

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Abstract

Background: The recent growth of Artificial Intelligence (AI) has attracted increasing attention in mathematics learning research, yet a comprehensive understanding of its development remains limited.Objective: This study aims to explore the research evolution of AI in mathematics learning from 2015 to 2026 using a bibliometric approach.Method: Data were collected from the Scopus database, yielding 169 publications comprising journal articles and conference papers. Analysis was conducted using Bibliometrix and VOSviewer to examine publication trends, leading sources, contributing countries, influential references, keyword cooccurrence, and thematic evolution.Results: The findings reveal a significant growth in publications, particularly after 2021, reflecting expanding research interest. The United States and China are the most productive contributors, while several recent works demonstrate strong citation impact. Keyword and thematic analyses reveal a focus on the intersection of AI and mathematics education, with emerging topics such as generative AI, chatbots, and personalized learning.Conclusion: Overall, the research of AI in mathematics learning has shifted from general technological exploration toward more pedagogically oriented applications. These findings suggest that educators and curriculum developers should prioritize AI tools for personalized and effective learning, while researchers are encouraged to focus empirically evaluating their impact in real classroom contexts.
Co-Authors Ade Riastuti Al Jupri Aswin Fatimah Fatmawati Hafsah Adha Diana Khairunnisa Nurdiyah Kurniati Putri Armania Sani Sahara Verra Budhi Lestari Woro Anglia Banda Sutomo