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JPP (Jurnal Pendidikan dan Pembelajaran)
Published by Universitas Negeri Malang
ISSN : 2302996X     EISSN : 25802313     DOI : 10.17977
Core Subject :
JPP (Jurnal Pendidikan dan Pembelajaran) publishes article on education and learning in general. Contains articles/results of research results written by experts, scientists, practitioners, and reviewers in educational and learning disciplines. Some JPP scopes include: Theory and foundation of education and learning Philosophy of education and learning Educational and learning technology Educational and learning media Education evaluation Education management Educational and learning innovations Education for all Formal education Informal education Nonformal education Rural education Urban education Education and learning curriculum Educators and students Education and learning policies Learning methods and strategies Learning assessment
Arjuna Subject : -
Articles 115 Documents
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Child-Centered User Interface Design for Early Language Learning Applications: A Qualitative Comparative Study Fenie Fedora Wijaya; Shienny Megawati Sutanto
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: In the digital learning era, user interface (UI) design plays an important role in shaping how children engage with educational applications, particularly in early language learning contexts. however, many applications are not fully aligned with children’s cognitive, emotional, and developmental needs. Objective: This study aims to examine how UI design in child-centered language learning applications can be optimized to support children’s cognitive and emotional needs while enhancing learning outcomes. Method: This study adopts a qualitative comparative approach, integrating a literature review, visual analysis of two English-language learning applications (Duolingo ABC and BOOKR Class), semi-structured interviews with three design experts, and focus group discussions with six children aged 5–8. Data were collected through observation, expert validation, and user interaction, and analyzed using thematic analysis. Results: The findings indicate that intuitive, minimal-step navigation reduces cognitive load and supports task completion; balanced color strategies sustain attention without overstimulation; large sans-serif typography improves reading accuracy; and expressive mascots enhance emotional engagement. However, children’s preferences vary across developmental stages, highlighting the need for adaptive rather than standardized design approaches. Conclusion: UI design functions as a pedagogical mediator that influences comprehension, engagement, and early literacy development. The study proposes a child-centered guideline integrating cognitive simplicity, emotional resonance, and context- ensitive design decisions, contributing to educational technology by demonstrating how developmentally aligned interface design can improve both usability and learning 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.
Teachers’ Readiness to Adopt AI for Teaching Materials Development: The Impact of AI Literacy Training at a Senior High School in Depok Kiki Fauziah; Hanif Inamullah; Aviazka Firdhaussi; Wiwit Ratnasari; Sadewa Ersa Pamungkas; Annisa Rizky
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: This article analyses teachers’ readiness to adopt artificial intelligence when developing teaching materials. It explicitly measures teachers’ competency after participating in AI literacy training. Objective: This study aimed to determine whether the training can improve high school teachers’ understanding and competence in utilising generative artificial intelligence as a tool for developing teaching materials. Method: This quantitative study employed a one-group pretest–posttest design and a pre-experimental method. Fifty teachers at SMAN 1 Depok were chosen as responders using a total sampling technique. A questionnaire was used to gather information in order to assess the effectiveness of the AI literacy training program. In order to supplement the quantitative data, observations and interviews were also carried out. Results: The study's findings show that instructors at SMAN 1 Depok are highly prepared to incorporate AI into the creation of instructional materials. The AI literacy training has effectively improved the teachers’ perceptions, knowledge, and skills while applying AI in educational contexts. Conclusion: Seven variables measured in this study, which include aspects of understanding, skills, views, ethics, threat perception, innovation, and job satisfaction, experienced a statistically significant increase (p < 0.05), with a large effect size (Cohen’s d > 0.8) in almost all aspects, indicating a substantial practical impact of the training.
Artificial Intelligence in Education: Readiness, Perceptions, and Implementation in an Early Childhood Teacher Education Program at Universitas Mataram Fahruddin; Mansur Hakim; Hasanuddin Chaer; Lale Dewi Nurlita Safitri
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: Early Childhood Teacher Education Program (PGPAUD) requires complex pedagogical translation of content into concrete learning experiences. In this context, Artificial Intelligence (AI) has the potential to support prospective teachers in developing personalized learning media, generating age-appropriate instructional content, and simulating interactive environments aligned with children’s cognitive and socio-emotional development.Objective: This study aims to examine the readiness, perceptions, and implementation of AI in learning activities within the PGPAUD program, Faculty of Teacher Training and Education, Universitas Mataram.Method: This research employed a descriptive qualitative approach. The participants consisted of lecturers and students of the PGPAUD program. Data were collected through interviews, observations, and documentation using relevant research instruments. The data were analyzed using qualitative data analysis techniques, including data reduction, data display, and conclusion drawing.Results: The findings indicate that lecturers and students demonstrate adequate digital readiness. However, the integration of AI in instructional practices remains limited. While AI improves learning efficiency and access to information, its use remains largely individual and exploratory due to limited training, lack of experience, and a absence of institutional policies.Conclusion: Integrating AI into PGPAUD requires institutional support, targeted training, and clear policy frameworks. This study helps Indonesian higher education design adaptive, AI-integrated curricula, particularly for teacher education.
Artificial Intelligence in Primary School Writing Instruction: A Bibliometric Analysis of Global Research Trends (2016–2026) Nurul Umrotullatifah; Rina Heryani; Angga Hadiapurwa
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 rapid integration of artificial intelligence (AI) into primary education has generated substantial scholarly interest, yet no comprehensive bibliometric study has systematically mapped the intersection of AI and writing instruction at the primary school level.Objective: This study aims to analyze global research trends, identify key contributors and collaboration patterns, and uncover dominant thematic clusters within this domain over the period 2016–2026.Method: A bibliometric research design was employed, drawing on a corpus of 2,277 documents retrieved from the Scopus database in April 2026, filtered to include only English-language journal articles. Data visualization and network mapping were conducted using VOSviewer, encompassing keyword co-occurrence analysis, author co-authorship mapping, country collaboration networks, and overlay visualization by year.Results: The findings reveal an exponential growth in publication output, rising from five documents in 2016 to a peak of 1,023 in 2025, with a critical inflection point emerging in 2022 coinciding with the public release of generative AI tools. China, the United States, and Indonesia emerged as the three most productive nations, while four thematic clusters were identified: AI tools and writing performance, affective and motivational dimensions, literacy and pedagogy, and machine learning approaches.Conclusion: The study demonstrates that the field has matured from technically oriented inquiry toward a holistic, learner-centered research agenda. These findings carry significant implications for researchers, educators, and policymakers, underscoring the urgency of developing ethically grounded, contextually inclusive frameworks for AI integration in primary writing instruction, particularly for underrepresented linguistic and cultural contexts globally.

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