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Jurnal Pendidikan Progresif
Published by Universitas Lampung
ISSN : 20879849     EISSN : 25501313     DOI : https://doi.org/10.23960/jpp
Core Subject : Education,
Education
urnal Pendidikan Progresif is an academic journal that published all the studies in the areas of education, learning, teaching, curriculum development, learning environments, teacher education, educational technology, educational developments from various types of research such as surveys, research & development, experimental research, classroom action research, etc. Jurnal Pendidikan Progresif covers all the educational research at the level of primary, secondary, and higher education. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on Educational advancements and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of Education. Topics of Interest include, but are not limited to, the following Disaster literacy and Risk Management Education Ethnopedagogy-based STEM Education Integrating technology into the curriculum: Challenges & Strategies Collaborative & Interactive Learning Tools for 21st Century learning Learning Analysis Education Management Systems Education Policy and Leadership Business Education Virtual and remote laboratories Pedagogy Enhancement with E-Learning Course Management Systems Teacher Evaluation Curriculum, Research, and Development Web-based tools for education Games and simulations in Education Learning / Teaching Methodologies and Assessment Counselor Education Student Selection Criteria in Interdisciplinary Studies Global Issues in Education and Research Technology Support for Pervasive Learning Artificial Intelligence, Robotics and Human-computer Interaction in Education Mobile/ubiquitous computing in education Web 2.0, Social Networking, Blogs and Wikis Multimedia in Education Educating the educators Professional Development for teachers in ICT
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 797 Documents
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Trends in Artificial Intelligence and Digital Technology Research in Islamic Education: A Scopus-Based Bibliometric Analysis Eric Wahyu Dimas Pradana; Adhi Setiyawan; Muchamad Mufid
Jurnal Pendidikan Progresif Vol 16, No 3 (2026): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v16i3.pp1562_1583

Abstract

The objective of this research is to outline the trends, intellectual framework, and thematic progression of artificial intelligence (AI) and digital technology within Islamic education, using Scopus database records from 2018 to 2026. The study focuses on publication rates, top authors, key institutions, and leading countries, and identifies research gaps to guide future studies. Guided by the PRISMA 2020 guidelines, an initial 225 documents from Scopus underwent identification, screening, and eligibility evaluations, resulting in a final selection of 52 articles from 35 journals, written by 196 authors. A quantitative assessment was conducted via the Bibliometrix (R package) and Biblioshiny, encompassing performance metrics, thematic mapping, and visual networks of keyword co-occurrences. The research area shows significant expansion, boasting a 27.54% Annual Growth Rate (AGR), well above the average for scientific publications, and an international collaboration rate of 30.77%. With 224 citations, Indonesia leads in citation count, while UIN Sunan Kalijaga is the top-contributing institution. The analyzed data includes 225 author keywords and 2,766 references, with an average document age of 1.73 years, indicating the topic's novelty. Thematic evaluations highlight "Islamic education" and "higher education" as primary drivers. Meanwhile, "ChatGPT," "generative AI," "sentiment analysis," and "deep learning" are considered niche topics yet to enter mainstream discussions. Although "digital transformation" and "Islamic religious education" stand out as strategic themes, notable gaps remain in methodologies, themes, geography, and values, especially within madrasah and pesantren contexts. The results suggest that studies on AI in Islamic education are still in their foundational, exploratory phases. Consequently, three main strategies are proposed: enhancing global partnerships, conducting empirical research on generative AI grounded in Islamic principles, and developing AI tools tailored to Islamic educational environments. Keywords: artificial intelligence, Islamic education, bibliometric analysis, Scopus, digital technology.
An Integrated Diagnostic Profile of Undergraduate Students’ Cognitive Processes, Mental Models, and Learning Interest in Moon Phase Concepts Using Rasch Measurement and Qualitative Analysis Neli Oktavia Suhyani; Winny Liliawati; Ika Mustika Sari; Feri Apryandi; Fitria Arifiyanti; Beyzanur Hopa
Jurnal Pendidikan Progresif Vol 16, No 3 (2026): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v16i3.pp1663-1678

Abstract

This study profiled undergraduate students’ cognitive processes, mental models, and learning interest regarding moon phases using an integrated empirical approach. A convergent mixed-methods design was employed in which quantitative and qualitative data were collected concurrently and then merged. Cognitive processes were measured using an eight-item test aligned with the revised Bloom’s taxonomy (C3–C5), and learning interest was assessed using a Likert scale questionnaire; mental models were inferred from students’ written explanations and confirmed through semi-structured interviews. A total of 65 first-year students from Universitas Pendidikan Indonesia participated through purposive sampling. Quantitative data were analyzed using descriptive statistics and the Rasch model, whereas qualitative data were analyzed thematically. The Rasch analysis indicated acceptable item fit (MNSQ 0.65–1.27), high item reliability (0.96), and acceptable person reliability (0.73), although the two most difficult items (CE1 and T) exceeded most students’ ability level. Mean performance decreased systematically across cognitive levels, from applying (C3) to analyzing (C4) and evaluating (C5). Mental-model analysis showed that 40.0% of students held Initial models, 50.8% Synthetic models, and 9.2% Scientific models, while 61.5% reported high learning interest. These results reveal a consistent gap between students’ motivational readiness and their cognitive–conceptual readiness, indicating that high interest functions as an entry condition for engagement rather than an indicator of conceptual mastery. These findings indicate that students’ high learning interest should be treated as motivational readiness rather than evidence of conceptual mastery, thereby highlighting the need for scaffolded, diagnostic-based, and differentiated astronomy instruction. Keywords: cognitive processes, learning interest, mental models, moon phases, rasch analysis.
Cognitive Behavioral Therapy Intervention: Enhancing Vocational High School Students’ Enthusiasm in Islamic Education Rizqi Dwicahyanti; Askar Askar; Mirnawati Mirnawati
Jurnal Pendidikan Progresif Vol 16, No 3 (2026): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v16i3.pp1584-1604

Abstract

Cognitive Behavioral Therapy (CBT) represents one of the most well-established psychotherapeutic approaches, centered on the reconstruction of negative thoughts and maladaptive beliefs into more positive and psychologically tenable alternatives. This study examines the effectiveness of CBT in enhancing students' enthusiasm for learning in Islamic Religious Education (PAI) at SMK Negeri 3 Palu. Confronting the persistent challenge of diminished motivational engagement in Islamic Education contexts, the study investigates whether a psychologically grounded intervention rooted in cognitive restructuring can significantly elevate students' affective involvement in the subject. A quasi-experimental design incorporating pre-test and post-test control groups was employed, involving 26 students divided into an experimental class and a control class. Hypothesis testing was conducted using an Independent-Samples t-test after verifying the assumptions of normality and homogeneity. Instrument reliability was confirmed by a Cronbach's alpha value exceeding the accepted threshold. Statistical analysis was conducted primarily using JASP software. At the outset, both the experimental and control groups were positioned at equivalent levels, as evidenced by a homogeneity probability value (sig.) of 0.907, which surpasses the 0.05 threshold. Hypothesis analysis further revealed a significant difference between pre-test and post-test scores, with a probability value (sig.) of 0.034, falling below the 0.05 significance level, indicating that a meaningful change occurred following the application of the CBT approach. Departing from this shared baseline, the cognitive behavioral therapy implemented within the experimental class yielded results that substantively confirm CBT's effectiveness in enhancing PAI learning enthusiasm among students in the experimental group. Keywords: cognitive behavioral therapy, enthusiasm, Islamic studies, journaling-self monitoring.
Fostering Algorithmic Thinking through AI-Supported STEM Activities: Experimental Study Using Cacao Disease Classification Firma Nur Muttakin; Dafik Dafik; Zainur Rasyid Ridlo; Udaya Sri Kakarla
Jurnal Pendidikan Progresif Vol 16, No 3 (2026): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v16i3.pp1679-1703

Abstract

This study investigated the effect of AI-integrated STEM activities using cocoa leaf disease classification materials on undergraduate students’ algorithmic thinking skills. This quasi-experimental study used a non-randomized pretest–posttest comparison design and involved 66 undergraduate students. Data were collected using an algorithmic thinking test and an instrument validation sheet. The instrument demonstrated acceptable content validity, with a mean validation score of 4.57, a feasibility percentage of 91.38%, Aiken’s V coefficient of 0.892, and very high internal consistency (Experimental α = 0.942 and Control α = 0.938 ). The data were analyzed using assumption testing, Welch’s t-tests, gain-score analysis, and ANCOVA. The experimental group achieved a substantially larger mean gain than the control group (d = 1.43) and a higher average normalized gain (〈g〉 = 0.87 versus 0.52), and outperformed the control group on all seven algorithmic thinking indicators (d = 0.72 to 1.60). The ANCOVA indicated a significant group difference in posttest performance, F(1, 63) = 29.302, p < .001, with a higher adjusted mean in the experimental group (M = 76.8) than in the control group (M = 66.5). However, the pretest covariate explained virtually none of the posttest variance, so the covariance adjustment was negligible, and the two intact classes differed significantly at baseline. Because posttest variance was also heterogeneous, interpret the findings with appropriate caution and understand them as associational rather than causal. These results suggest that AI-integrated STEM activities based on cocoa leaf disease classification may support the development of undergraduate students’ algorithmic thinking through structured, iterative, and evidence-based learning processes. Keywords: algorithmic thinking, STEM activities, cacao diseases, classification, undergraduate students.
Exploring Assessment Literacy & Practice among Geography Teachers In Indonesian Senior High Schools: A Survey Study Sriyanto Sriyanto; Edi Kurniawan; Mohammad Syifauddin; Hanifah Mahat
Jurnal Pendidikan Progresif Vol 16, No 3 (2026): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v16i3.pp1605-1623

Abstract

Assessment literacy is a critical competency that teachers must possess to support high-quality assessment practices and improve student learning outcomes. However, research on assessment literacy among geography teachers remains relatively limited, particularly in Indonesia. This study investigated the assessment literacy and assessment practices of Indonesian secondary school geography teachers using survey data collected from multiple regions and identified differences between public and private schools. The study employed a quantitative approach with a cross-sectional comparative survey design. A total of 271 geography teachers from various regions across Indonesia participated in the study. The research instrument was developed based on the concepts of Assessment for Learning (AfL) and Data-Based Decision Making (DBDM). Data were analyzed using descriptive statistics and comparative tests. The results revealed that geography teachers demonstrated moderate to high levels of assessment literacy and assessment practices. The highest competencies were observed in analyzing and interpreting assessment results (83.37%), providing feedback to students (83.33%), and principal support for assessment implementation (81.62%). In contrast, scores were relatively lower for the use of information technology in assessment (75.62%), teachers’ attitudes and behaviors toward assessment (77.16%), and professional collaboration among teachers (78.58%). Furthermore, most dimensions of assessment literacy and assessment practices did not differ significantly between geography teachers in public and private secondary schools in Indonesia. These findings underscore the need for continuous professional development programs focused on strengthening digital assessment literacy, enhancing professional collaboration, and optimizing assessment as an integral part of instructional improvement. This study contributes to assessment literacy research in geography education and provides an empirical foundation for designing teacher training programs in Indonesia. Keywords: assessment literacy, assessment for learning, assessment data, formative assessment, data-based decision making.
Humanizing AI in English Education for Society 5.0: Narrative Reconstructions of Teacher and Learner Digital Identities Pikir Wisnu Wijayanto; Dodi Mulyadi; Yahdi Siradj
Jurnal Pendidikan Progresif Vol 16, No 3 (2026): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v16i3.pp1704-1732

Abstract

Generative AI is widely used in English learning, yet how teachers and learners narrate it as part of their evolving digital identities remains under-researched. This study explores (1) teachers' and students' narratives of AI-mediated English learning, (2) how these narratives reflect digital-identity transformation, and (3) pedagogical principles for humanizing AI. This qualitative narrative inquiry involved five English educators and 15 students from secondary and higher education in Indonesia. Data were collected from interviews, reflective narratives, and anonymized learning artifacts, and analyzed using deductive-inductive narrative thematic analysis. Analysis identified five themes: (1) a shift from apprehension to pedagogical negotiation; (2) reconstruction of learner agency through reflective engagement; (3) reconfiguration of teacher identity from corrector to ethical mediator; (4) emergence of collaborative digital learning identities; and (5) counter-narratives exposing tensions around dependence, authorship, and diminished human interaction, underpinning the proposed Humanized AI-Mediated Digital Learning Identity (HADLI) framework. Generative AI neither humanizes nor dehumanizes English education; its value is co-constructed through teacher facilitation, learner reflection, and ethical transparency, with implications for teacher education, curriculum, and AI policy under Society 5.0. Keywords: humanizing AI, english education, digital learning identity, narrative inquiry, Society 5.0.
Learning Behavior Components as Predictors of Third-Grade Achievement in Banten Reni Apriani; Abdul Qodir; Fuzi Arianto; Supaphorn Akkapin
Jurnal Pendidikan Progresif Vol 16, No 3 (2026): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v16i3.pp1624-1640

Abstract

This study examines the partial and simultaneous effects of five learning behavior components: attitude, learning motivation, learning strategies, memory, and metacognition, on the academic achievement of third-grade students in Banten Province, Indonesia. A quantitative explanatory survey was conducted involving 94 third-grade students selected through intact-group cluster sampling from three public elementary schools in Serang, Cilegon, and Tangerang. Learning behavior was measured using Likert-scale questionnaires, and academic achievement was assessed using semester report card grades. Response quality was evaluated using the Rasch measurement model, and Ordinal Logistic Regression was employed for analysis. Results indicated that the overall model significantly predicted students' academic achievement (χ² = 12.414, p = 0.030; Nagelkerke pseudo-R² = 0.157). Among the five components, memory was the only statistically significant predictor (B = 0.215, OR = 1.24, p = 0.020), while attitude, learning motivation, learning strategies, and metacognition showed no significant unique effects. It is concluded that learning behavior is a multidimensional construct with unequal contributions from its components, and that memory emerged as the strongest independent predictor. These findings suggest that elementary teachers should prioritize instructional practices strengthening students' memory processes through retrieval practice and structured learning activities. Keywords: academic achievement, elementary school, learning behavior, memory, metacognition.

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