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Journal of Pedagogi
Published by PT Anagata Sembagi Education
ISSN : -     EISSN : 30469554     DOI : https://doi.org/10.62872/arcvet10
Core Subject : Education,
Education
The journal publishes all original articles on current issues and trends occurring internationally within the scope of education such as, science education, social science, religion, language, etc.
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 185 Documents
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Constitutional Civic Behavior Model of Constitutional Law Students in Facing Digital Governance Transformation Aminudin; Ikbal; Risman Munanto
Journal of Pedagogi Vol. 3 No. 4 (2026): Journal of Pedagogi - August
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/qpqyq319

Abstract

This study aims to develop a Constitutional Civic Behavior model for Constitutional Law students in responding to the transformation of digital governance, which increasingly influences the relationship between citizens, technology, and digital governmental systems. The study examines the effects of Digital Political Literacy (DPL), Policy Literacy (PL), and AI Governance Awareness (AIGA) on Political Trust (PT), Constitutional Identity (CI), and Constitutional Civic Behavior (CCB), while also evaluating the mediating roles of PT and CI in the relationship between digital literacy, policy literacy, AI awareness, and constitutional civic behavior. Employing a quantitative survey design, data were collected from 120 respondents through purposive sampling. Research instruments utilized a 5-point Likert scale questionnaire, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that among the direct effects tested, only Policy Literacy (PL) significantly influences Political Trust (PT), and Constitutional Identity (CI) significantly influences Constitutional Civic Behavior (CCB). Digital Political Literacy (DPL) and AI Governance Awareness (AIGA) do not show significant effects on PT or CI, while PT exhibits a negative and significant effect on CCB. Mediation analysis indicates that neither PT nor CI significantly mediates the relationship between DPL, PL, or AIGA and CCB. These findings underscore that the internalization of Constitutional Identity remains the dominant factor in shaping students' constitutional civic behavior.  
Integrating Computational Thinking into Mathematics Instruction to Enhance Higher-Order Thinking Skills (HOTS) Nuril Huda
Journal of Pedagogi Vol. 3 No. 4 (2026): Journal of Pedagogi - August
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/t50sx702

Abstract

Higher-order thinking skills (HOTS) remain difficult to cultivate in mathematics classrooms that emphasize procedural fluency over structured, algorithmic reasoning. This study investigates whether integrating computational thinking (CT)—decomposition, pattern recognition, abstraction, and algorithm design—into mathematics instruction can significantly improve students' HOTS. A quantitative, quasi-experimental, nonequivalent pretest-posttest control-group design was used, involving two intact classes: an experimental group taught through a CT-integrated instructional model and a control group taught conventionally. HOTS was measured with a validated essay test aligned with the analyzing, evaluating, and creating levels of Bloom's revised taxonomy. Data were examined through normality and homogeneity tests, N-gain scores, and an independent-samples t-test supplemented by ANCOVA with the pretest as covariate. Results show the experimental group achieved a significantly higher mean N-gain, in the moderate-to-high category, than the control group, with significant differences (p < .05) across all HOTS indicators, most notably analyzing and creating. These findings extend prior CT-mathematics research, which has largely been correlational, perception-based, or review-based, by providing direct experimental evidence linking structured CT integration to measurable HOTS gains and offering an empirically validated, technology-independent instructional design for mathematics teachers and curriculum developers.
Technology-Based Learning in Higher Education: Current Trends and Future Perspectives Nur Patria Pujitama Sari; Wildha Banuyekti
Journal of Pedagogi Vol. 3 No. 4 (2026): Journal of Pedagogi - August
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/c6z3b970

Abstract

The rapid diffusion of digital technologies has reshaped teaching and learning practices in universities worldwide, yet the scholarly literature on this transformation remains fragmented across disciplines, technologies, and institutional contexts. This study systematically reviews current trends and future perspectives of technology-based learning in higher education. Following the PRISMA 2020 protocol, a structured search across Scopus, Web of Science, and Google Scholar identified 246 records, of which 25 peer-reviewed articles published between 2023 and 2025 met the inclusion criteria and were analyzed thematically. Five dominant themes emerged: artificial intelligence-driven personalization and intelligent tutoring, extended reality and immersive simulation, digital-twin and game-based engineering education, institutional digital transformation and digital literacy, and technology-acceptance frameworks such as UTAUT. The findings indicate that technology-based learning consistently improves engagement, motivation, and, in most contexts, cognitive and skill-based outcomes, although effectiveness is moderated by learner readiness, disciplinary context, and institutional infrastructure. Persistent gaps include limited longitudinal evidence, uneven digital-equity considerations, and underexplored ethical and pedagogical implications of generative artificial intelligence. The review offers an integrated framework linking technological, pedagogical, and institutional dimensions of digital transformation and outlines an agenda for future research and policy on sustainable, equitable technology integration in higher education
Principal Management Strategies for Implementing Artificial Intelligence in Learning Assessment Abdul Kodir Nurhasan; Muhammad Rizal; Syaeful Rokhman
Journal of Pedagogi Vol. 3 No. 4 (2026): Journal of Pedagogi - August
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/jg66mt85

Abstract

The rapid diffusion of artificial intelligence (AI) into schooling has begun to reshape how student learning is measured, yet the managerial pathways through which principals translate this technology into legitimate assessment practice remain poorly understood, particularly outside higher-education settings. This article examines the management strategies principals employ when implementing AI in learning assessment at the school level. Using a qualitative descriptive multi-site case study design, data were gathered through semi-structured interviews, classroom and meeting observations, and documentation review across six schools purposively selected for varying stages of AI adoption. Data were triangulated by source, method, and time, then analyzed using the Miles and Huberman interactive model of condensation, display, and conclusion drawing. Findings show that principals operationalize AI-assessment implementation through four interrelated managerial functions planning, organizing, actuating, and controlling supported by a cross-cutting emphasis on capacity building and stakeholder communication. The study contributes a context-grounded, function-based model that integrates classical school management theory with contemporary AI-governance concerns such as data ethics, algorithmic bias, and teacher agency, offering both theoretical refinement and practical guidance for principals navigating AI-based assessment reform.
The Use of Artificial Intelligence Chatbots Based on Natural Language Processing (NLP) to Improve Mandarin Speaking Skills David Darwin; Febi Nur Biduri; Reny Syafrida
Journal of Pedagogi Vol. 3 No. 4 (2026): Journal of Pedagogi - August
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/86f9bb47

Abstract

Mandarin is one of the most demanding languages for adult foreign learners to speak fluently, owing to its tonal system, syllable-based homophony, and the absence of alphabetic correspondence between sound and script. Conventional classroom instruction rarely supplies the volume of individualized, low-stakes oral practice that tonal accuracy and fluency require. Artificial intelligence (AI) chatbots built on natural language processing (NLP) offer a scalable alternative, simulating conversational partners that can listen, transcribe, evaluate, and respond to spoken language in real time. This article reports a systematic literature review synthesizing 25 empirical and conceptual studies, published between 2021 and 2026, on the use of NLP-based AI chatbots to improve second-language speaking skills, with particular attention to Mandarin/Chinese-as-a-foreign-language contexts. Following a PRISMA-informed search and screening procedure across Google Scholar, Scopus, ERIC, and major computer-assisted language learning journals, studies were thematically synthesized. The review finds consistent evidence that chatbot-mediated practice improves oral fluency, pronunciation, and willingness to communicate while reducing speaking anxiety, but that this evidence is concentrated in English-as-a-foreign-language contexts; direct evidence on Mandarin tone acquisition remains scarce. The review's novelty lies in explicitly separating general EFL findings from the small Mandarin-specific evidence base and mapping NLP subcomponents onto discrete Mandarin speaking sub-skills. Implications for chatbot design and future research are discussed.

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