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Journal of Paddisengeng Technology
Published by PT. Sinergi Bersahaja Sejahtera
ISSN : -     EISSN : 30893046     DOI : https://doi.org/10.65224/jopate
Core Subject :
Journal of Paddisengeng Technology (JOPATE) is a peer-reviewed scientific journal that publishes original research articles and scholarly reviews concerning developments in science, technology, and education. The journal covers educational sciences, educational administration, educational technology, and interdisciplinary applications of technology in teaching, learning, and institutional development. Every manuscript undergoes an initial editorial assessment followed by a peer-review process involving reviewers with expertise relevant to the manuscripts subject.
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Articles 7 Documents
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Search results for , issue "vol. 2 no. 3 (2026)" : 7 Documents clear
Generative AI-Assisted Competitive Microlearning Strategy: Development and Validation of the Plomp Model in Classroom Teacher Education in Finland Juha Laaksonen; Antti Vainio; Heidi Korhonen
Journal of Paddisengeng Technology Vol. 2 No. 3 (2026)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v2i3.284

Abstract

Background. The rapid adoption of generative artificial intelligence (AI) in education has created challenges in designing responsible and adaptive learning strategies. Meanwhile, competitive elements in gamified learning remain debated due to inconsistent effects on learner engagement. Purpose. This research aimed to develop and evaluate a generative AI-assisted competitive microlearning strategy for improving instructional media development skills among Finnish Luokanopettajakoulutus (Class Teacher Education) students. Novelty. This study introduces a novel instructional design that integrates generative AI, microlearning, and optional quality-based competition. Unlike conventional competitive gamification approaches, the proposed strategy recognizes learner differences by examining whether competition produces varied outcomes across learning groups Method. Using the Plomp development model, the study involved 79 undergraduate students from four parallel classes. Data from expert validation, practicality questionnaires, and product assessments were analyzed using Aiken’s V and descriptive statistics. Results. The strategy achieved high validity (Aiken’s V = 0.87) and strong practicality (83.1% student response; 85.9% lecturer response). Variation in competition participation (41–62%) indicated different effects among learner groups. Conclusion. The findings contribute an adaptive AI-assisted microlearning framework that balances innovation, learner diversity, and educational equity in teacher education.
ChatGPT, Achievement Motivation, and Problem-Solving: Evidence from Thai and Cambodian Undergraduates Ming Pong; Sokha Dara; N. S. Jayasundara
Journal of Paddisengeng Technology Vol. 2 No. 3 (2026)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v2i3.289

Abstract

Background. The rapid global adoption of ChatGPT has raised growing interest in its role in supporting student learning, yet the effectiveness of generative AI tools in enhancing higher-order cognitive skills such as problem-solving may depend on individual learner characteristics that remain underexplored. Purpose. This quantitative study aimed to examine the relationship between ChatGPT usage and problem-solving ability among students enrolled in a Media Design course, and to test whether this relationship is moderated by achievement motivation. Method. The study involved 115 university students from four intact classes across two higher education institutions in Thailand and Cambodia. Data were collected through a survey questionnaire and analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM), preceded by a measurement invariance test (MICOM) to assess the appropriateness of pooling data across the two national samples. Results. The findings indicate that ChatGPT usage was positively and significantly associated with problem-solving ability (? = 0.386, p < 0.001), as was achievement motivation (? = 0.291, p < 0.01). The interaction between ChatGPT usage and achievement motivation also showed a significant positive effect (? = 0.157, p < 0.05), indicating that achievement motivation strengthens the relationship between ChatGPT usage and problem-solving ability. The model explained 44.6% of the variance in problem-solving ability (R² = 0.446). Conclusion. This study has significant implications for instructional practices in higher education settings, particularly for lecturers designing AI-integrated learning activities. By understanding how achievement motivation shapes students’ benefit from ChatGPT, educators can tailor instructional strategies that support both technology adoption and the development of independent problem solving skills.
Constructivist Flipped Learning as a Recursive Knowledge Transformation Cycle Muhamm Azzam Almubarok; Ming Kir; Abena Boateng
Journal of Paddisengeng Technology Vol. 2 No. 3 (2026)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v2i3.290

Abstract

Background. Flipped learning has been widely implemented to reorganize learning activities across pre class, in class, and post class environments. However, existing models often emphasize instructional inversion and activity sequencing without adequately explaining how learners transform prior understanding into reconstructed knowledge. Purpose. This conceptual study develops the Constructivist Flipped Learning Cycle (CFLC), an integrative theoretical model explaining knowledge transformation through cognitive and social constructivist mechanisms. Method. The study employed a conceptual theory-building design comprising targeted literature identification, theoretical comparison, conceptual synthesis, framework development, and proposition formulation. Relevant perspectives on flipped learning, constructivism, cognitive conflict, social negotiation, knowledge reconstruction, and metacognitive reflection were integrated into a coherent explanatory model. Results. The CFLC comprises seven interconnected stages: prior knowledge activation, exploratory pre-class engagement, cognitive conflict, social negotiation, knowledge reconstruction, authentic application, and metacognitive reflection. These stages form a recursive cycle in which reconstructed knowledge becomes prior knowledge for subsequent learning. Novelty. The CFLC reframes flipped learning from a temporal-spatial inversion of instruction into a knowledge-transformation architecture and introduces a mechanism-based explanation linking cognitive conflict, social negotiation, and knowledge reconstruction across interconnected learning environments. Conclusion. The CFLC provides a theoretically grounded framework for explaining how meaningful conceptual transformation may occur in flipped learning and offers testable propositions for future empirical validation across diverse educational contexts.
Augmented Reality Media Based on Moral Ethics to Increase High School Students Learning Motivation Peri Sanria; Maurice Van Veen; Natalia Ramos; Sudirman Sudirman
Journal of Paddisengeng Technology Vol. 2 No. 3 (2026)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v2i3.291

Abstract

Background. The transformation of global digital technology is in line with the increasing cases of juvenile delinquency in East Java, while education still focuses on cognitive aspects and pays less attention to students’ moral aspects. Purpose. This research aims to develop Augmented Reality (AR)-based learning media that contains moral ethics and test its effectiveness on high school students’ learning motivation. Method. The study used the Lee & Owens Research and Development model approach, combining a quasi-experimental nonequivalent control group design, involving 41 high school students in East Java (Class A=20 as the experiment, Class B=21 as the control). Data were analyzed using N-Gain and Independent Sample t-test. Novelty. Unlike previous AR research, which generally focused on cognitive subjects (mathematics, science, and social studies), this study strengthens the integration by integrating AR into the affective domain, namely moral ethics education. Results. The product was declared highly feasible based on expert validation (average score 4.3/5.0). The experimental group showed a moderate increase in learning motivation (N-Gain=0.58) compared to the low control group (N-Gain=0.18), with a significant difference (t=4.12; p=0.001). Conclusion. AR media contains appropriate moral ethics and effectively increases high school students’ learning motivation, although generalization is still limited given the small sample scale.  
A VR-Based Multimodal System for Assessing Presentation Integrity and Character Formation in Higher Education Nurfaikah Nurfaikah; Suryadi Suryadi; Rachel O’Donovan; Claire Nolan
Journal of Paddisengeng Technology Vol. 2 No. 3 (2026)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v2i3.292

Abstract

Background. Artificial intelligence (AI) integration in online presentation assessment has expanded rapidly; however, existing facial emotion recognition systems in education remain largely focused on surveillance and behavioral monitoring, with limited validation against human judgment and insufficient attention to ethical and character-development dimensions. Purpose. This study aimed to develop and validate a virtual reality (VR)-based multimodal assessment framework for evaluating presentation integrity among higher education students. Method. A design science research approach was employed involving 64 students from two parallel classes (A1, n = 33; A2, n = 31) at a university in South Sulawesi, Indonesia. Data from expert validation, technical performance evaluation, NASA-TLX, System Usability Scale, and lecturer assessments were analyzed using content validity analysis with modified kappa, classification metrics, Bland-Altman agreement analysis, and descriptive statistics. Novelty. This study introduces a human-centered AI-VR assessment approach that integrates facial emotion recognition, gaze detection, and cognitive load measurement into a reflective Presentation Integrity Index. Unlike conventional AI-based monitoring systems that generate binary judgments, the proposed framework emphasizes ethical interpretation by combining affective, behavioral, and cognitive indicators to support formative character-based assessment. Results. The framework demonstrated satisfactory content validity (S-CVI/Ave = 0.83), although refinement of several indicators was required. Emotion and gaze modules achieved accuracy levels of 85.3% and 89.0%, respectively. The Presentation Integrity Index showed 93.8% agreement with lecturer assessments, moderate cognitive load (NASA-TLX = 46.7), and good usability (SUS = 76.4). Conclusion. The proposed AI-VR framework provides an ethical and reflective approach for character-based presentation assessment while requiring broader validation involving multiple evaluators and diverse educational contexts.
Integration of Student-Centered vs Teacher Centered Approaches and Digital Media in Character Education Learning for Prospective Teachers in Punjab India Parwinder Kaur; Nirmala M; Natalia Ramos
Journal of Paddisengeng Technology Vol. 2 No. 3 (2026)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v2i3.298

Abstract

Background. The growing global and national attention to character education, reinforced by India’s National Education Policy (NEP) 2020 call for learner-centered pedagogy, has outpaced empirical evidence on which teaching approaches are most effective in cultivating character among prospective teachers. Purpose. This study examined the comparative effectiveness of digitally supported student-centered and teacher-centered instructional approaches on character education outcomes among prospective teachers in Punjab, India. Method. A quasi-experimental, mixed-methods design was employed involving 123 prospective teachers across four intact classes, assigned to student-centered (n = 63) and teacher-centered (n = 60) conditions. ANCOVA and MANCOVA tested effects on character formation across three dimensions-moral knowing, moral feeling, and moral action-complemented by semi-structured interviews. Novelty. Unlike prior studies reporting composite character scores, this study disaggregated character formation into theoretically distinct dimensions and explicitly engaged an unresolved methodological debate regarding cognitive-versus-behavioral measurement bias in character education research. Results.The student-centered group showed significantly greater gains in overall character outcomes, F(1, 120) = 88.02, p < .001, partial n² = .421, with the strongest effect observed for moral knowing (n² = .402). Conclusion. Digitally supported student-centered instruction shows promise for character formation in teacher education, though findings warrant cautious interpretation pending randomized, longitudinal replication with behavioral outcome measures.
AI Use and Learning Outcomes Among Undergraduate Students: The Mediating Role of Learning Motivation, Locus of Control, and Learning Preferences Achmad Nashrul Waahib; Aminah Aminah; Abdul Sahib; M Syahputra
Journal of Paddisengeng Technology Vol. 2 No. 3 (2026)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v2i3.300

Abstract

Background. The growing use of artificial intelligence (AI) in higher education has created new opportunities for personalized learning, although its contribution to student achievement remains theoretically and empirically contested. Purpose. This study examined the direct and indirect effects of AI use on conceptual understanding and problem-solving ability through learning motivation, locus of control, and learning preferences. Method. A quantitative explanatory design was employed with 88 pre-service teachers enrolled in an Instructional Media course at a teacher education institution in Central Java, Indonesia. Data were collected using validated questionnaires and cognitive assessments. Preliminary analyses were conducted using SPSS, while the measurement and structural models were evaluated through PLS-SEM with 5,000 bootstrap subsamples. Novelty. This study simultaneously tested three psychological and learning-related mediators within a single structural model, thereby extending previous research that primarily examined the direct relationship between AI use and academic performance. Results. AI use significantly predicted learning motivation and locus of control but did not significantly influence learning preferences. Learning motivation significantly predicted learning outcomes and mediated the relationship between AI use and learning outcomes. In contrast, locus of control and learning preferences showed no significant mediating effects. The direct effect of AI use on learning outcomes was also nonsignificant. Conclusion. AI contributes to student learning primarily by strengthening learning motivation rather than through direct technological exposure. Effective AI integration should therefore emphasize reflective, autonomous, and cognitively engaging learning activities.

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