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Journal of Innovative Technologies in Learning and Education
Published by Universitas Citra Bangsa
ISSN : -     EISSN : 30641039     DOI : https://doi.org/10.37792/jitle.v3i1
Core Subject : Science, Education, Social,
Computer Science & IT Education Social Sciences Other
Journal of Innovative Technologies in Learning and Education (J-ITLE) is a peer-reviewed international journal that publishes cutting-edge research on the integration of innovative technologies in educational settings. The journal covers a wide range of topics, including but not limited to digital learning tools, educational software development, virtual and augmented reality in education, adaptive learning systems, and the impact of artificial intelligence on pedagogy. J-ITLE aims to bridge the gap between theory and practice by showcasing studies that provide actionable insights for educators, researchers, and technologists. The journal welcomes original research articles, review papers, case studies, and technical reports that contribute to the advancement of educational technology and its application in both formal and informal learning environments. Targeting an international audience, J-ITLE serves as a platform for the dissemination of scholarly work that addresses the evolving challenges and opportunities in education brought about by technological innovation.
Arjuna Subject : Umum - Umum
Articles 32 Documents
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DEVELOPMENT OF COMIC-BASED TEACHING MATERIALS TO IMPROVE STUDENT LEARNING OUTCOMES ON WATER CYCLE MATERIALS IN CLASS VC SDN MAULAFA KUPANG CITY Bernadino Ceunfin; Yulsy Marselina Nitte; Heryon Bernard Mbuik
Journal of Innovative Technologies in Learning and Education Vol. 2 No. 2 (2025): Journal of Innovative Technologies in Learning and Education - September 2025
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/jitle.v2i2.1874

Abstract

This research aims to develop comic-based teaching materials that are feasible, attractive, practical, and effective to improve student learning outcomes on water cycle materials in the VC class of SDN Maulafa Kupang City. The research method uses a Research and Development (R&D) approach with the ADDIE model which includes needs analysis, design, development through expert validation, trial implementation, and evaluation. The research subjects consisted of 29 students, with instruments in the form of expert validation questionnaires, teacher and student response questionnaires, and learning outcome tests. The results of the study showed that the comic teaching materials received very decent assessments from material experts (98%), linguists (90%), media experts (97%), teacher responses (97%), and student responses (93%). Student learning outcomes also increased significantly, with an average pretest score of 79% rising to 88% on the posttest (very good category). The gain test value of 0.84 (>0.7) indicates an increase in the high category. Data analysis using the t-test with the help of SPSS version 23 shows that the data is normally distributed so that it can be analyzed parametrically. The test results showed a Sig. (2-tailed) value < 0.05, which means Ho was rejected and Ha was accepted. Thus, the use of comic-based teaching materials has a significant effect on improving student learning outcomes. This study concludes that comic-based teaching materials are effectively used and can be an innovative alternative in learning science science in elementary schools, especially in water cycle materials.
IMPROVEMENT OF STUDENT ACHIEVEMENT THROUGH PROBLEM-BASED LEARNING SYSTEM WITH A DIFFERENTIATED APPROACH: OBJECT-ORIENTED PROGRAMMING SUBJECT Wahyudin Wahyudin; Dwi Fitria Al Husaeni; R. Rasim; Khyrina Airin Fariza Abu Samah; Shah Nazir
Journal of Innovative Technologies in Learning and Education Vol. 3 No. 1 (2026): Journal of Innovative Technologies in Learning and Education - January 2026
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/jitle.v3i1.1884

Abstract

The quality of education can determine a country's success in facing the industrial revolution 4.0. Learning innovation towards a new paradigm is expected to be able to solve problems entering the era of Industrial Revolution 4.0. Therefore, this research creates a learning innovation that aims to improve student learning outcomes, especially in object-oriented programming material using a problem-based learning system with a differentiated learning approach. Quantitative research methods with a quasi-experimental design in the form of a non-equivalent pretest-posttest control group design were used in this research. The research subjects were 71 students in class X vocational school majoring in software engineering at SMKN 1 Cimahi, Indonesia. This research focuses on improving learning outcomes for object-oriented programming. The research results show that the abilities of students who use a problem-based learning system with a differentiated approach are more even and higher. Using a differentiated learning approach in problem-based learning is more effective in improving student learning outcomes in object-oriented programming material, compared to just using a problem-based learning model. It is hoped that this research can become a reference to improve the quality of learning to prepare students to face the era of industrial revolution 4.0.
THE EFFECTIVENESS OF USING AUDIO-VISUAL MEDIA BASED ON POLYA'S PROBLEM-SOLVING THEORY IN ELEMENTARY SCHOOL STUDENTS' MATHEMATICS LEARNING (CASE STUDY AT THE UPTD SDN MAULAFA) Khatrin Taku Neno
Journal of Innovative Technologies in Learning and Education Vol. 3 No. 1 (2026): Journal of Innovative Technologies in Learning and Education - January 2026
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/jitle.v3i1.1919

Abstract

This study aimed to examine the effectiveness of using audio-visual media based on Polya’s Problem-Solving Theory in improving elementary school students’ mathematical problem-solving abilities. This research employed a quantitative approach with a quasi-experimental design using a pretest–posttest control group design. The subjects of the study were elementary school students at UPTD SDN Maulafa, who were divided into an experimental group and a control group. The experimental group was taught using audio-visual media integrated with Polya’s problem-solving stages, while the control group received conventional instruction. Data were collected through problem-solving tests and classroom observations. The data were analyzed using descriptive statistics and inferential statistics, including normality tests, homogeneity tests, and independent samples t-tests. The results showed that students in the experimental group achieved higher posttest scores and greater improvement in mathematical problem-solving abilities compared to students in the control group. Statistical analysis indicated that the data were normally distributed and homogeneous, and the t-test results revealed a significant difference between the two groups. Observation results also showed that students in the experimental group demonstrated higher levels of engagement, participation, and motivation during the learning process. Based on these findings, it can be concluded that the use of audio-visual media based on Polya’s Problem-Solving Theory is effective in improving elementary school students’ mathematical problem-solving abilities and learning activities. This instructional approach can be considered an effective and innovative alternative for enhancing the quality of mathematics learning in elementary schools.
The AI Co-Author: Investigating the Impact of Generative AI on Creative Short Story Writing Skills on the Students of English Education Study Program Christmas Prasetia Ate; Dortean Amelia Jois Jaha
Journal of Innovative Technologies in Learning and Education Vol. 3 No. 1 (2026): Journal of Innovative Technologies in Learning and Education - January 2026
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/jitle.v3i1.1921

Abstract

This qualitative case study investigates the impact of Generative AI (GenAI) as a "co-author" on the creative short story writing skills of 19 fourth-semester students in the English Education Study Program at Citra Bangsa University. Amidst the growing debate on AI in education, this study explores how EFL learners utilize tools like ChatGPT to overcome challenges such as blank page syndrome and limited lexical resources. Data were collected through semi-structured interviews, reflective journals, and analysis of digital artifacts (chat logs and story drafts) following a six-week creative writing workshop. The findings reveal that GenAI significantly reduced writing anxiety by serving as an ideation partner and expanded students' descriptive vocabulary through context-specific synonyms. However, the study also highlights a complex negotiation of authorship, where students acted as "creative directors," curating AI outputs to ensure cultural relevance and narrative voice. The research concludes that integrating GenAI requires a pedagogical shift from product-oriented to process-oriented assessment, emphasizing "prompt engineering" as a critical new literacy for future English teachers
ENGLISH-MAJOR STUDENTS’ PERCEPTIONS OF AI-ASSISTED IELTS WRITING TASK 2 PRACTICE IN HIGHER EDUCATION: A QUALITATIVE STUDY AT THANH DO UNIVERSITY, VIETNAM Nguyet Pham Thi
Journal of Innovative Technologies in Learning and Education Vol. 3 No. 2 (2026): Journal of Innovative Technologies in Learning and Education - September 2026
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/jeswmn23

Abstract

This study investigated English-major students’ perceptions of AI-assisted tools in IELTS Writing Task 2 practice at Thanh Do University, Vietnam. The study aimed to explore how students perceived the usefulness and challenges of using AI-assisted writing technologies during IELTS-oriented writing activities. A qualitative research design was employed, involving semi-structured interviews with 15 third-year English-major students enrolled in the Integrated English 2 course during the second semester of the 2025 academic year. The participants had experience using AI-assisted tools such as ChatGPT, Grammarly, and Gemini to support IELTS Writing Task 2 practice. Interview data were analyzed using thematic analysis. The findings revealed that students generally perceived AI-assisted writing tools positively due to their usefulness in idea generation, essay organization, grammar correction, vocabulary enhancement, and self-study support. Participants also believed that AI technologies improved writing confidence and encouraged learner autonomy. However, concerns regarding overreliance on AI-generated content, reduced independent thinking, and the reliability of AI-generated feedback were also identified. The study highlights the potential of AI-assisted writing technologies as supplementary learning resources in IELTS-oriented writing instruction while emphasizing the importance of responsible and balanced AI integration in higher education contexts.
Governing the Algorithmic Classroom: A Comparative Policy Analysis of National AI Strategies in Public Education Systems Debopom Ghosh
Journal of Innovative Technologies in Learning and Education Vol. 3 No. 2 (2026): Journal of Innovative Technologies in Learning and Education - September 2026
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/8s7zjb81

Abstract

There is a rapid adoption of artificial intelligence (AI) within the public education system, which represents a major shift in state governance, regulatory oversight, and public administration. The comparative policy analysis examines the structural, regulatory, and pedagogical aspects of national AI strategies across multiple geopolitical archetypes, including rights-based restrictive regimes (the European Union), decentralized market-driven systems (the United States), state-centric optimization regimes (China and Singapore), emerging democratic regimes (India), and sovereign digital development regimes (Bangladesh and Sub-Saharan Africa). Utilizing a hybrid comparative approach grounded in Most Different Systems Design (MDSD), this study systematically measures and indexes the “rhetoric-reality gap” in national policies and juxtaposes the prevailing technocratic Optimization Paradigm and the idealistic Restructuring Paradigm. The paper’s empirical evaluation of high-stakes algorithmic failures, including the 2020 Ofqual examination scandal in the UK, and its focus on the 2026 OECD Digital Education Outlook’s key findings on the “Performance-Learning Gap” should be taken as a wake-up call to the systemic loopholes of “metacognitive laziness” and corporate control capture that endanger public education. Finally, we operationalize the Sustainable Public Innovation Ecosystem (SPIE) model as a dynamic governance blueprint, providing cost, sequenced policy recommendations and a novel, non-algorithmic alternative assessment architecture intended to preserve pedagogical agency and democratic equity in the algorithmic age.
Federated Explainable Multi-Agent Governance Framework for Adaptive Personalized Learning Equity in Higher Education KAMAL SINGH KUNWAR
Journal of Innovative Technologies in Learning and Education Vol. 3 No. 2 (2026): Journal of Innovative Technologies in Learning and Education - September 2026
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/rxtajs29

Abstract

The rapid deployment of artificial intelligence (AI) in higher education raises questions of equity, transparency, accountability, privacy, and governance in adaptive personalized learning. While AI-enabled personalization can increase educational responsiveness, top-down personalized learning architectures may reinforce inequality through decentralized institutional data representation, esoteric decision-making, and insufficient stakeholder agency. Prior work has advanced federated learning, multi-agent systems, explainable AI (XAI), and algorithmic fairness, yet such components have not been fully integrated into a governance architecture for equitable higher education. This paper proposes an adaptive personalized learning federated explainable multi-agent governance architecture for equitable higher education. A theory-building research methodology leveraging critical realism and abductive inference combines concepts in distributed machine learning, multi-agent coordination, XAI, educational equity, and AI governance. The architecture consists of four interacting layers: federated learning for distributed institutional data; multi-agent governance comprising student, instructor, policy, and optimizer agents; explainability for decision traceability and interpretation; and equity evaluation to inform ongoing bias mitigation. Theoretical triangulation, construct-to-function mapping, cross-domain consistency testing, and boundary-condition analysis serve as the analytical validation process. Privacy, distributed governance, XAI, and equity are systemically positioned as mutually constraining properties. The architecture can inform design principles and empirical evaluation for agency-aware, privacy-preserving, equitable institutional AI governance.
BETWEEN ASSISTANCE AND CHEATING: ENGLISH LECTURERS’ EVALUATION OF AI-SUPPORTED STUDENT WRITING Ninh Nguyen Tuan; Nguyet Pham Thi
Journal of Innovative Technologies in Learning and Education Vol. 3 No. 2 (2026): Journal of Innovative Technologies in Learning and Education - September 2026
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/1me3xf95

Abstract

The rapid emergence of generative artificial intelligence (AI) tools such as ChatGPT has transformed writing practices in higher education and raised important questions regarding authorship, assessment, and academic integrity. Although previous studies have explored the benefits and challenges of AI-assisted writing, limited research has examined how lecturers evaluate student writing that involves AI support. This study investigates how English lecturers conceptualise the boundary between acceptable AI-assisted writing and academic misconduct and explores the factors influencing their assessment and grading decisions in Vietnamese higher education. A qualitative design was employed. Semi-structured interviews were conducted with twenty English lecturers from three universities in Hanoi. The interviews were analysed using reflexive thematic analysis, with coding and theme development cross-checked by two researchers. The findings indicate that lecturers do not view AI use in student writing as inherently unethical. Rather, they understand AI use along a continuum, distinguishing between AI as a learning support and AI as a substitute for students’ intellectual effort and authorship. Assessment decisions were influenced by perceptions of student agency, transparency in AI use, evidence of learning, ethical considerations, institutional expectations, and professional experience. Rather than relying primarily on AI-detection tools, lecturers emphasised students’ ability to explain, justify, and reflect on their writing processes. The study concludes that assessing AI-supported writing is a pedagogical and interpretative practice rather than a purely technical or rule-based process. The findings highlight the need for context-sensitive assessment frameworks, clearer institutional guidance, and professional development to support lecturers in navigating AI-related assessment challenges.
EFFECT OF POWERPOINT PRESENTATION ON SENIOR SECONDARY STUDENTS’ ACHIEVEMENT IN CIVIC EDUCATION Abiola Olori; Adeola Ogunsanya
Journal of Innovative Technologies in Learning and Education Vol. 3 No. 2 (2026): Journal of Innovative Technologies in Learning and Education - September 2026
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/4nhj2e34

Abstract

This study examined the effect of PowerPoint Presentation (PPP) on the academic achievement of Senior Secondary (SSII) students in civic education within the Ogun Central Senatorial District, Nigeria. Guided by one research question and two null hypotheses, the study employed a pre-test, post-test, control group quasi-experimental design. A sample of 140 students was selected, and achievement was measured using the validated Civic Education Achievement Test (CEAT), which yielded a reliability index of 0.85. The experimental group received instruction via multimedia PowerPoint presentations, while the control group was taught using conventional "chalk-and-talk" method. Findings of hypothesis one show significant effect of PPP on students’ achievement (F (1,137) =214.472, P<0.05). Since p is less than 0.05, it shows significant difference in the post-test mean achievement scores of students taught with PPP and those taught with chalk and talk method.  Findings of hypothesis two revealed no significant interaction effect of treatment and gender on students’ achievement (F (1, 137) =.521, P>0.05). This shows there is no significant interaction effect of treatment and gender on the post -test mean achievement scores of students. Since p is greater than 0.05, this implies that there is no significant difference in the mean achievement scores of male and female students in the experimental group. Based on these findings, it is recommended that the Ministry of Education and school stakeholders prioritize teacher training workshops on the integration of multimedia technologies in the civic education curriculum to enhance pedagogical outcomes
AI-ENABLED INNOVATION AND ENTREPRENEURSHIP COURSES IN HIGHER EDUCATION: RESEARCH HOTSPOTS, EVOLUTIONARY TRAJECTORIES, AND EMERGING FRONTIERS YUNDONG WU
Journal of Innovative Technologies in Learning and Education Vol. 3 No. 2 (2026): Journal of Innovative Technologies in Learning and Education - September 2026
Publisher : Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/erhfvg60

Abstract

Artificial intelligence (AI), generative AI (GenAI), large language models, and intelligent agents are transforming university innovation and entrepreneurship education. These tools support opportunity recognition, market analysis, prototyping, pitch preparation, and feedback, yet raise critical concerns regarding evidence, authorship, data governance, and academic integrity. Although research in both fields has expanded, their intersection remains fragmented.  This article presents a CiteSpace-informed bibliometric synthesis examining AI-enabled innovation and entrepreneurship courses. A traceable core corpus of 48 international and policy sources was analyzed across key domains, mapping keyword co-occurrences, conceptual clusters, temporal trajectories, and emerging frontiers.  Five major research hotspots were identified: AI as an innovation collaborator; integration of AI literacy with entrepreneurial competence; authentic project-based learning; assessment and academic integrity; and ethical and governance boundaries. The field has evolved across four stages: tool introduction, pedagogical integration, curriculum reconstruction, and governance deepening. Emerging frontiers highlight course-specific intelligent agents, human-AI-teacher-enterprise collaboration, evidence-centered assessment, authentic user validation, and institutional responsible-use policies.  The article outlines a curriculum reform framework structured around problem chains, intelligent-agent scaffolding, learning-evidence portfolios, and risk-based governance. As an exploratory synthesis of a core corpus, findings offer a conceptual blueprint rather than an absolute measure of overall publication volume.

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