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Journal of Learning Innovation and Educational Technology
Published by PT Suria Academic Press
ISSN : -     EISSN : 31643302     DOI : https://doi.org/10.67467/jliet.v1i1
Core Subject :
The Journal of Learning Innovation and Educational Technology (JLIET) aims to advance research and practice in learning innovation and educational technology by publishing rigorous empirical, theoretical, conceptual, and evidence-based studies. The journal covers innovative pedagogy, digital and technology-enhanced learning, artificial intelligence and emerging technologies, learning analytics, digital learning media, instructional design, educational assessment, digital literacy, STEM/STEAM education, and technology-driven educational transformation across diverse educational contexts and levels.
Arjuna Subject : -
Articles 5 Documents
 1 
Artificial Intelligence-Supported Personalized Learning for Enhancing Students' Critical Thinking Skills: A Systematic Literature Review Muharleni; Neni Sriwahyuni
Journal of Learning Innovation and Educational Technology Vol. 1 No. 1 (2026): June 2026
Publisher : Suria Academic Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67467/jliet.v1i1.109

Abstract

The rapid advancement of Artificial Intelligence (AI) has transformed education toward more personalized, adaptive, and learner-centered approaches. Although numerous studies have reported the benefits of AI in improving learning quality, comprehensive evidence explaining the relationship between AI, personalized learning, and students' critical thinking skills remains limited. This study aims to examine the implementation of AI in personalized learning, identify its opportunities and challenges, and propose a conceptual model explaining how AI contributes to the development of students' critical thinking skills. This research employed a Systematic Literature Review (SLR) following the PRISMA 2020 guidelines. Literature was retrieved from five international databases, including Scopus, Web of Science, ERIC, IEEE Xplore, and Google Scholar. Following the identification, screening, and eligibility processes, 42 articles published between 2021 and 2025 were selected and analyzed using a thematic synthesis approach. The findings indicate that AI functions as an enabling technology supporting personalized learning through adaptive learning systems, learning analytics, intelligent tutoring systems, and Generative Artificial Intelligence. The contribution of AI to students' critical thinking is not direct but is mediated by enhanced student engagement, self-regulated learning, and metacognitive awareness. However, the implementation of AI also faces significant challenges related to teachers' pedagogical readiness, AI literacy, digital infrastructure, data privacy, algorithmic bias, and ethical governance. This study proposes a conceptual model integrating Artificial Intelligence, personalized learning, student engagement, self-regulated learning, and critical thinking skills, providing a theoretical contribution to the field of Artificial Intelligence in Education (AIEd) while offering practical implications for educators, policymakers, and future research.
Development and Evaluation of CTL-Based Digital Learning Materialsfor Pancasila Education: Integrating Islamic Values in ElementarySchools Raisya Andre Pandoe; Arwin
Journal of Learning Innovation and Educational Technology Vol. 1 No. 1 (2026): June 2026
Publisher : Suria Academic Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67467/jliet.v1i1.112

Abstract

Learning Pancasila Education in elementary schools remains insufficiently contextual and lacks the utilization of digital media; therefore, it is necessary to develop CTL-based teaching materials integrated with Islamic values to foster students’ national and religious character. This study aims to develop and examine the feasibility of Digital Teaching Materials for Pancasila Education based on the Contextual Teaching and Learning (CTL) approach integrated with Islamic values for Grade IV students at Integrated Islamic Elementary Schools (SDIT). The research employed a Research and Development (R&D) method using the ADDIE model, which consists of five stages: Analysis, Design, Development, Implementation, and Evaluation. The research subjects included teachers and Grade IV students from four SDIT in Padang City: SDIT Arafah, SD Islam Nibros, SDIT Cendekia Andalas, and SDIT Permata. Research instruments consisted of validation sheets for material experts, media experts, and language experts, as well as practicality questionnaires for teachers and students, and learning outcome tests (pretest–posttest). The results showed that the developed product was categorized as highly valid with an average score of 93%, highly practical with a score of 93.5%, and effective in improving students’ learning outcomes with an N-Gain score of 0.75 (high category). Learning using CTL-based digital teaching materials was proven to enhance student engagement, understanding, and character formation, particularly in instilling the values of unity, ukhuwah (brotherhood), ta’awun (mutual help), and amanah (responsibility). Thus, the CTL-Based Digital Teaching Materials for Pancasila Education Integrated with Islamic Values are declared valid, practical, and effective as an innovative instructional resource for Pancasila Education in integrated Islamic elementary schools. This product is expected to serve as a reference for developing contextual and character-based digital learning media in the era of the Kurikulum Merdeka.
Immersive Learning Technologies in Education: A Systematic Review of Augmented Reality and Virtual Reality for Conceptual Understanding Neni Sriwahyuni; Muharleni
Journal of Learning Innovation and Educational Technology Vol. 1 No. 1 (2026): June 2026
Publisher : Suria Academic Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67467/jliet.v1i1.116

Abstract

The growing adoption of Augmented Reality (AR) and Virtual Reality (VR) has transformed educational technology by providing immersive learning environments that promote interactive and meaningful learning experiences. Despite increasing interest in these technologies, previous studies have reported inconsistent findings regarding their effectiveness in enhancing students' conceptual understanding, highlighting the need for a comprehensive synthesis of current evidence. This study aims to systematically review empirical research on the educational applications of AR and VR, with particular emphasis on their impact on conceptual understanding, supporting factors, implementation challenges, and pedagogical implications. A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines. Scientific articles published between 2015 and 2025 were retrieved from Scopus, Web of Science, ScienceDirect, SpringerLink, ERIC, and Google Scholar using predefined inclusion and exclusion criteria. Of the 436 studies initially identified, 36 peer-reviewed articles met the eligibility criteria and were included in the thematic synthesis. The findings indicate that AR and VR consistently improve conceptual visualization, learner engagement, motivation, and experiential learning. However, their effectiveness in promoting conceptual understanding remains inconsistent and is strongly influenced by instructional design quality, pedagogical integration, cognitive load management, teacher competence, technological infrastructure, and learner readiness. The review further reveals that immersive technologies produce more meaningful learning outcomes when integrated with active learning approaches, such as inquiry-based, problem-based, and project-based learning, rather than functioning solely as visualization tools. This study proposes a conceptual framework that positions instructional design, pedagogical strategies, and implementation readiness as key determinants of successful immersive learning. These findings contribute to the advancement of educational technology literature and provide practical guidance for educators, instructional designers, and policymakers in developing pedagogically meaningful and sustainable AR- and VR-supported learning environments.
The Effectiveness of ChatGPT-Assisted Project-Based Learning in Enhancing Critical Thinking Skills among Pre-Service Teachers Andri Candra
Journal of Learning Innovation and Educational Technology Vol. 1 No. 1 (2026): June 2026
Publisher : Suria Academic Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67467/jliet.v1i1.221

Abstract

The integration of Generative Artificial Intelligence (GenAI) into higher education has created new opportunities to enhance student-centered learning and foster higher-order thinking skills. However, empirical evidence regarding the effectiveness of ChatGPT-assisted Project-Based Learning (PBL) in teacher education remains limited. This study investigated the effectiveness of ChatGPT-assisted PBL in improving the critical thinking skills of pre-service teachers. A quasi-experimental pretest–posttest control group design was employed involving 68 pre-service teachers enrolled in an Educational Technology course. Participants were assigned to an experimental group (n = 34), which received ChatGPT-assisted PBL, and a control group (n = 34), which received conventional PBL. Critical thinking was assessed using a validated performance-based instrument based on Facione’s six dimensions. Data were analyzed using descriptive statistics, Shapiro–Wilk and Levene’s tests, paired and independent samples t-tests, normalized gain (N-Gain), and Cohen’s d. The findings revealed that the experimental group achieved significantly higher critical thinking scores than the control group (t = 7.36, p < 0.001), with a high N-Gain (0.71) compared to a moderate gain (0.43) in the control group. The intervention also demonstrated a large practical effect (Cohen’s d = 0.97), particularly improving students’ analytical reasoning and explanatory abilities. These findings suggest that integrating ChatGPT into Project-Based Learning effectively promotes critical thinking by supporting inquiry, evidence-based reasoning, and reflective learning. The study highlights the potential of Generative AI as a pedagogical partner in preparing future teachers for AI-enhanced educational environments.
Predicting Student Learning Outcomes Using Learning Analytics Dashboards in Hybrid Higher Education: A Systematic Literature Review Nurhaliza
Journal of Learning Innovation and Educational Technology Vol. 1 No. 1 (2026): June 2026
Publisher : Suria Academic Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67467/jliet.v1i1.222

Abstract

The rapid adoption of hybrid learning in higher education has generated extensive educational data, creating opportunities to enhance teaching and learning through Learning Analytics Dashboards (LADs). By integrating data visualization and predictive analytics, LADs enable institutions to monitor student engagement, identify academically at-risk students, and support timely instructional interventions. However, existing research remains fragmented across learning analytics, machine learning, and dashboard design, limiting a comprehensive understanding of their role in predicting student learning outcomes. This study aims to systematically synthesize current evidence on the implementation of Learning Analytics Dashboards in hybrid higher education. A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines. Relevant studies published between 2020 and 2026 were identified from Scopus, Web of Science, ScienceDirect, SpringerLink, and IEEE Xplore using predefined inclusion and exclusion criteria. The selected studies were analyzed through qualitative thematic synthesis to examine publication trends, predictive algorithms, learning indicators, dashboard functionalities, educational impacts, implementation challenges, and future research directions. The findings indicate that Learning Analytics Dashboards have evolved into strategic decision-support systems by integrating multidimensional learning data with machine learning techniques to improve early identification of at-risk students and support evidence-based instructional decisions. Nevertheless, challenges related to data quality, interoperability, ethical governance, explainability, and institutional readiness remain significant. This review provides an integrated perspective and practical recommendations for developing transparent, intelligent, and learner-centered predictive analytics systems in higher education.

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