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International Transactions on Education Technology (ITEE)
Published by Pandawan Sejahtera Indonesia
ISSN : 29636078     EISSN : 29631947     DOI : https://doi.org/10.33050/itee
Core Subject : Social, Engineering,
Control & Systems Engineering Social Sciences
Computer Science/informatics, Circular Digital Economy, Computer engineering/computer systems, Software Engineering, Information Technology, Information Systems, Cyber Security, Data Science, Artificial Intelligence
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 58 Documents
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Enhancing Student Engagement with AI-Driven Personalized Learning Systems Zaharuddin; Chen Yu; Yao, Goh
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.662

Abstract

This paper explores the impact of AI-driven personalized learning systems on enhancing student engagement in educational settings. With the increasing integration of artificial intelligence (AI) in various sectors, education is also experiencing a shift towards more adaptive and personalized learning environments. The study investigates how personalized learning paths, powered by AI algorithms, can address diverse learning needs and promote greater involvement from students. Through a comprehensive analysis of engagement metrics, pre-and post-implementation comparisons, and surveys from both students and educators, this research identifies key factors that contribute to improved student motivation, interaction, and academic performance. The findings suggest that AI-driven systems not only provide tailored learning experiences but also foster a deeper connection between students and their learning content. The paper concludes with recommendations for future research and practical applications in educational institutions to further optimize the use of AI for enhancing student engagement.
A Model-Driven Approach to Developing Scalable Educational Software for Adaptive Learning Environments Sutarman, Asep; Williams, Jack; Wilson, Daniel; Ismail, Farid Bin
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.663

Abstract

This research presents a model-driven approach to the development of scalable educational software tailored to adaptive learning environments. With the increasing demand for personalized education, adaptive learning systems play a crucial role in meeting diverse student needs by adjusting instructional content dynamically. This paper proposes a software engineering framework that integrates model-driven development (MDD) techniques with scalability principles, allowing for the efficient design and implementation of educational applications that can handle varying workloads and user demands. The framework emphasizes modular architecture, reusability, and flexibility to ensure that software can evolve with emerging educational requirements. Key components include the design of a learning content management system (LCMS) and the application of adaptive algorithms to personalize learning pathways. Additionally, this study explores the integration of cloud technologies to enhance the scalability and performance of educational platforms. A prototype system was developed and tested in a controlled environment, showing significant improvements in scalability, system performance, and student engagement compared to traditional static e-learning platforms. The results indicate that the model-driven approach not only improves software development efficiency but also offers a robust solution for creating adaptive educational systems that can scale to meet the growing needs of learners and institutions. This research contributes to the field of educational software development by providing a systematic methodology for building scalable and adaptive learning environments using advanced software engineering techniques.
Exploring Digital Circular Economy Principles in Educational Institutions Martinez, Santiago; Rodríguez, Juan Carlos; Lestari, Sri
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.664

Abstract

The integration of digital circular economy (DCE) principles within educational institutions has gained increasing attention in recent years, as institutions strive to adopt sustainable and resource-efficient models. This paper explores the background of how DCE can be applied to enhance sustainability in the educational sector, focusing on reducing waste, optimizing resources, and fostering circular economic practices. The objective of this research is to analyze the effectiveness of DCE implementation in improving institutional sustainability and educational outcomes. The study employs a mixed-method approach, combining qualitative interviews with educational professionals and quantitative surveys to gather data on the adoption and impact of DCE principles. Results indicate that institutions which have integrated DCE strategies, such as digital resource sharing and the reuse of educational materials, have seen significant improvements in both resource management and educational performance. The findings suggest that the application of digital circular economy models contributes to reducing costs and enhancing the learning environment by promoting efficiency and sustainability. The conclusion highlights the potential of DCE as a transformative approach in the educational context, recommending further research on scaling these practices and their long-term impact on educational institutions.
Cybersecurity in Learning Systems: Data protection and privacy in educational information systems and digital learning environments Watini, Sri; Davies, George; Andersen, Nicole
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.665

Abstract

This research addresses the growing cybersecurity challenges within educational information systems and digital learning platforms, focusing on the protection of sensitive data and user privacy. The objective is to identify prevalent cybersecurity threats in these environments and propose effective solutions to mitigate them. A mixed-method approach is employed, combining a comprehensive literature review with a survey distributed to IT professionals and educators working in digital learning environments. The findings highlight the increasing sophistication of cyberattacks, including data breaches, phishing, and malware, which compromise the integrity and security of educational data. Moreover, the study reveals a gap in the implementation of robust cybersecurity policies, especially in underfunded educational institutions. The proposed solutions emphasize the integration of advanced encryption methods, multifactor authentication, and regular cybersecurity training for all stakeholders. In conclusion, this research underscores the importance of developing a resilient cybersecurity framework tailored to educational systems, ensuring the protection of both institutional data and the privacy of users, thereby enhancing trust and security in digital learning environments.
The Impact of AI on Personalized Learning and Educational Analytics Silva, Gabriel; Godwin, Gelard; Jayanagara, Oscar
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.669

Abstract

The rapid advancement of artificial intelligence (AI) has revolutionized personalized learning and educational analytics, presenting new opportunities and challenges for adaptive education. This paper explores the impact of AI-driven technologies in creating personalized learning environments by examining how adaptive algorithms and data analytics shape educational experiences. The primary objective of this study is to assess the effectiveness of AI in enhancing learner engagement and outcomes through tailored instructional methods. Utilizing a mixed-method approach, this research gathers quantitative data from learning management systems to analyze engagement metrics, while qualitative insights are derived from interviews with educators and students. The findings indicate that AI-driven personalized learning significantly improves both student motivation and academic performance by adapting content to individual learning needs. Moreover, educational analytics enabled by AI offer educators critical insights into student progress, enabling proactive intervention and support. However, the study also highlights concerns regarding data privacy and the potential over-reliance on AI technologies in educational settings. These findings suggest that while AI holds transformative potential, a balanced approach is necessary to integrate technology with traditional teaching methods to ensure optimal educational outcomes. The study concludes that AI can serve as a powerful tool in enhancing personalized learning and educational analytics, provided that ethical considerations and data security are prioritized.
Management of Educational Institutions through Information Systems for Enhanced Efficiency and Decision-Making Sunarjo, Richard Andre; Chakim, Mochamad Heru Riza; Maulana, Sabda; Fitriani, Gaby
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.670

Abstract

This paper explores the application of information systems in the management of educational institutions, aiming to enhance operational efficiency and support informed decision-making processes. Educational institutions face growing demands for streamlined administration and resource optimization, which form the background of this study. The objective is to assess the effectiveness of implementing information systems tailored to manage complex educational processes and institutional needs. A mixed-method approach was employed, combining quantitative analysis of system usage data and qualitative feedback from administrators and educators within various institutions. This method allowed for a comprehensive understanding of the impacts and challenges associated with integrating these technologies. Results reveal that institutions using information systems report significant improvements in administrative efficiency, resource management, and data-driven decision-making capabilities, as well as enhanced stakeholder satisfaction. Furthermore, the findings suggest that well-designed information systems reduce redundant administrative tasks, enabling staff to allocate more time toward core educational activities. In conclusion, the adoption of tailored information systems for educational institutions not only enhances management efficiency but also supports a culture of informed decision-making, paving the way for more responsive and adaptive educational environments. These insights underscore the value of integrating technology into educational administration, offering a strategic path toward more effective institutional management.
Exploring Sustainable Strategies for Education through the Adoption of Digital Circular Economy Principles Meria, Lista; Bangun, Cicilia Sriliasta; Edwards, John
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.675

Abstract

This study investigates sustainable strategies in education by examining the adoption of digital circular economy principles, aiming to address the growing need for resource efficiency within educational systems. As educational institutions face pressures to reduce environmental impact and enhance sustainability, integrating circular economy practices offers promising pathways. The objective of this research is to explore how digital tools and circular principles can be effectively applied to minimize waste and promote resource regeneration in academic settings. A mixed-method approach was employed, combining qualitative case studies and quantitative surveys across several institutions actively implementing circular economy initiatives. Data was collected from educators, administrators, and students to assess the impact of digital circular models on resource management, cost-efficiency, and environmental awareness. Findings indicate that digital circular economy strategies, including digital resource sharing platforms and waste reduction initiatives, significantly enhance both operational sustainability and educational outcomes by fostering a culture of environmental responsibility. Furthermore, the adoption of these strategies has led to measurable reductions in material waste and increased awareness of sustainable practices among students and staff. The research concludes that digital circular economy principles are not only viable but also essential for creating a sustainable educational environment that aligns with global sustainability goals. These findings provide valuable insights for policymakers, educators, and stakeholders in education seeking to develop sustainable frameworks and underline the importance of continued investment in digital circular economy initiatives to support long-term educational and environmental objectives.
Applying Data Science to Analyze and Improve Student Learning Outcomes in Educational Environments Anwar, Nizirwan; Juanda; Anderson, James; Williams, Tane
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.679

Abstract

This study explores the application of data science to analyze and improve student learning outcomes within educational environments, responding to the increasing demand for data-driven approaches in education. The objective is to identify key performance indicators that influence learning success and to develop predictive models that support personalized academic interventions. The research applies a mixed-method approach, combining quantitative data analysis from student records and qualitative insights gathered from educational stakeholders. Machine learning algorithms and statistical models are employed to identify patterns and relationships within large datasets, helping to pinpoint factors such as attendance, engagement levels, and assessment performance that most strongly correlate with learning outcomes. Results indicate that predictive models can effectively forecast student performance, allowing educators to proactively support at risk students and tailor learning experiences to individual needs. Furthermore, the findings demonstrate that integrating data science tools into educational decision-making can improve not only academic outcomes but also institutional strategies for student success. This study concludes that data science offers substantial potential for enhancing learning environments, enabling a more responsive and personalized education system that supports each student’s unique journey towards academic achievement
Harnessing Artificial Intelligence in Higher Education: Balancing Innovation and Ethical Challenges Aprianto, Ronal; Lestari, Etty Puji; Sadan; Fletcher, Eamon
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.680

Abstract

The development of Artificial Intelligence (AI) in higher education has created new opportunities while presenting major challenges. This research aims to explore the impact of AI on higher education, both in terms of benefits and risks that may arise in the future. AI has opened up opportunities to personalize learning experiences, automate administrative processes, and support innovation in curriculum development, potentially improving educational effectiveness. However, there are also concerns regarding the digital divide, data privacy, ethical considerations, and the readiness of educators and institutions to deal with these technological changes. This research uses a literature review approach by analyzing current research on AI implementation in higher education institutions. It also compares case studies from several developed and developing countries to gain a broader picture of the global influence of AI in the education sector. The results show that while AI can have a positive impact in terms of more efficient learning and more effective operations, challenges in terms of equitable access and transparency must be addressed. The novelty of this research lies in the comprehensive analysis of the long-term implications of AI on higher education, as well as the strategies that institutions need to implement to maximize the benefits of AI and minimize the risks. This research makes an important contribution to education stakeholders in understanding the importance of responsible AI adoption to create an inclusive and sustainable educational environment.
The Impact of Educational Information Systems on Learning Accessibility in Higher Education Munthe, Rusli Ginting; Abbas, Maulana; Fernandez, Rico; Ulita, Novena
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.686

Abstract

This study explores the impact of educational information systems on enhancing learning accessibility in higher education, as digital tools increasingly become integral to academic support, and student engagement. The main objective is to assess how these systems improve access to learning resources and facilitate communication, particularly for students from diverse backgrounds and with varying educational needs. Using a mixed-methods approach, this research combines quantitative analysis of accessibility metrics with qualitative insights from surveys and interviews with students and faculty across different higher education institutions. The findings show that educational information systems significantly enhance learning accessibility by providing flexible access to resources, facilitating real-time feedback, and supporting personalized learning paths. These systems also improve student engagement by enabling convenient access to materials and fostering a collaborative learning environment that accommodates different learning styles. However, the study identifies several barriers, including gaps in digital literacy, usability challenges, and unequal access to the necessary infrastructure, which can limit the effectiveness of these systems in reaching all students equally. Additionally, concerns around data privacy and system complexity are noted as areas needing attention to build user trust and ensure smoother system integration. The study concludes that while educational information systems hold great promise for improving accessibility and inclusivity in higher education, addressing these barriers through targeted training, digital equity initiatives, and robust data protection policies is essential for maximizing their potential. These insights offer valuable guidance for educational institutions aiming to create more inclusive learning environments through strategic integration of educational information systems.

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