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Adam Mudinillah
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alhijr@staialhikmahpariangan.ac.id
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Al-Hijr: Journal of Adulearn World
Published by Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar
ISSN : 28293894     EISSN : 28294351     DOI : https://doi.org/10.55849/alhijr
Core Subject : Science, Education,
Computer Science & IT Education Languange, Linguistic, Communication & Media Other
Al-Hijr: Journal of Adulearn World is a multi-disciplinary, peer-refereed open-access international journal which has been established for the dissemination of state-of-the-art knowledge in the field of education, teaching, development, instruction, educational projects and innovations, learning methodologies, and new technologies in education and learning. The journal publishes state-of-art papers in fundamental theory, experiments, and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion, and concise conclusion. As our commitment to the advancement of science and technology, the Al-Hijr follows the open access policy that allows the published articles freely available online without any subscription. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
Arjuna Subject : Umum - Umum
Articles 6 Documents
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Search results for , issue "Vol. 4 No. 1 (2025)" : 6 Documents clear
Application of Machine Learning to Personalization of Adaptive Curriculum in Indonesian Middle Schools Rachman, Azhariah
Al-Hijr: Journal of Adulearn World Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/alhijr.v4i1.845

Abstract

In recent years, there has been increasing interest in utilizing Machine Learning (ML) to personalize the learning experience in educational settings. The application of ML in middle school curriculums in Indonesia presents an opportunity to enhance adaptive learning models tailored to individual students’ needs. This study aims to explore the potential of integrating ML algorithms to create a personalized, adaptive curriculum for middle school students. The primary objective is to evaluate how ML can optimize learning outcomes by adjusting content delivery based on student performance and learning patterns. Using a mixed-methods approach, the research combines qualitative data from educators and quantitative data from student performance metrics to design a model for adaptive learning. The ML algorithms used include decision trees, clustering, and reinforcement learning, which adaptively modify the curriculum based on real-time student feedback. The results show a significant improvement in student engagement and academic performance, with tailored content leading to better learning outcomes. The study concludes that ML-driven personalization can be effectively integrated into middle school curriculums, offering a scalable solution to enhance educational quality in Indonesia.
Development of Gamification-Based Smart Education Platforms to Increase Student Involvement Syarif, Afwan; Som, Rit; Pao, Chai
Al-Hijr: Journal of Adulearn World Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/alhijr.v4i1.846

Abstract

The integration of technology into education has led to innovative teaching methods aimed at enhancing student engagement and participation. One such method is gamification, which leverages game mechanics to make learning more interactive and motivating. However, traditional educational models often fail to fully engage students, resulting in disengagement and suboptimal learning outcomes. This study aims to develop a gamification-based smart education platform designed to increase student involvement by integrating game elements into the learning process. The primary objective is to assess the effectiveness of gamification in enhancing student engagement, learning outcomes, and overall classroom participation. A mixed-methods approach was used, combining both qualitative and quantitative data collection methods. The research involved the design, development, and implementation of a smart education platform that incorporated elements such as points, badges, leaderboards, and challenges. Data was gathered from 200 students across various disciplines, and engagement metrics, academic performance, and student feedback were analyzed. The results showed a significant increase in student involvement and motivation, with notable improvements in academic performance and class participation. Students reported a higher level of enjoyment and interaction with the platform, indicating that gamification enhanced their learning experience. This study concludes that gamification-based smart education platforms are an effective tool for increasing student engagement and improving learning outcomes, offering a promising approach for modern educational environments.
Management of AI-Based Education Data to Optimize the Learning Process Oci, Markus; Na, Li; Hui, Zhou
Al-Hijr: Journal of Adulearn World Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/alhijr.v4i1.850

Abstract

The rapid advancement of artificial intelligence (AI) technologies has led to their growing integration in educational systems, promising to revolutionize the learning process. AI has the potential to optimize learning by personalizing educational experiences, improving decision-making, and enhancing the management of educational data. However, despite these advancements, there is still a lack of systematic approaches to managing AI-based education data in a way that can consistently optimize the learning process. This study aims to explore how AI-based education data management can enhance the learning process by improving data-driven decision-making, student engagement, and performance tracking. A mixed-methods research design was used, combining qualitative case studies and quantitative data analysis. The study involved analyzing AI-driven data management tools used in several educational institutions to optimize learning outcomes. Surveys, interviews, and data analysis were used to evaluate the effectiveness of these tools in real-world educational settings. The results indicate that AI-based data management tools significantly enhance the learning process by providing real-time feedback, personalized learning paths, and better resource allocation. Educators and students reported increased engagement and improved learning outcomes due to the use of AI-powered tools. This study concludes that effective management of AI-based education data is essential for optimizing the learning process. Educational institutions should prioritize the integration of AI-driven data systems to maximize learning outcomes and efficiency.
Adaptive Curriculum Development Based on Learning Analytics Analysis in Higher Education Sumilat, Rohyani Rigen Is; Lee, Ava; Tan, Ethan; Purnomo, Widiharto
Al-Hijr: Journal of Adulearn World Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/alhijr.v4i1.851

Abstract

The integration of learning analytics into higher education has the potential to revolutionize curriculum development by providing data-driven insights into student learning patterns, strengths, and weaknesses. Adaptive curriculum development, which tailors educational content to the diverse needs of students, is becoming increasingly important as educational institutions seek to improve student engagement, retention, and success rates. However, the effective implementation of adaptive curricula based on learning analytics remains underexplored in higher education contexts. This study aims to explore the potential of learning analytics in developing adaptive curricula that align with students’ learning behaviors, preferences, and academic performance. A mixed-methods approach was employed, combining quantitative data analysis of learning analytics with qualitative feedback from students and instructors. Data was collected from a cohort of 200 students enrolled in a large university, utilizing learning management systems to track student interactions, assessments, and engagement. The results indicate that curricula developed based on learning analytics led to significant improvements in student performance and engagement, particularly for at-risk students. Personalized learning paths and real-time adjustments were shown to enhance learning outcomes. This study concludes that learning analytics can play a crucial role in adaptive curriculum development in higher education, providing a pathway for more effective and personalized learning experiences.
The Role of The Teacher as A Facilitator in Project-Based Learning With AI Support Yuna, Jung; Minho, Kim; Jiwon, Han; Jiwon, Lee; Suyitno, Suyitno
Al-Hijr: Journal of Adulearn World Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/alhijr.v4i1.855

Abstract

Project-based learning (PBL) has gained widespread recognition as an effective instructional method that promotes critical thinking, collaboration, and problem-solving skills among students. In this context, the role of the teacher as a facilitator is crucial in guiding students through the learning process while encouraging autonomy and exploration. With the increasing integration of artificial intelligence (AI) in education, AI tools have become valuable resources to support both teachers and students in PBL environments. However, the specific role of teachers as facilitators in AI-supported PBL settings remains underexplored. This study aims to investigate the role of the teacher as a facilitator in project-based learning environments where AI tools are utilized to enhance the learning experience. A mixed-methods approach was employed, including surveys, interviews, and classroom observations involving 150 students and 20 teachers from schools implementing AI-supported PBL. The study assessed the impact of AI tools on teacher facilitation and student outcomes in terms of engagement, creativity, and problem-solving abilities. The results indicate that AI tools significantly supported teachers in managing and facilitating PBL, allowing for more personalized guidance and efficient task management. Students reported higher levels of engagement and improved collaboration, while teachers emphasized the increased ability to focus on individualized support. This study concludes that the teacher’s role as a facilitator is essential in leveraging AI tools to optimize project-based learning, enhancing both teaching practices and student outcomes.
The Influence of Mobile Learning on Student Motivation in Remote Areas Al-Mansour, Youssef; Al-Jawad, Khaled; Al-Nasser, Maha
Al-Hijr: Journal of Adulearn World Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/alhijr.v4i1.860

Abstract

Mobile learning has become a pivotal educational tool, especially in remote areas where access to traditional educational resources is limited. In these settings, mobile learning offers flexibility, accessibility, and the potential to engage students in their learning process. The influence of mobile learning on student motivation in remote areas, however, remains an area that has not been extensively studied. This research investigates the impact of mobile learning on student motivation in remote areas, aiming to understand how mobile devices and applications can improve student engagement, learning outcomes, and persistence in these regions. A mixed-methods approach was employed, combining quantitative surveys to measure student motivation and qualitative interviews to gather insights into the personal experiences of students and educators. The study involved 300 students from remote areas who used mobile learning tools over a semester. The results show a significant increase in student motivation, with 65% of students reporting greater engagement in learning activities. Students cited the flexibility, accessibility, and interactive nature of mobile learning as key factors that contributed to their motivation. This study concludes that mobile learning positively influences student motivation in remote areas, offering valuable opportunities for improving education in underserved regions. Mobile learning can be an essential tool in bridging educational gaps and fostering student engagement, even in challenging learning environments.

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