Article Per Year (5 Year)
p-Index From 2021 - 2026
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All Journal JUTECH : Journal Education and Technology TOFEDU: The Future of Education Journal
Mugiarti Nur Fadlilah
Universitas Muhammadiyah Purwokerto
Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Other

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ARTIFICIAL INTELLIGENCE DAN SELF-REGULATED LEARNING: TELAAH EPISTEMOLOGIS PERSPEKTIF TEORI BARAT DAN FILSAFAT ISLAM Fawwaz Adzansyah Islamy; Mugiarti Nur Fadlilah; Rr Setyawati
JUTECH : Journal Education and Technology Vol 6, No 2 (2025): JUTECH DESEMBER
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jutech.v6i2.5979

Abstract

The development of artificial intelligence in higher education has transformed the ways students access, process, and construct knowledge, thereby generating significant epistemic implications for self-regulated learning. This article aims to examine the relationship between AI and self-regulated learning from an epistemological perspective by integrating Western theories and Islamic philosophy. The study employs a systematic literature review of scholarly publications from 2021 to 2025 that address artificial intelligence, self-regulated learning, and epistemic cognition among university students. The findings indicate that, from a Western perspective, AI is conceptualized as a cognitive and metacognitive tool that supports planning, monitoring, and reflective learning through adaptive feedback and personalized learning experiences. However, uncritical use of AI may weaken students’ epistemic agency and foster cognitive dependency. From the perspective of Islamic philosophy, AI is positioned as a wasilah (means) that holds epistemic value when used ethically and guided by intention (niyyah), moral conduct (akhlaq), and moral responsibility. This article underscores that the epistemic value of AI is not inherent in the technology itself, but is determined by the quality of students’ self-regulated learning and their epistemic awareness as learning subjects.
Development of a Peer Social Support Scale for Students: A Content Validity Approach Through Expert Judgment Mugiarti Nur Fadlilah; Azzura Laila Amalisy
The Future of Education Journal Vol 5 No 2 (2026)
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah Yayasan Pendidikan Tumpuan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61445/tofedu.v5i2.1748

Abstract

Social support is a crucial psychosocial factor that contributes to individuals’ mental health and well-being, particularly during emerging adulthood when peer relationships become increasingly significant. Despite extensive research on social support, measurement of peer social support remains inconsistent and often lacks specificity and contextual relevance. This study aimed to develop a psychological measurement scale of peer social support based on five dimensions: emotional support, esteem support, tangible/instrumental support, informational support, and network support. The research employed a quantitative approach with an instrument development design focusing on content validity evaluation. A total of 30 items were constructed and assessed by four psychology experts using a relevance rating scale. Content validity was analyzed using Aiken’s V coefficient. The results indicated that Aiken’s V values ranged from 0.35 to 0.80, with 19 items meeting the validity threshold (V ≥ 0.60), consisting of highly valid and valid items, while 11 items were excluded. The findings suggest that the developed instrument demonstrates adequate content validity in representing the construct of peer social support, although some dimensions require further refinement. This study highlights the importance of systematic item development and expert evaluation in ensuring measurement accuracy. Future research is recommended to examine construct validity and reliability to establish the psychometric robustness of the scale.
Global Trends in Intervention Strategies for Academic Integrity in the Age of Generative Artificial Intelligence: A Bibliometric Analysis Mugiarti Nur Fadlilah; Arthadi Fitri Utami; Fiki Febriani; Herdian Herdian; Nur'aeni Nur'aeni
The Future of Education Journal Vol 5 No 2 (2026)
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah Yayasan Pendidikan Tumpuan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61445/tofedu.v5i2.1937

Abstract

The rapid adoption of Generative Artificial Intelligence (AI), particularly ChatGPT and other large language models, has transformed higher education and raised significant concerns regarding academic integrity. This study aims to analyze global research trends on intervention strategies for maintaining academic integrity in the era of Generative AI through a bibliometric approach. Data were collected from the Scopus database, resulting in 100 publications published between 2021 and 2024. Bibliometric analysis was conducted using VOSviewer to examine publication trends, country contributions, keyword co-occurrence networks, and thematic developments. The findings indicate a substantial increase in scholarly attention following the emergence of Generative AI technologies. Five major thematic clusters were identified: academic integrity and plagiarism prevention, Generative AI integration in higher education, assessment redesign and pedagogical intervention, AI literacy and ethical education, and student behavior and psychological responses. The results reveal a notable shift from detection- and punishment-based approaches toward preventive and educational strategies, including AI literacy programs, authentic assessment redesign, ethics education, and institutional policy development. The study also highlights the growing importance of holistic intervention frameworks that integrate technological adaptation, pedagogical innovation, and ethical awareness. These findings provide a comprehensive overview of the evolving research landscape and offer valuable insights for developing sustainable academic integrity frameworks in higher education.
Co-Authors Arthadi Fitri Utami Azzura Laila Amalisy Fawwaz Adzansyah Islamy Fiki Febriani Herdian Nur'aeni Nur'aeni Rr Setyawati