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All Journal Information Technology Education Journal Artificial Intelligence in Lifelong and Life-Course Education Artificial Intelligence in Educational Decision Sciences Journal of Vocational, Informatics and Computer Education Journal of Applied Artificial Intelligence in Education Journal of Education for Creativity and Innovation Journal of Educational Studies in Science, Technology, Engineering, Arts and Humanities JESI : Journal of Engineering Service and Innovation
Nurrahmah Agusnaya
Universitas Negeri Makassar
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Determinants of AI Trust in Education: The Role of Ethical Awareness, Ethical Risk, and Human-Centered Orientation Abil Alam; Nur Wahyu Adrian; Nurrahmah Agusnaya; Saipul Abbas; Santi Widyawati
Journal of Vocational, Informatics and Computer Education Vol 3, No 2 (2025): December 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v3i2.265

Abstract

The development of Artificial Intelligence in Education (AIED) is increasingly being used by university students in Indonesia, particularly through generative chatbots and AI-based learning systems to support assignment writing, reference searches, and material comprehension. Although offering efficiency and academic support, the use of AIED also raises ethical issues such as academic integrity, data security, bias, transparency, and responsibility, indicating that student trust is not only determined by the benefits of technology, but also by ethical awareness and human-centered orientation of use. This study aims to analyze the influence of AI Ethical Awareness, Perceived Ethical Risk, Perceived Usefulness, and Human-Centered Orientation on AI Trust, as well as the role of AI Trust in shaping Ethical Awareness in AIED among university students in Indonesia. The study used a quantitative approach with a cross-sectional survey design. Data were collected using a Likert scale questionnaire that measured six main constructs, then analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) to test the validity, reliability, and structural relationships between variables. The results showed that perceptions of the benefits of AIED, human-centered orientation, and ethical awareness contributed positively to the formation of students' trust in AIED, while perceptions of ethical risks tended to weaken that trust. Furthermore, trust in AIED plays an important role in increasing students' ethical awareness in the use of AI in academic environments. These findings emphasize the importance of strengthening AI ethics literacy and applying human-centered principles in AIED policies and designs to encourage more responsible use of AI in higher education.
Hands-on Training Magicschool: Peningkatan Keterampilan Pembelajaran Digital bagi Guru SMKS Handayani Gowa Berbasis Experiential Learning Approach Putri Nirmala; Nurrahmah Agusnaya; Taufik Bahtiar; M. Miftach Fakhri; Rosidah
Journal of Engineering Service and Innovation Volume 1, Issue 1 (Agustus) 2025
Publisher : Fakultas Teknik

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Abstract

Perkembangan teknologi digital menuntut guru untuk memiliki keterampilan dalam memanfaatkan media pembelajaran interaktif agar dapat menciptakan pembelajaran yang inovatif dan relevan dengan kebutuhan siswa abad ke-21. Namun, tingkat keterampilan digital guru di SMKS Handayani Sungguminasa Gowa masih berada pada tahap pengembangan dan membutuhkan peningkatan yang lebih optimal. Untuk menjawab tantangan ini, dilakukan kegiatan pengabdian kepada masyarakat melalui hands-on training berbasis experiential learning menggunakan platform Magicschool sebagai alat bantu pembuatan konten interaktif. Pelatihan ini dirancang dalam empat tahap: concrete experience, reflective observation, abstract conceptualization, dan active experimentation. Hasil pretest menunjukkan keterampilan digital guru masih rendah, sedangkan hasil posttest menunjukkan peningkatan signifikan dengan skor rata-rata 4,33 hingga 4,67. Analisis Paired Samples T-Test menunjukkan perbedaan signifikan antara skor pretest dan posttest pada semua indikator (p < 0,001). Temuan ini menunjukkan bahwa pelatihan hands-on berbasis experiential learning efektif dalam meningkatkan keterampilan guru dalam penggunaan media pembelajaran digital. Dengan demikian, pelatihan ini dapat menjadi alternatif solusi dalam mengembangkan kompetensi guru dalam menghadapi tantangan transformasi pendidikan di era digital.
Learning Autonomy and Effectiveness in AI-Supported Engineering Education Integrating Technology Acceptance and Motivation Haeril Anwar; Ismawati; Nurrahmah Agusnaya; Andi Akram Nur Risal; Dary Mochammad Rifqie
Artificial Intelligence in Lifelong and Life-Course Education Vol 1 No 2 (2026): Artificial Intelligence in Lifelong and Life-Course Education
Publisher : PT. Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/aillce.v1i2.14

Abstract

Purpose – This study examines the influence of learning autonomy on learning effectiveness in artificial intelligence supported learning among engineering students by extending the Technology Acceptance Model with motivational and psychological factors.Design/methods/approach – A quantitative cross-sectional survey was conducted involving 90 engineering students from a public university in Indonesia who had experience using artificial intelligence tools for academic learning. Data were analyzed using partial least squares structural equation modeling to examine the relationships among perceived usefulness, self-efficacy, willingness for autonomous learning, and learning effectiveness and autonomy.Findings – The results indicate that perceived usefulness, self-efficacy, and willingness for autonomous learning all have significant positive effects on learning effectiveness and autonomy. Willingness for autonomous learning emerged as the strongest predictor, highlighting the central role of students’ internal motivation and readiness to manage their own learning processes in AI-supported environments.Research implications/limitations – The study is limited by its cross-sectional design, reliance on self-reported data, and a sample restricted to engineering students from a single institution, which may limit generalizability.Originality/value – This study extends the Technology Acceptance Model by integrating learning autonomy and motivational factors within an artificial intelligence supported learning context, offering empirical evidence to inform the design of balanced and student-centered AI-enhanced learning in higher education.
Co-Authors Abil Alam Ahmad Faris Al Faruq Akbar Fadila Ana Sulistiana Alwi Andi Akram Nur Risal Andi Anggi Kemalasari Andi Dio Nurul Awalia Andi Muhammad Faruq Arum Putri Rahayu Dary Mochammad Rifqie Dewi Fatmarani Surianto Fadhil Zil Ikram Fajriani Azis Firdaus Fitra Yusuf Haeril Anwar Irwansyah Suwahyu Ismawati Khalil Mubaraq Darwing M. Andika Aswa M. Miftach Fakhri M. Miftach Fakhri M.Miftach Fakhri Muh Amirul Mukmi Muh Andhka Maharsaka Suaib Muh. Yusril Anam Muhammad Fardan Muhammad Husair Nawawi Nur Syafitra Ramadhani Nur Wahyu Adrian Nurwahyuni Paallo Pramudya Asoka Syukur Putri Nirmala Rachmawaty Kadir Rahmawati Rina Asriani J Tudon B Rosidah Rosidah Saipul Abbas Sakinah Mawaddah Santi Widyawati Taufik Bahtiar Ummul Khaeri Masna Yohana Rara