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All Journal JURNAL PENDIDIKAN TAMBUSAI Jurnal Ilmiah Ilmu Terapan Universitas Jambi
Safitri, Rahma Ayu
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Education Engineering Industrial & Manufacturing Engineering Social Sciences

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ADOPTION OF ARTIFICIAL INTELLIGENCE IN STEM LEARNING: EXAMINING THE EFFECTS OF PERFORMANCE, EFFORT, AND SOCIAL FACTORS Sumandya, I Wayan; Widana, I Wayan; Hendra, Robi; Supian, Supian; Yusuf, Muhammad; Wijaya, Hansein Arif; Safitri, Rahma Ayu
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 4 (2025): Volume 9, Nomor 4, December 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i4.44475

Abstract

Artificial Intelligence (AI) has recently gained prominence in higher education, particularly in Science, Technology, Engineering, and Mathematics (STEM) disciplines, offering transformative potential for learning and innovation. However, students’ adoption of AI tools is influenced by multiple psychological and contextual factors. This study aims to examine the effects of performance expectancy, effort expectancy, and social influence on students’ behavioral intentions to integrate AI into STEM education. A quantitative research design was employed, involving 203 undergraduate students from the University of Jambi and Universitas PGRI Mahadewa Indonesia. Data were analyzed using Structural Equation Modeling (SEM) through SmartPLS 3.3 to identify direct and mediating relationships among variables. The findings revealed that performance expectancy significantly influenced students’ behavioral intentions, indicating that perceived usefulness of AI outweighs ease of use in determining adoption. Effort expectancy also had a substantial effect and mediated the relationship between performance expectancy and behavioral intentions, while social influence showed no significant impact. These results highlight that students’ engagement with AI in STEM learning is driven more by perceived academic and functional benefits than by peer or social reinforcement. The novelty of this study lies in its integration of the Unified Theory of Acceptance and Use of Technology (UTAUT) framework with the STEM education context in developing countries, providing new empirical insights into AI adoption behavior. The study recommends designing AI-supported learning environments that emphasize practical benefits, user-friendly interfaces, and pedagogical integration to enhance students’ learning outcomes and technological readiness.
Studi Kualitatif Efektivitas Penerapan Model CTL, Group Investigation, dan Quantum Learning dalam Proses Pembelajaran di Sekolah Safitri, Rahma Ayu; Anggun, Anggun; Iryani, Eva
Jurnal Pendidikan Tambusai Vol. 9 No. 3 (2025): Desember
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

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Abstract

Sistem pendidikan yang mendorong siswa untuk berpikir kritis, inovatif, berkolaborasi, dan berkomunikasi diperlukan di abad ke-21. Paradigma pembelajaran saat ini beralih dari guru ke siswa. Guru bukan lagi satu-satunya sumber pengetahuan; mereka sekarang membantu siswa belajar secara mandiri sebagai fasilitator dan motivator. Studi ini akan menyelidiki bagaimana tiga model pembelajaran baru—Contextual Teaching and Learning (CTL), Group Investigation (GI), dan Quantum Learning—mampu meningkatkan kualitas pembelajaran di sekolah. Studi dilakukan dengan membaca literatur terkait. Hasil analisis menunjukkan bahwa CTL membantu menghubungkan materi pembelajaran ke situasi dunia nyata siswa; GI meningkatkan kemampuan siswa untuk berpikir kritis dan bekerja sama; dan Quantum Learning dapat membuat lingkungan belajar yang menyenangkan dan bermakna. Mereka berbeda dalam pendekatan, strategi, dan fokus pengembangan, meskipun keduanya berfokus pada meningkatkan keaktifan dan makna belajar siswa.
Co-Authors Anggun Anggun, Anggun Eva Iryani, Eva Hansein Arif Wijaya Hendra, Robi I Wayan Sumandya Muhammad Yusuf Supian Widana, I Wayan