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All Journal Jurnal Pendidikan Terapan Journal of Vocational, Informatics and Computer Education Journal of Applied Artificial Intelligence in Education
Aprilianti Nirmala S
Universitas Negeri Makassar
Humanities Computer Science & IT Education Social Sciences Other

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The Effect Of Ai Literacy, Ethics, And Motivation On Student Learning Gains Shofiyah Rosyadah; Ahmad Siddiq Mappatunru; Aprilianti Nirmala S; M. Miftach Fakhri
Jurnal Pendidikan Terapan Vol 3, No 3 September (2025)
Publisher : Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The increase in the use of artificial intelligence (AI) in higher education is happening faster than the readiness of literacy and ethical frameworks, thus creating a need to understand the factors that influence the effectiveness of AI utilization on student learning outcomes. This study aims to examine the influence of AI Literacy, AI Ethical Awareness, and Motivation to Learn with AI on Learning Gains and to identify the most dominant predictors. The study used a cross-sectional quantitative design with a sample of university students in Makassar selected through purposive sampling. The measurement of motivation adapted some items from the Academic Motivation Scale (AIMS) that had been psychometrically tested prior to structural analysis. The model was evaluated using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results showed that the three independent variables had a positive and significant effect on Learning Gains, with coefficients β = 0.208 for AI Literacy, β = 0.236 for AI Ethical Awareness, and β = 0.358 for Motivation to Learn with AI. The R² value of 0.532 indicates the model's explanatory power in the moderate category. The f² effect size shows that motivation makes the largest contribution (0.329), while AI Literacy and AI Ethical Awareness have a small effect. Thus, motivation emerges as the strongest predictor, confirming that the successful integration of AI in learning depends not only on technical competence and ethical awareness, but also on the affective dimension of students. These findings contribute to the development of AIED studies and motivation theory, and emphasize the importance of educational strategies that balance literacy, ethics, and motivational support.
The Role of Anthropomorphism in Shaping Students’ Emotional Attachment to AIED: A Triangular Theory of Love Approach Asmi Ulfiah; Al Haytsam Mappaita; Aprilianti Nirmala S; Pramudya Asoka Syukur; Andi Baso Kaswar; Riyama Ambarwati
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.v3i2.263

Abstract

In the digital learning era, Artificial Intelligence in Education (AIED) functions not only as an academic support tool but is also becoming an object of emotional attachment among students. While such attachment may enhance learning motivation, it also raises concerns about emotional dependence and its implications for students’ social and emotional well-being. This study investigates the effects of commitment, enthusiasm, emotional closeness, and anthropomorphic perceptions on students’ emotional dependence on AIED. A quantitative cross-sectional survey was conducted with 109 university students in Makassar using a 1–5 Likert-scale questionnaire. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The structural model explained 62.7% of the variance in emotional dependence on AI (R² = 0.627), indicating moderate to strong explanatory power. Emotional closeness (β = 0.324; t = 2.893; p = 0.004) and anthropomorphic perception (β = 0.440; t = 4.871; p < 0.001) significantly increased emotional dependence, whereas commitment to continued AI use (β = 0.092; t = 0.883; p = 0.377) and enthusiasm toward AI (β = 0.081; t = 0.901; p = 0.367) were not significant predictors. These findings suggest that emotional dependence is driven more by affective engagement and the perception of AI as socially human-like than by cognitive motivation or usage intention. AIED interaction therefore extends beyond functional support into a relational experience resembling interpersonal connection. Given the limited geographic scope, future studies should involve broader populations and employ mixed-method approaches to deepen understanding of emotional dynamics in AIED use.
Analisis Model UTAUT Untuk Mengetahui Tingkat Penerimaan Teknologi Mahasiswa Pada Aplikasi Kahoot Andika Isma; Sitti Hajerah Hasyim; Aprilianti Nirmala S; Nurzabrina Anugrani; Ahmad Luthfi; Ibrahim Al khalil
Journal of Vocational, Informatics and Computer Education Vol 2, No 1 (2024): Juni 2024
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/voice.v2i1.30

Abstract

Teknologi dan internet telah menjadi pendorong utama dalam globalisasi pendidikan, memungkinkan adopsi platform pembelajaran online seperti Kahoot. Penelitian ini menggunakan Model Unified Theory of Acceptance and Use of Technology (UTAUT) sebagai kerangka kerja untuk menganalisis penerimaan dan penggunaan aplikasi Kahoot oleh mahasiswa di Universitas Negeri Makassar. Metode penelitian yang diterapkan adalah pendekatan kuantitatif dengan menggunakan desain cross-sectional, dan data dikumpulkan melalui kuesioner dari 76 responden.Hasil penelitian mengungkapkan bahwa mahasiswa menunjukkan respon positif terhadap manfaat dan kemudahan penggunaan Kahoot. Namun, terdapat variabilitas dalam pandangan terkait dukungan lingkungan, persepsi guru, dan niat pengguna, menggambarkan kompleksitas adopsi teknologi ini di lingkungan pendidikan. Rekomendasi penelitian mencakup pengembangan dukungan lingkungan yang lebih baik, pelatihan bagi dosen dan mahasiswa, serta evaluasi infrastruktur teknologi guna meningkatkan efektivitas pemanfaatan Kahoot dan teknologi pembelajaran di Universitas Negeri Makassar. Temuan ini memberikan wawasan berharga untuk pengembangan pendidikan berbasis teknologi dan inovasi di era digital.
Affective Drivers and Ethical Concerns Shaping AI Use Among University Students Nabilah Auliah Rahman; Melda Auliyah Zakina; Aprilianti Nirmala S; Saipul Abbas
Journal of Applied Artificial Intelligence in Education Vol 1, No 2 (2026): January 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v1i2.6

Abstract

The rapid growth of artificial intelligence (AI) use in higher education raises concerns about how students’ emotional states and the quality of their interactions with AI shape both affective engagement and ethical awareness in academic contexts. This study aims to examine the effects of emotional well-being, AI credibility, and AI interaction quality on students’ ethical awareness, with affective engagement positioned as a mediating mechanism. A quantitative cross-sectional survey was administered to higher education students who use AI tools for academic activities, and the proposed relationships were tested using PLS-based structural modeling with bootstrapping procedures. The findings indicate that emotional well-being (β = 0.549, p < 0.001) and AI interaction quality (β = 0.420, p < 0.001) significantly enhance affective engagement, whereas AI credibility shows no significant effect (β = –0.045, p = 0.342). Affective engagement has a significant positive influence on ethical awareness (β = 0.597, p < 0.001) and significantly mediates the effects of emotional well-being and interaction quality on ethical awareness, while no indirect effect is observed for AI credibility. Overall, these results imply that ethical awareness in student AI use is fostered more strongly through emotionally supportive experiences and high-quality human–AI interactions than through credibility perceptions alone, underscoring the need for human-centered AI integration and ethics-oriented guidance in higher education
Co-Authors Ahmad Luthfi Ahmad Siddiq Mappatunru Al Haytsam Mappaita Andi Baso Kaswar Andika Isma Asmi Ulfiah Ibrahim Al khalil M. Miftach Fakhri Melda Auliyah Zakina Nabilah Auliah Rahman Nurzabrina Anugrani Pramudya Asoka Syukur Riyama Ambarwati Saipul Abbas Shofiyah Rosyadah Sitti Hajerah Hasyim