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All Journal Jurnal Pendidikan Terapan Journal of Embedded Systems, Security and Intelligent Systems Journal of Vocational, Informatics and Computer Education Journal of Education for Creativity and Innovation
Aprilianti Nirmala S
Universitas Negeri Makassar
Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media 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

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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.
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.
Analisis Model Penerimaan Teknologi dengan EXT TAM Pada E-learning di Perguruan Tinggi A.Muh Syahidurrahman; Muh Naufal Ramadhani Alwi; Nurul Fadly; Aprilianti Nirmala S
Journal of Education for Creativity and Innovation Vol. 1 No. 1 (2025): Agustus
Publisher : PT. Global Research Collaboration

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Abstract

Universitas mengutamakan keunggulan pendidikan dengan menggunakan sistem e-learning. Studi ini menganalisis model penerimaan teknologi yang diperluas (EXT TAM) dalam konteks ini untuk menunjukkan dinamika penerimaan teknologi di lingkungan pendidikan e-learning perguruan tinggi. Research ini membutuhkan penafsiran yang lebih baik tentang komponen yang membentuk persepsi siswa dan karyawan akademis terhadap adopsi teknologi. Variabel-variabel penting seperti persepsi kegunaan, persepsi kemudahan penggunaan, dan faktor sosial dievaluasi berdasarkan desain penelitian yang hati-hati. Dengan berfokus pada model EXT TAM, analisis data mendalam memberikan gambaran mendalam tentang bagaimana kombinasi faktor-faktor ini memengaruhi adopsi teknologi di institusi pendidikan tinggi. Penelitian ini tidak hanya menambah literatur tentang penerimaan teknologi, tetapi juga memberi administrator akademis ide tentang bagaimana menggunakan teknologi untuk meningkatkan e-learning perguruan tinggi. Hasil ini diharapkan memberikan dasar untuk pembuatan kebijakan pendidikan yang lebih fleksibel dan beradaptasi dengan tuntutan teknologi di dunia pendidikan saat ini.
Development of Doe'ku Application: A Digital Solution to Manage Personal Finance Effectively Nur Annafiah; M. Miftach Fakhri; La Ode Lisbar; Amelia Syamsuddin; Nur Yahya Akhmad; Aprilianti Nirmala S
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 3 (2024): November 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i3.5039

Abstract

The development of the Doe'ku application aims to provide an effective digital solution for managing personal finances. The application is designed to improve users' financial literacy through various features, such as transaction records, budget setting, savings plans, and scheduled transactions. This study utilizes the prototype model software development method, which allows for continuous interaction between developers and users during the application creation process. The results show that the Doe'ku application can assist users in effectively monitoring and managing their finances. User evaluations showed that the application provides an optimal user experience with an intuitive and responsive interface. In addition, the application is designed to be accessible and easy to operate, meeting both the functional and nonfunctional needs of users. As such, the Doe'ku application is expected to contribute significantly to improving users' financial literacy and personal financial management capabilities.
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.
Co-Authors A.Muh Syahidurrahman Ahmad Luthfi Ahmad Siddiq Mappatunru Al Haytsam Mappaita Amelia Syamsuddin Andi Baso Kaswar Andika Isma Asmi Ulfiah Ibrahim Al khalil La Ode Lisbar M. Miftach Fakhri Muh Naufal Ramadhani Alwi Nur Annafiah Nur Yahya Akhmad Nurul Fadly Nurzabrina Anugrani Pramudya Asoka Syukur Riyama Ambarwati Shofiyah Rosyadah Sitti Hajerah Hasyim