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All Journal Mattawang: Jurnal Pengabdian Masyarakat Vokatek : Jurnal Pengabdian Masyarakat Journal of Embedded Systems, Security and Intelligent Systems Journal of Vocational, Informatics and Computer Education Indonesian Technology and Education Journal Jurnal MediaTIK Jurnal MEKOM: Media Komunikasi Pendidikan Kejuruan Journal of Renewable Energy and Smart Device Innovation and Applied Education Journal
Pramudya Asoka Syukur
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Humanities Computer Science & IT Education Electrical & Electronics Engineering Engineering Public Health Social Sciences Other

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Journal : Journal of Vocational, Informatics and Computer Education

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Integrasi ChatGPT dalam Blended Learning dalam Mengoptimalkan Pemahaman Materi Pembelajaran Aminuddin; Nurmila; Pramudya Asoka Syukur; Nurul Islamia; Andi Dio Nurul Awalia
Journal of Vocational, Informatics and Computer Education Vol 2, No 2 (2024): Desember 2024
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/voice.v2i2.20246

Abstract

Kemajuan teknologi menghadirkan tantangan bagi perguruan tinggi untuk menghasilkan lulusan yang tidak hanya menguasai ilmu pengetahuan, tetapi juga mampu memanfaatkan teknologi digital dalam mendukung produktivitas dan daya saing. Penelitian ini bertujuan untuk menganalisis pengaruh integrasi blended learning dan ChatGPT terhadap pemahaman materi, efisiensi pembelajaran, dan pengalaman penggunaan di perguruan tinggi. Metode yang digunakan adalah pendekatan kuantitatif dengan desain penelitian cross-sectional dan pengumpulan data melalui kuesioner menggunakan skala Likert. Hasil penelitian menunjukkan bahwa blended learning secara efektif meningkatkan pemahaman materi dengan partisipasi aktif dalam diskusi, ChatGPT mendukung motivasi dan kreativitas mahasiswa dalam belajar, serta kombinasi keduanya meningkatkan efisiensi pembelajaran melalui penghematan waktu dan akses informasi yang lebih baik. Mayoritas responden memberikan tanggapan positif terhadap penerapan model ini, mencerminkan keberhasilan integrasi teknologi dalam pembelajaran. Hasil ini juga mendukung relevansi blended learning dan ChatGPT sebagai solusi inovatif dalam memenuhi kebutuhan pembelajaran modern. Penelitian ini mengimplikasikan bahwa integrasi teknologi dalam pendidikan dapat mempercepat transformasi pembelajaran yang lebih efektif dan fleksibel.
The Role of Anthropomorphism in Shaping Students’ Emotional Attachment to AIED: A Triangular Theory of Love Approach and PLS-SEM Analysis in Makassar Universities Asmi Ulfiah; Mappaita, Al Haytsam; Aprilianti Nirmala S; Pramudya Asoka Syukur; Andi Baso Kaswar; Riyama Ambarwati
Journal of Vocational, Informatics and Computer Education Vol 3, No 2 (2025): Desember 2025
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/pkd1h154

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 Akis, Dwi Ihza Sari Aminuddin, Amin Andi Baso Kaswar Andi Baso Kaswar Andi Dio Nurul Awalia Andika Isma Annajmi Rauf Aprilianti Nirmala S Arsyanda Asham Bin Jamaluddin Asmi Ulfiah Asri Ismail Dahniar Darwis, Muhammad Ridha Devi Miftahul Jannah Elma Nur Jannah Fadhel Akbar Fathur Rahman Izzaturrahman Kurnia Prima Putra Linggi, Cantika Randa M. Gilang Ramadhan M. Miftach Fakhri Mahardika, Ananta Tri Mappaita, Al Haytsam Muh. Rahmat Wahyudi JY Muhalim Muhammad Iqram Nur Amalia Ramadhan Nur Annafiah Nur Fadhylah As Nurmila Nurul Islamia Riyama Ambarwati Rosidah Sofyan, Vina Annisa SRI RAHAYU Vina Annisa Sofyan Wahyu Hidayat M