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All Journal Jurnal Kolaboratif Sains UPGRADE: Jurnal Pendidikan Teknologi Informasi
Lalu Setia Yuda
Universitas Negeri Yogyakarta
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PLS-SEM Analysis of Students’ AI Use Examining the Impact of Computational Thinking and Deep Learning Skills Reny Refitaningsih Peby Ria; Nining Anggeraini; Lalu Setia Yuda; Mia Awaliyah
Upgrade : Jurnal Pendidikan Teknologi Informasi Vol 3 No 2 (2026): Februari
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/upgrade.v3i2.6159

Abstract

The massive integration of generative artificial intelligence (AI) in higher education, particularly in scientific writing, calls for a deeper examination of the cognitive foundations underlying students’ AI use. Although prior research has predominantly focused on AI adoption and attitudes, limited attention has been devoted to modeling the cognitive skills that meaningfully shape AI engagement. Addressing this gap, the present study develops and empirically tests a structural model of students’ AI use by investigating the roles of Computational Thinking (CT) and Deep Learning Skills (DLS).A quantitative correlational research design was employed, involving 273 undergraduate students from three teacher education programs. Data were collected using a structured self-administered questionnaire and analyzed through Partial Least Squares–Structural Equation Modeling (PLS-SEM) to evaluate both the measurement model (reliability and validity) and the structural relationships among constructs. The results indicate that both CT and DLS significantly predict students’ AI use in academic writing, with DLS demonstrating a stronger structural effect. The proposed model explains a moderate proportion of variance in AI utilization, suggesting that higher-order cognitive and learning competencies function as central determinants of effective and responsible AI engagement. These findings contribute theoretically by positioning AI use not merely as a technological adoption issue but as a cognitively grounded learning process. The study further implies that higher education curricula should systematically integrate CT and DLS development to ensure that AI serves as a cognitive augmentation tool that strengthens academic integrity and learning quality.
Efek Chat Generative Pre-training Transformer terhadap Kemampuan Berpikir Kritis dan Computational Thinking Mahasiswa dalam Penulisan Karya Ilmiah di Era Revolusi Industri 5.0 Reny Refitaningsih Peby Ria; Lalu Setia Yuda
Upgrade : Jurnal Pendidikan Teknologi Informasi Vol 2 No 2 (2025): Februari
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/upgrade.v2i2.4777

Abstract

Di era perkembangan teknologi, kecerdasan buatan seperti ChatGPT (Generative Pre-training Transformer) telah muncul sebagai alat yang berpotensi mendukung proses pembelajaran serta pengembangan kemampuan berpikir kritis dan Computational Thinking (CT) terutama dalam konteks penulisan karya ilmiah. Oleh karena itu, tujuan penelitian ini untuk mengetahui pengaruh penggunaan ChatGPT terhadap kemampuan berpikir kritis dan mengetahui pengaruh kemampuan berpikir kritis terhadap CT. Metode penelitian ini adalah penelitian deskriptif kuantitatif. Sampel penelitian ini adalah 40 mahasiswa program studi ilmu komputer yang mengambil mata kuliah riset teknologi informasi. Teknik dan instrumen pengumpulan data menggunakan kuesioner. Teknik analisis data menggunakan analisis regresi sederhana. Hasil penelitian ini menunjukkan bahwa terdapat pengaruh positif dan signifikan penggunaan ChatGPT terhadap kemampuan berpikir kritis, serta terdapat pengaruh positif dan signifikan kemampuan berpikir kritis terhadap CT. Implikasi hasil penelitian ini dapat digunakan sebagai referensi ilmiah bagi peneliti selanjutnya yang akan mengkaji lebih mendalam terkait pengaruh penggunaan ChatGPT terhadap kemampuan berpikir dan CT mahasiswa yang memiliki potensi besaruntuk meningkatkan kualitas pembelajaran.
Bibliometric Insights into Computational Thinking and Green Computing Awareness: Emerging Trends Toward Sustainable Digital Pedagogy (2015–2024) Reny Refitaningsih Peby Ria; Lalu Setia Yuda; Elyakim Nova Supriyedi Patty
Jurnal Kolaboratif Sains (Special Issue) - Jurnal Kolaboratif Sains (JKS) - November 2025
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v8i11.9055

Abstract

The digital transformation in higher education requires the integration of computational literacy and environmental awareness to achieve sustainable learning practices. This study aims to map the interrelation between Computational Thinking (CT), Green Computing Awareness (GCA), and the use of statistical analysis software within the framework of Sustainable Digital Pedagogy. The research employed a descriptive bibliometric approach. The dataset consisted of 60 documents refined from the Scopus database covering the 2015–2024 period. Data were analyzed using the analyze results feature on the Scopus website and the VOSviewer software to identify publication trends, thematic networks, and the global evolution of related studies. The findings reveal that CT occupies the most central position in the research landscape, while GCA forms an independent cluster emphasizing energy efficiency and technological sustainability. The use of statistical analysis software serves as a conceptual bridge between the two domains. These findings highlight the need for an integrative approach that combines cognitive, ecological, and analytical dimensions in higher education. This study provides conceptual insights and strategic implications for developing curricula and green digital campus policies oriented toward sustainability.
Co-Authors Elyakim Nova Supriyedi Patty, Elyakim Nova Supriyedi Nining Anggeraini Reny Refitaningsih Peby Ria Reny Refitaningsih Peby Ria Reny Refitaningsih Peby Ria