Analysis of factors influencing students’ adoption of generative AI as a programming learning resource
Bibliographic Data
| ID | 21632893 |
|---|---|
| Authors | Theresiawati Theresiawati (Universitas Pembangunan Nasional Veteran Jakarta, corresponding author), Achmad Nizar Hidayanto (0000-0002-5793-9460, University of Indonesia), Henki Bayu Seta (0000-0001-9771-3792, Universitas Pembangunan Nasional Veteran Jakarta), Anindya Maulida Widyatmoko (University of Indonesia), Masabil Arraya Muhammad (University of Indonesia), Muhammad Fawwa Arshad Said (University of Indonesia), Shafir Ramadhina Adifai (University of Indonesia) |
| Year | 2026 |
| Volume | 34 |
| Issue | 4 |
| Pages | 2513-2530 |
| Publication date | 2026-04-21 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Interactive Learning Environments (JOURNAL) |
| Journal identifiers | ISSN: 1049-4820 • E-ISSN: 1744-5191 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10494820.2025.2546630 |
| OpenAlex | W7128217944 |
| Language | EN |
| Citations received | 1 |
| References cited | 71 |
Generative AI has the potential to serve as a valuable learning resource in programming education by offering individualized learning experiences, self-directed learning support, and automatic feedback. However, research on the factors influencing its adoption in programming education in students’ perspectives is scarce. Thus, this study investigates the factors that motivate students to utilize generative AI as a programming learning tool. The focus is on how technophilia and perceived intelligence affect how students think about and use technology. We conducted a survey involving 410 respondents and analyzed the data using SmartPLS and structural equation modeling (SEM). The findings show that both technophilia and perceived intelligence have a significant impact on perceived usefulness, ease of use, trust, and enjoyment, all of which have an indirect effect on adoption intention. Furthermore, perceived usefulness, enjoyment, and trust significantly impact students’ intention to use generative AI in programming learning, while perceived ease of use lacks this impact. These findings offer significant insights for generative AI developers and policymakers seeking to improve the intelligence and usability of generative AI in programming education. This study advances AI-driven programming education by providing a deeper understanding of students’ adoption behaviors, resulting in more effective and engaging learning environments
Educational technology · Electronic learning · Generative grammar · Generative model · AI in Service Interactions · Diverse Interdisciplinary Research Innovations · Teaching and Learning Programming
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| Citations per year | 1 |
|---|---|
| Citation span | 2025 - 2025 (1) |
| Highly cited | No |