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Analysis of factors influencing students' adoption of generative AI as a programming learning resource.

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Τίτλος: Analysis of factors influencing students' adoption of generative AI as a programming learning resource.
Συγγραφείς: Theresiawati1 (AUTHOR) theresiawati@upnvj.ac.id, Hidayanto, Achmad Nizar2 (AUTHOR), Seta, Henki Bayu1 (AUTHOR), Widyatmoko, Anindya Maulida2 (AUTHOR), Muhammad, Masabil Arraya2 (AUTHOR), Said, Muhammad Fawwa Arshad2 (AUTHOR), Adifai, Shafir Ramadhina2 (AUTHOR)
Πηγή: Interactive Learning Environments. Jun2026, Vol. 34 Issue 4, p2513-2530. 18p.
Θεματικοί όροι: *Generative artificial intelligence, *Computer programming education, *Innovation adoption, *User experience, *Teaching aids, *Cognitive ability, *Attitudes toward technology, *Structural equation modeling
Περίληψη: 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. [ABSTRACT FROM AUTHOR]
Βάση Δεδομένων: Academic Search Index
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  Data: Analysis of factors influencing students' adoption of generative AI as a programming learning resource.
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  Data: <searchLink fieldCode="JN" term="%22Interactive+Learning+Environments%22">Interactive Learning Environments</searchLink>. Jun2026, Vol. 34 Issue 4, p2513-2530. 18p.
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  Data: 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. [ABSTRACT FROM AUTHOR]
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        Value: 10.1080/10494820.2025.2546630
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        Text: English
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      – SubjectFull: Innovation adoption
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              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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