Extending the TAM framework: Exploring learning motivation and agility in educational adoption of generative AI
Yazarlar (3)
Doç. Dr. Ahmet Salih ŞİMŞEK Kırşehir Ahi Evran Üniversitesi, Türkiye
Gülüzar Şule Tepetaş Cengiz Bolu Abant İzzet Baysal Üniversitesi, Türkiye
Mazhar Bal Akdeniz Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | Education and Information Technologies (Q1) | ||
| Dergi ISSN | 1360-2357 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SSCI | ||
| Makale Dili | Türkçe | Basım Tarihi | 05-2025 |
| Kabul Tarihi | 12-04-2026 | Yayınlanma Tarihi | – |
| Cilt / Sayı / Sayfa | 30 / 15 / 20913–20942 | DOI | 10.1007/s10639-025-13591-9 |
| Makale Linki | https://doi.org/10.1007/s10639-025-13591-9 | ||
| Özet |
| Generative AI technologies are rapidly transforming educational practices, creating both opportunities and challenges for teacher-preparation programs. As these advanced tools become increasingly prevalent in classrooms, understanding the factors that influence pre-service teachers' acceptance and adoption of such technologies has become critically important for effective educational policies and practices. This study aims to extend the Technology Acceptance Model (TAM) to examine the factors influencing pre-service teachers' adoption of generative AI tools. The research is based on data collected from 748 pre-service teachers from 12 universities in Turkey. The model includes the core constructs of TAM as well as exogenous variables such as Metacognitive Self-regulation (MSR), Subjective Norm (SN), Learning Motivation (LM) and Learning Agility (LA). The results of Structural Equation Modeling showed … |
| Anahtar Kelimeler |
| Agility | Generative artificial ıntelligence | Learning motivation | Structural equation modeling | Technology acceptance model |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 17 |
| Scopus | 8 |
| Web of Science | 8 |