Autonomous driving paper index
What drives preservice teachers’ use of generative AI as instructional media? A structural and configurational analysis
One-line summary
Introduction The accelerating diffusion of Generative AI (GenAI) in education has sparked interest in understanding how preservice teachers adopt it as instructional media.
Engineering notes
Performance expectancy, perceived learning opportunity, perceived trust, and social impact significantly influenced intended behaviour.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Introduction The accelerating diffusion of Generative AI (GenAI) in education has sparked interest in understanding how preservice teachers adopt it as instructional media. Drawing on the “Unified Theory of Acceptance and Use of Technology 2 (UTAUT2)” as a guided framework, this study examined cognitive, motivational, and contextual drivers of Generative AI use among preservice teachers in Ghana. Methods The descriptive cross-sectional survey design was used and data were collected from 783 preservice teachers using validated questionnaires. The study used the “Partial Least Squares Structural Equation Modelling (PLS-SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA)” to analyse the data. Results and discussion The structural model revealed that behavioural intention strongly predicted GenAI use. Performance expectancy, perceived learning opportunity, perceived trust, and social impact significantly influenced intended behaviour. However, the conditions for facilitation, perceived learning opportunity, and perceived trust directly predicted actual use. Together, the model was able to explain 64.7% of the variance in behavioural intention and 68.8% in GenAI use, both using strong predictive relevance. FsQCA results revealed multiple sufficient configurations leading to high behavioural intention and GenAI use. This emphasises that diverse combinations of cognitive, institutional, and affective factors can drive adoption. The findings further highlight that perceived trust and learning opportunities are central to preservice teachers’ engagement with GenAI. Also, behavioural intention and structural support remain necessary for sustained use. The study offers both theoretical and practical contributions for embedding GenAI literacy and innovative teaching techniques into teacher education programmes.
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