Survey analysis reveals key factors influencing teacher education students' acceptance of large language models, suggesting improvements for educational tech training.
Key Points
The strongest predictor of behavioral intention for using large language models is subjective norms.
Perceived ease of use significantly and positively impacts attitudes toward large language models by teacher education students.
Perceived time risk has a significant negative effect on perceived usefulness of large language models in educational settings.
Usage experience enhances learning motivation, fostering adoption behaviors for large language models among students.