Alvarez, Lionel Ortoleva, Giulia Sutter Widmer, Denise Fritz, Mattia Bugmann, Julien Boéchat-Heer, Stéphanie Ramillon, Corinne 2024 Generative artificial intelligence (genAI) has undergone rapid advancements, presenting challenges to teacher education. In this study, we explore genAI acceptance among pre-service teachers, concerning both their roles as current students and aspiring professionals. Our survey engaged a sample size of 256 pre-service teachers drawn from six universities in French-speaking Switzerland. Their perspectives offer valuable context for understanding genAI acceptance and calls for a review of the General Extended Technology Acceptance Model for E-Learning (GETAMEL), as genAI shows several peculiarities. For instance, the perceived ease of use seems to be insignificant in predicting acceptance. As genAI continues to evolve, educators’ viewpoints will significantly influence its adoption and transformation within educational contexts. Our results underscore the dynamic landscape of genAI in education and the importance of informed adoption strategies within teacher training institutions. application/pdf https://folia.unifr.ch/unifr/documents/329547 https://folia.unifr.ch/documents/329547/files/74a1adb0d0fb-___paper_224377.pdf eng info:eu-repo/semantics/openAccess License undefined Journal of Technology and Teacher Education. - 2024, vol. 32, no. 3, p. 383-408 info:eu-repo/classification/udc/37 Future teachers’ beliefs about generative AI. Assessing technology acceptance as students or as aspiring professionals http://purl.org/coar/resource_type/c_6501