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ERIC Number: EJ1447872
Record Type: Journal
Publication Date: 2024
Pages: 26
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1059-7069
EISSN: EISSN-1943-5924
Future Teachers' Beliefs about Generative AI. Assessing Technology Acceptance as Students or as Aspiring Professionals
Lionel Alvarez; Giulia Ortoleva; Denise Sutter Widmer; Mattia Fritz; Julien Bugmann; Stéphanie Boéchat-Heer; Corinne Ramillon
Journal of Technology and Teacher Education, v32 n3 p383-408 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.
Association for the Advancement of Computing in Education. P.O. Box 719, Waynesville, NC 28786. Tel: 828-246-9558; Fax: 828-246-9557; e-mail: info@aace.org; Web site: http://www.aace.org
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Switzerland
Grant or Contract Numbers: N/A