{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T01:37:13Z","timestamp":1792805833935,"version":"4.5.0"},"reference-count":137,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T00:00:00Z","timestamp":1714348800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fundamental Research Funds for the Central Universities","award":["2022NTSS17"],"award-info":[{"award-number":["2022NTSS17"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Behavioral Sciences"],"abstract":"<jats:p>Generative artificial intelligence (GenAI) has taken educational settings by storm in the past year due to its transformative ability to impact school education. It is crucial to investigate pre-service teachers\u2019 viewpoints to effectively incorporate GenAI tools into their instructional practices. Data gathered from 606 pre-service teachers were analyzed to explore the predictors of behavioral intention to design Gen AI-assisted teaching. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this research integrates multiple variables such as Technological Pedagogical Content Knowledge (TPACK), GenAI anxiety, and technology self-efficacy. Our findings revealed that GenAI anxiety, social influence, and performance expectancy significantly predicted pre-service teachers\u2019 behavioral intention to design GenAI-assisted teaching. However, effort expectancy and facilitating conditions were not statistically associated with pre-service teachers\u2019 behavioral intentions. These findings offer significant insights into the intricate relationships between predictors that influence pre-service teachers\u2019 perspectives and intentions regarding GenAI technology.<\/jats:p>","DOI":"10.3390\/bs14050373","type":"journal-article","created":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T04:01:52Z","timestamp":1714449712000},"page":"373","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":150,"title":["Pre-Service Teachers\u2019 GenAI Anxiety, Technology Self-Efficacy, and TPACK: Their Structural Relations with Behavioral Intention to Design GenAI-Assisted Teaching"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3795-4719","authenticated-orcid":false,"given":"Kai","family":"Wang","sequence":"first","affiliation":[{"name":"Center for Teacher Education Research, Beijing Normal University, Beijing 100091, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5886-233X","authenticated-orcid":false,"given":"Qianqian","family":"Ruan","sequence":"additional","affiliation":[{"name":"School of Education, Minzu University of China, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1524-5038","authenticated-orcid":false,"given":"Xiaoxuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Education, Central China Normal University, Wuhan 430070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9187-7670","authenticated-orcid":false,"given":"Chunhua","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Education, Minzu University of China, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5901-8446","authenticated-orcid":false,"given":"Boyuan","family":"Duan","sequence":"additional","affiliation":[{"name":"School of Education, Minzu University of China, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Thayyib, P., Mamilla, R., Khan, M., Fatima, H., Asim, M., Anwar, I., Shamsudheen, M., and Khan, M.A. (2023). 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