Chengming Zhang , Min Hu , Weidong Wu , Yanfen Chen , Farrukh Kamran , Xining Wang
{"title":"职前教师人工智能接受度概况分析:结合行为、技术和人为因素","authors":"Chengming Zhang , Min Hu , Weidong Wu , Yanfen Chen , Farrukh Kamran , Xining Wang","doi":"10.1016/j.tate.2025.105086","DOIUrl":null,"url":null,"abstract":"<div><div>This study aims to identify distinct profiles of AI acceptance among pre-service teachers. Latent profile analysis and ANOVAs were conducted to determine whether homogeneous latent profiles exist within a sample of 453 pre-service teachers in China. Our findings revealed four different profiles: High Acceptors (19.21 %), Cautious Supporters (54.30 %), Skeptics (16.56 %), and Pragmatic Adopters (9.93 %). Additionally, the findings indicate that all groups express concern about AI-related technological factors. More specifically, the results point out the importance of AI compatibility and factors related to digital literacy in shaping AI acceptance among pre-service teachers across different groups.</div></div>","PeriodicalId":48430,"journal":{"name":"Teaching and Teacher Education","volume":"163 ","pages":"Article 105086"},"PeriodicalIF":4.0000,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A profile analysis of pre-service teachers’ AI acceptance: Combining behavioral, technological, and human factors\",\"authors\":\"Chengming Zhang , Min Hu , Weidong Wu , Yanfen Chen , Farrukh Kamran , Xining Wang\",\"doi\":\"10.1016/j.tate.2025.105086\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study aims to identify distinct profiles of AI acceptance among pre-service teachers. Latent profile analysis and ANOVAs were conducted to determine whether homogeneous latent profiles exist within a sample of 453 pre-service teachers in China. Our findings revealed four different profiles: High Acceptors (19.21 %), Cautious Supporters (54.30 %), Skeptics (16.56 %), and Pragmatic Adopters (9.93 %). Additionally, the findings indicate that all groups express concern about AI-related technological factors. More specifically, the results point out the importance of AI compatibility and factors related to digital literacy in shaping AI acceptance among pre-service teachers across different groups.</div></div>\",\"PeriodicalId\":48430,\"journal\":{\"name\":\"Teaching and Teacher Education\",\"volume\":\"163 \",\"pages\":\"Article 105086\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2025-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Teaching and Teacher Education\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0742051X25001635\",\"RegionNum\":1,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Teaching and Teacher Education","FirstCategoryId":"95","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0742051X25001635","RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
A profile analysis of pre-service teachers’ AI acceptance: Combining behavioral, technological, and human factors
This study aims to identify distinct profiles of AI acceptance among pre-service teachers. Latent profile analysis and ANOVAs were conducted to determine whether homogeneous latent profiles exist within a sample of 453 pre-service teachers in China. Our findings revealed four different profiles: High Acceptors (19.21 %), Cautious Supporters (54.30 %), Skeptics (16.56 %), and Pragmatic Adopters (9.93 %). Additionally, the findings indicate that all groups express concern about AI-related technological factors. More specifically, the results point out the importance of AI compatibility and factors related to digital literacy in shaping AI acceptance among pre-service teachers across different groups.
期刊介绍:
Teaching and Teacher Education is an international journal concerned primarily with teachers, teaching, and/or teacher education situated in an international perspective and context. The journal focuses on early childhood through high school (secondary education), teacher preparation, along with higher education concerning teacher professional development and/or teacher education. Teaching and Teacher Education is a multidisciplinary journal committed to no single approach, discipline, methodology, or paradigm. The journal welcomes varied approaches (qualitative, quantitative, and mixed methods) to empirical research; also publishing high quality systematic reviews and meta-analyses. Manuscripts should enhance, build upon, and/or extend the boundaries of theory, research, and/or practice in teaching and teacher education. Teaching and Teacher Education does not publish unsolicited Book Reviews.