Predicting teachers’ sense of efficacy: A multimodal analysis integrating SEM, deep learning, and ANN

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dc.authorid0000-0001-6513-4569en_US
dc.authorid0000-0002-2867-9583en_US
dc.authorid0000-0001-8395-2020en_US
dc.authorid0000-0002-1833-9286en_US
dc.contributor.authorArpacı, İbrahim
dc.contributor.authorKarataş, Kasım
dc.contributor.authorGün, Feyza
dc.contributor.authorSüer, Sedef
dc.date.accessioned2024-08-14T11:06:17Z
dc.date.available2024-08-14T11:06:17Z
dc.date.issued2024en_US
dc.departmentDicle Üniversitesi, Ziya Gökalp Eğitim Fakültesi, Eğitim Bilimlerien_US
dc.description.abstractThis study aims to investigate the predictive role of cultural intelligence, motivation to teach, and “culturally responsive classroom management self-efficacy” (CRCMSE) in teachers’ sense of efficacy. The study utilized a combination of “structural equation modeling” (SEM), deep learning, and “artificial neural network” (ANN) to analyze data collected from 1061 preservice teachers. The SEM analysis indicated that cultural intelligence, motivation to teach, and CRCMSE significantly predicted the sense of efficacy of the teacher candidates, accounting for 59% of the variance. Additionally, the ANN model accurately predicted the teachers’ sense of efficacy with 75.71% and 75.17% accuracy for training and testing, respectively. The sensitivity analysis revealed that CRCMSE played the most crucial role in predicting the preservice teachers’ sense of efficacy. The deep learning model also predicted the sense of efficacy with an overall accuracy of 74.18%. The utilization of a multimodal analysis approach facilitated the identification of both linear and nonlinear relationships between the constructs.en_US
dc.identifier.citationArpacı, İ., Karataş, K., Gün, F. ve Süer, S. (2024). Predicting teachers’ sense of efficacy: A multimodal analysis integrating SEM, deep learning, and ANN. Psychology in the Schools, 61(8), 3373-3389.en_US
dc.identifier.endpage3389en_US
dc.identifier.issn0033-3085
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-85192218518
dc.identifier.scopusqualityQ2
dc.identifier.startpage3373en_US
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/10.1002/pits.23222
dc.identifier.urihttps://hdl.handle.net/11468/28733
dc.identifier.volume61en_US
dc.identifier.wosWOS:001217228600001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorSüer, Sedef
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Inc.en_US
dc.relation.ispartofPsychology in the Schools
dc.relation.isversionof10.1002/pits.23222en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassroom managementen_US
dc.subjectCultural intelligenceen_US
dc.subjectMotivation to teachen_US
dc.subjectSelf-efficacyen_US
dc.titlePredicting teachers’ sense of efficacy: A multimodal analysis integrating SEM, deep learning, and ANNen_US
dc.titlePredicting teachers’ sense of efficacy: A multimodal analysis integrating SEM, deep learning, and ANN
dc.typeArticleen_US

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