Exploring Iranian collective teacher efficacy beliefs in different ELT settings through developing a context–specific English language teacher collective efficacy scale

Clicks: 356
ID: 53741
2018
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
To capture the unique nature of collective teacher efficacy as reflected in ELT settings, the current study attempted to develop and validate a context-specific collective efficacy scale and use it in exploring collective efficacy beliefs in different ELT contexts. To achieve this goal, guided by the related literature, the most prominent constituent elements of collective teacher efficacy were identified through a series of semistructured interviews with English language teachers and instructors in educational contexts of school, institute, and university. Based on the seven-component initial model obtained from qualitative content analysis, a 32-item questionnaire was developed and tried on 405 EFL teachers and instructors. The data were then subjected to exploratory factor analysis. The proposed model consisted of 21 items encompassing four factors. The results of the confirmatory factor analysis indicated that the scale showed indices of construct validity and suitably fit the proposed collective efficacy model. Applying a one-way ANOVA also revealed that the three educational contexts differed significantly with respect to English teacher collective efficacy beliefs. English language institute teachers displayed the highest collective efficacy level while university instructors showed the lowest level. A significant difference existed between institute and high school teachers and university instructors.
Reference Key
abedini2018exploringcogent Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Abedini, Farahnaz;Bagheri, Mohammad Sadegh;Sadighi, Firooz;
Journal cogent education
Year 2018
DOI
DOI not found
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.