This study investigated the relationships between a professional learning community (PLC), faculty trust in colleagues, teachers’ collective efficacy, and their commitment to students. The findings from exploratory factor analysis indicated that three clear components could be extracted from the scale of Professional Learning Communities Assessment (PLCA) in a Chinese setting. Multilevel analyses was conducted to investigate how school-level variables, including the three factors of PLC, faculty trust in colleagues, and collective teacher efficacy, affect teachers’ commitment to students. The findings from the Hong Kong teacher sample indicated that two PLC factors including collective learning and application and supportive conditions – structures, and the factors faculty trust in colleagues and collective teacher efficacy could significantly and positively account for the school-level variances of teachers’ commitment to students. Another PLC factor, shared and supportive leadership, was not identified as a significant predictor to teachers’ commitment to students in a Chinese setting. The findings of school-level regressions indicated that all three factors of PLC as well as faculty trust in colleagues could significantly and positively affect teachers’ collective efficacy on instructional strategies. However, only one PLC factor, collective learning and application, and the factor faculty trust in colleagues were significant predictors to teachers’ collective efficacy on student discipline. Copyright © 2011 Elsevier Ltd.
|Journal||Teaching and Teacher Education|
|Publication status||Published - Jul 2011|
CitationLee, J. C.-k., Zhang, Z., & Yin, H. (2011). A multilevel analysis of the impact of a professional learning community, faculty trust in colleagues and collective efficacy on teacher commitment to students. Teaching and Teacher Education, 27(5), 820-830.
- Teacher development
- Professional learning community
- Faculty trust in colleagues
- Collective teacher efficacy
- Teacher commitment to students
- Hierarchical linear model