Distinguishing Subtypes of Self-Efficacy Among Secondary School Teachers : A Latent Profile Analysis

Jing HUANG*, Youliang ZHANG, Alex Yue Feng ZHU, Yang (Frank) GONG, Ho Man Raymond KONG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

Abstract

Teacher self-efficacy is a crucial factor in teaching and learning, yet there is limited understanding of its heterogeneity among the Asian population. Therefore, the objectives of this study were to (a) identify different self-efficacy patterns among 3,095 Singaporean lower secondary school teachers, (b) investigate potential variations in job satisfaction, constructivist beliefs, and teacher co-operation across different self-efficacy profiles, and (c) examine the predictions of teacher background characteristics in relation to profile membership. By employing latent profile analysis, four distinct self-efficacy profiles were identified: (a) Low Self-Efficacy, (b) Moderate Self-Efficacy, (c) High Self-Efficacy, and (d) Divergent Moderate Self-Efficacy. The results also revealed significant differences in job satisfaction, constructivist beliefs, and teacher co-operation among the self-efficacy profiles. Moreover, teaching experience emerged as a significant predictor of profile membership. These highlight the need for tailored professional development programs and interventions that consider teachers’ self-efficacy profiles, teacher outcomes, and teaching experience.
Original languageEnglish
JournalJournal of Teacher Education
Early online date11 Mar 2024
DOIs
Publication statusE-pub ahead of print - 11 Mar 2024

Bibliographical note

I would like to express my gratitude to Professor Joshua Mok Ka-ho, the editors, and anonymous reviewers for their valuable comments on an earlier draft of this article.

Publisher Copyright:
© 2024 American Association of Colleges for Teacher Education.

Keywords

  • teacher self-efficacy
  • job satisfaction
  • constructivist beliefs
  • teacher co-operation
  • teaching experience
  • latent profile analysis

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