ABSTRACT
Teacher collaboration (TC) is an effective means of enhancing teachers’ psychological factors towards their jobs. Yet research on the extent to which the personal and structural characteristics and their synergistic effects of collaboration on teachers’ psychological factors remain ambiguous. This study examines the effects of TC on multidimensional measures of teacher satisfaction and self-efficacy. The study also explores the moderated effects of personal and structural characteristics on the relationship of TC with job satisfaction and self-efficacy. The study employed latent moderated structural equation modelling on the Korean portion of the Programme of International Study Assessment 2018 data. The results show that TC positively predicted all job satisfaction and self-efficacy dimensions. However, not all personal and structural factors predicted job satisfaction and self-efficacy subscales. Gender had a moderating effect on the relationship between TC and job satisfaction. Additionally, participation in professional learning communities moderated the relationship between TC and work environment.
Disclosure statement
We have no known conflict of interest to disclosure. This work does not receive any financial support.
Additional information
Notes on contributors
Jaehong Jang
Jaehong Jang received his doctoral degree in Educational Technology from Korea University. He has been an elementary school teacher since 2011. His major research interests include teacher education, teaching and learning methods, and longitudinal studies.
Hawon Yoo
Hawon Yoo is currently a Ph.D. candidate in Educational Technology in the Department of Education at Korea University. Her major research interests include adaptive learning systems design and development and technology-integrated instructional design.
Pey-Yan Liou
Pey-Yan Liou is a Professor in the Department of Education at Korea University. Her research agenda has focused on examining the contribution of multiple psychological constructs to people’s behaviours and intentions using international large-scale assessment datasets.