Selected Factors Contributing to Teacher Job Satisfaction: A Quantitative Investigation Using 2013 TALIS Data

ABSTRACT

This study aims to analyze how selected student and school factors may affect teacher job satisfaction, in addition to teacher factors, through multilevel regression and commonality analysis of U.S. data from the Teaching and Learning International Survey (TALIS) 2013. In the overall model of teacher job satisfaction, the factors of low achievers, behavioral problems, SES, classroom discipline climate, school location, principal job satisfaction, school autonomy for instruction, participation among stakeholders, experience, teacher self-efficacy, teacher-student relationship, teacher cooperation, and effective professional development are important predictors for teacher job satisfaction based on the values of beta weights and structure coefficients. Furthermore, the commonality analysis reveals that student, school, and teacher factors uniquely contribute 4.19%, 7.07%, and 6.41% of variance, respectively. Findings provide significant implications for educational policies on teacher job satisfaction and retention.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The minimum school participation rate in TALIS was set at 75% after replacement. Responding schools that reached at least 50% of responding teachers were considered to be “participating” schools. The U.S. response rate in 2013 was 37% of original schools (before substitution; weighted) and 61% after substitution (weighted). Based on the international standards, the United States did not achieve an acceptable level of response. (OECD [Organization for Economic Cooperation and Development], 2014b).

2. The TALIS program uses questionnaires containing single items that are combined (reduced) to form scales to measure teachers’ beliefs, attitudes, and practices and principals’ leadership styles. The basic advantage of developing scales is that each combines items covering the different characteristics of the items that make up the scale of interest, so providing measures of higher reliability and validity than single items. Another advantage is that they can alleviate issues of multicollinearity in models.

Additional information

Funding

This work was supported in part by the National Social Science Fund of China under Grant No. BHA180134 and Young Scholar Fund of Humanities & Social Science of Chinese Ministry of Education under Grant No. 18YJC880115.