Factors affecting teacher job satisfaction: a causal inference machine learning approach using data from TALIS 2018-Reference-Cited by-同舟云学术

Factors affecting teacher job satisfaction: a causal inference machine learning approach using data from TALIS 2018

Published:2023-05-12 Issue: Volume: Page:1-25
ISSN:0013-1911
Container-title:Educational Review
language:en
Short-container-title:Educational Review

Author:

McJames Nathan¹²^ORCID,Parnell Andrew¹²,O’Shea Ann²

Affiliation:

1. Hamilton Institute, Maynooth University, Maynooth, Ireland

2. Department of Mathematics and Statistics, Maynooth University, Maynooth, Ireland

Funder

Science Foundation Ireland

SFI Research Centre

Publisher

Informa UK Limited

Subject

Education

Link

https://www.tandfonline.com/doi/pdf/10.1080/00131911.2023.2200594

Reference79 articles.

1. Allen, M. B. (2005). Eight questions on teacher recruitment and retention: What does the research say? Education Commission of the States (NJ3).

2. Allen, R. & Sims, S. (2017). Improving science teacher retention: Do national STEM learning network professional development courses keep science teachers in the classroom. Education Research in STEM Subjects: Main Collection.

3. Why Didst Thou Go? Predictors of Retention, Transfer, and Attrition of Special and General Education Teachers from a National Perspective

4. Job satisfaction predicts teacher self-efficacy and the association is invariant: Examinations using TALIS 2018 data and longitudinal Croatian data

5. Mental health in teachers: Relationships with job satisfaction, efficacy beliefs, burnout and depression

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