The role of teacher selection criteria and preparation on teacher self-efficacy, satisfaction, and commitment: an analysis of Kazakhstani TALIS data

2023

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DOI 10.1080/13664530.2023.2176354
Data confidence 85 high
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Abstract

In Kazakhstan, an increasing school student population, low rates of graduates entering the profession, and high novice teacher attrition have made the attraction and retention of quality teachers a critical issue. To investigate this problem, the authors draw on the 2018 TALIS dataset involving a survey of 5201 Kazakhstani teachers from 275 participating schools. The study, framed by Chapman’s teacher attrition model, uses a nested data design. As an outcome variable, the authors make use of a corollary of attrition, the self-reported career commitment variable in the Kazakhstani TALIS dataset. The analysis suggests that teachers who enter the profession with enhanced altruistic tendencies have improved self-efficacy and job satisfaction. Further, teaching-as-a-first-career-choice appears to drive both job satisfaction and career commitment, while learning to manage behaviour and mixed-ability settings also appears to drive improved long-term career commitment. Implications for teacher education and research in other Central Asian and post-Soviet countries are offered.