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A Bayesian Workflow for the Analysis and Reporting of International Large-Scale Assessments: A Case Study Using the OECD Teaching and Learning International Survey
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David Kaplan; Kjorte Harra – Large-scale Assessments in Education, 2024
This paper aims to showcase the value of implementing a Bayesian framework to analyze and report results from international large-scale assessments and provide guidance to users who want to analyse ILSA data using this approach. The motivation for this paper stems from the recognition that Bayesian statistical inference is fast becoming a popular…
Descriptors: Bayesian Statistics, Administrator Surveys, Teacher Surveys, Measurement
A Bayesian Workflow for the Analysis and Reporting of International Large-Scale Surveys: A Case Study Using the OECD Teaching and Learning International Survey. OECD Education Working Papers No. 291
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David Kaplan; Kjorte Harra – OECD Publishing, 2023
This report aims to showcase the value of implementing a Bayesian framework to analyse and report results from international large-scale surveys and provide guidance to users who want to analyse the data using this approach. The motivation for this report stems from the recognition that Bayesian statistical inference is fast becoming a popular…
Descriptors: Bayesian Statistics, Statistical Inference, Data Analysis, Educational Research
Factors Affecting Teacher Job Satisfaction: A Causal Inference Machine Learning Approach Using Data from TALIS 2018
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Nathan McJames; Andrew Parnell; Ann O'Shea – Educational Review, 2025
Teacher shortages and attrition are problems of international concern. One of the most frequent reasons for teachers leaving the profession is a lack of job satisfaction. Accordingly, in this study we have adopted a causal inference machine learning approach to identify practical interventions for improving overall levels of job satisfaction. We…
Descriptors: Job Satisfaction, Teacher Surveys, Administrator Surveys, Faculty Mobility