ERIC Number: EJ1410333
Record Type: Journal
Publication Date: 2024
Pages: 36
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-2196-0739
A Bayesian Workflow for the Analysis and Reporting of International Large-Scale Assessments: A Case Study Using the OECD Teaching and Learning International Survey
Large-scale Assessments in Education, v12 Article 2 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 methodological framework for the analysis of educational data generally, and large-scale assessments more specifically. The paper argues that Bayesian statistical methods can provide a more nuanced analysis of results of policy relevance compared to standard frequentist approaches commonly found in large-scale assessment reports. The data utilized for this paper comes from the Teaching and Learning International Survey (TALIS). The paper provides steps in implementing a Bayesian analysis and proposes a workflow that can be applied not only to TALIS but to large-scale assessments in general. The paper closes with a discussion of other Bayesian approaches to international large-scale assessment data, in particularly for predictive modeling.
Descriptors: Bayesian Statistics, Administrator Surveys, Teacher Surveys, Measurement, Prediction, Statistical Inference, Teacher Attitudes, Teaching Methods
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://bibliotheek.ehb.be:2123/
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Teaching and Learning International Survey
Grant or Contract Numbers: N/A
Data File: URL: https://bmer.wceruw.org/index.html