Dataset supporting the thesis: Pupil competence during the COVID-19-induced school closures: An analysis of the effect of distance learning and remediation policies using international assessment data in 30 countries
Dataset supporting the thesis: Pupil competence during the COVID-19-induced school closures: An analysis of the effect of distance learning and remediation policies using international assessment data in 30 countries
This dataset accompanies the PhD thesis Pupil Competence During the COVID-19-induced School Closures: An Analysis of the Effect of Distance Learning and Remediation Policies Using International Assessment Data in 30 Countries. The dataset compiles country-level data derived from large-scale international student assessments, specifically PISA and PIRLS, covering the period 2000–2022. It was created by harmonising publicly available microdata from the OECD (for PISA) and IEA (for PIRLS), aggregated to the national level. The data were collected and processed using StataNow 18.5. The dataset can be opened in StataNow 18.5 software. Stata .do files are also provided to allow full reproducibility of the data preparation and analysis. The dataset is specifically structured to support advanced statistical modelling, including Latent Growth Curve Modelling (LGCM), Synthetic Control (SC), and Synthetic Difference-in-Differences (SDID), to examine the effects of COVID-19 policies on pupil competence across diverse national contexts.
Date Request Form: https://library.soton.ac.uk/datarequest
University of Southampton
Wang, Yin
d2b62b39-cf7e-49ed-9405-88f0f2a0dc63
Wang, Yin
d2b62b39-cf7e-49ed-9405-88f0f2a0dc63
Wang, Yin
(2025)
Dataset supporting the thesis: Pupil competence during the COVID-19-induced school closures: An analysis of the effect of distance learning and remediation policies using international assessment data in 30 countries.
University of Southampton
doi:10.5258/SOTON/D3644
[Dataset]
Abstract
This dataset accompanies the PhD thesis Pupil Competence During the COVID-19-induced School Closures: An Analysis of the Effect of Distance Learning and Remediation Policies Using International Assessment Data in 30 Countries. The dataset compiles country-level data derived from large-scale international student assessments, specifically PISA and PIRLS, covering the period 2000–2022. It was created by harmonising publicly available microdata from the OECD (for PISA) and IEA (for PIRLS), aggregated to the national level. The data were collected and processed using StataNow 18.5. The dataset can be opened in StataNow 18.5 software. Stata .do files are also provided to allow full reproducibility of the data preparation and analysis. The dataset is specifically structured to support advanced statistical modelling, including Latent Growth Curve Modelling (LGCM), Synthetic Control (SC), and Synthetic Difference-in-Differences (SDID), to examine the effects of COVID-19 policies on pupil competence across diverse national contexts.
Date Request Form: https://library.soton.ac.uk/datarequest
Text
Access_Request_Form_D3644.docx
- Dataset
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Published date: 2025
Identifiers
Local EPrints ID: 504264
URI: http://eprints.soton.ac.uk/id/eprint/504264
PURE UUID: 640e770a-fb56-440a-9442-6e543c13156e
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Date deposited: 02 Sep 2025 16:53
Last modified: 03 Sep 2025 02:06
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Creator:
Yin Wang
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