Benchmarking the international compulsory education performance of 65 countries and economies: Findings from PISA 2006, 2009, and 2012
Henry H. Bi. 2018. Benchmarking the international compulsory education performance of 65 countries and economies: Findings from PISA 2006, 2009, and 2012. Benchmarking: An International Journal (1463-5771). 25(1): 98-119. DOI: 10.1108/BIJ-09-2016-0144
23 Pages Posted: 5 Dec 2016 Last revised: 26 Apr 2019
Date Written: December 2, 2016
Purpose: The Programme for International Student Assessment (PISA) measured 15-year-olds’ performance in mathematics, reading, and science. This paper aims to use the assessment results of PISA 2006, 2009, and 2012 to benchmark the compulsory education performance of 65 countries and economies with emphasis on two benchmarking steps: identifying benchmarks and determining performance gaps.
Design/methodology/approach: We use a multi-criterion and multi-period performance categorization method to identify a group of best performers as benchmarks. Then we use two-sample t-tests to detect against benchmarks whether each country or economy has significant performance gaps on individual performance measures.
Findings: Based on the mean scores of three assessment subjects in PISA 2006, 2009, and 2012, six best performers (Top-6) are identified from 65 participating countries and economies. In comparison with Top-6’s weighted averages, performance gaps are found for most countries and economies on the mean score of each subject, the percentage of top-performing students in all three subjects, and the percentage of lowest-performing students in each subject.
Originality/value: For compulsory education systems around the world, this paper provides an original categorization of performance based on the results of three PISA cycles, and provides new insights for countries and economies to prioritize improvement efforts to increase average performance, pursue excellence, and tackle low performance. For benchmarking applications involving multi-criterion and multi-period data, this paper presents a novel method of using statistical control charts to identify benchmarks and then using two-sample t-tests to determine performance gaps on individual performance measures.
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