Data for the Paper titled "Beyond Rankings: A Multidimensional Analysis of Factors Shaping Student Achievement in the PISA 2022 Dataset"

The Programme for International Student Assessment (PISA) 2022 included approximately 690,000 students from 81 countries and economies, representing an estimated 29 million students worldwide. As in previous cycles, the assessments focused on three core subjects: reading, mathematics, and science. The primary data used in this dataset is sourced from the PISA 2022 assessment.

In the PISA 2022 dataset, individual student scores for mathematics, reading, and science are not directly reported as fixed values. Instead, the dataset provides ten plausible values for each subject. These plausible values are derived using advanced statistical techniques that aim to estimate the range of possible outcomes for a student’s performance, acknowledging the inherent uncertainty and complexity associated with large-scale international assessments. To facilitate analysis, a single representative score for each student in each subject was calculated by taking the arithmetic mean of the ten plausible values. This process provides a straightforward and interpretable estimate of each student’s performance. However, it is important to note that plausible values are intended to reflect a range of possibilities rather than a definitive score, emphasizing the probabilistic nature of the results. This method is consistent with established practices in analysing PISA data and ensures uniformity in reporting and interpretation.

To enhance the analysis, new variables were created based on the dataset, and some variables were modified to include them in the study. The dataset comprises 78 variables in total. Among these, 3 are used as dependent variables to measure student performance, and 48 are used as independent variables representing diverse factors grouped into six models. The first group of variables pertains to the home environment, including 9 variables. The second group focuses on students’ perceptions of school and includes 8 variables. The third group examines characteristics of schools and contains 12 variables. The fourth group addresses socioeconomic features of schools and consists of 6 variables. The fifth group pertains to teacher-related factors, encompassing 7 variables. The final group considers homework and additional instruction, comprising 6 variables.

In addition to these variables, five control variables were incorporated into each model. The first two control variables are gender and membership in the OECD, represented as dummy variables obtained from the PISA 2022 dataset. The other three control variables capture national political and economic characteristics that may influence student achievement. These include the Freedom in the World Index for 2024, GDP per capita at purchasing power parity rates for 2022 (measured in current international 1000 dollars), and the Government Effectiveness Index for 2023. Data for these variables were sourced from FreedomHouse and WorldBank.