Research graph
References from Recurrent and system-specific model-attribution patterns in PISA 2022 science performance across nine education systems. Local targets link to admitted publications; unresolved targets remain external evidence.
PISA 2022 results (volume I): the state of learning and equity in education
2023 · External reference
PISA 2022 technical report
2024 · External reference
PISA 2022 Results (Volume V): Learning Strategies and Attitudes for Life
2024 · External reference
Salvaging science literacy
2011 · External reference
Assessing the hypothesis of measurement invariance in the context of large-scale international surveys
10.1177/0013164413498257 · 2014 · External reference
Predicting science achievement scores with machine learning algorithms: a case study of OECD PISA 2015–2018 data
10.1007/s00521-023-08901-6 · 2023 · External reference
Stacking: an ensemble learning approach to predict student performance in PISA 2022
10.1007/s10639-024-13110-2 · 2025 · External reference
Applying a Support Vector Machine (SVM-RFE) Learning Approach to Investigate Students’ Scientific Literacy Development: Evidence from Asia, Europe, and South America
10.3390/jintelligence12110111 · 2024 · External reference
Uncovering student profiles. An explainable cluster analysis approach to PISA 2022
10.1016/j.compedu.2024.105166 · 2024 · External reference
Applying Machine Learning and SHAP Method to Identify Key Influences on Middle-School Students’ Mathematics Literacy Performance
10.3390/jintelligence12100093 · 2024 · External reference
Explainable artificial intelligence in education
2022 · External reference
Factors influencing secondary school students’ reading literacy: An analysis based on XGBoost and SHAP methods
10.3389/fpsyg.2022.948612 · 2022 · External reference
From Local Explanations to Global Understanding with Explainable AI for Trees
10.1038/s42256-019-0138-9 · 2020 · External reference
Considerations for the use of plausible values in large-scale assessments
10.1186/s40536-024-00213-y · 2024 · External reference
Large-scale assessments for learning: a human-centred AI approach to contextualizing test performance
10.18608/jla.2024.8007 · 2024 · External reference
Evaluating uncertainty: the impact of the sampling and assessment design on statistical inference in the context of ILSA
10.1186/s40536-025-00246-x · 2025 · External reference
Correction: evaluating uncertainty: the impact of the sampling and assessment design
2025 · External reference
Controlling the false discovery rate: a practical and powerful approach to multiple testing
10.1111/j.2517-6161.1995.tb02031.x · 1995 · External reference
Random Forests
10.1023/a:1010933404324 · 2001 · External reference
A comparative analysis of gradient boosting algorithms
10.1007/s10462-020-09896-5 · 2021 · External reference
A tutorial on support vector regression
10.1023/b:stco.0000035301.49549.88 · 2004 · External reference
The measure of socio-economic status in PISA: a review and some suggested improvements
10.1186/s40536-020-00086-x · 2020 · External reference
Socioeconomic status and academic achievement: a meta-analytic review of research
10.3102/00346543075003417 · 2005 · External reference
Role of self-efficacy and self-concept beliefs in mathematical problem solving: a path analysis
10.1037/0022-0663.86.2.193 · 1994 · External reference
The influence of academic self-efficacy on academic performance: A systematic review
10.1016/j.edurev.2015.11.002 · 2016 · External reference
Factors predicting mathematics achievement in PISA: a systematic review
2023 · External reference
Family scholarly culture and educational success: Books and schooling in 27 nations
2010 · External reference
Scholarly culture: How books in adolescence enhance adult literacy, numeracy and technology skills in 31 societies
10.1016/j.ssresearch.2018.10.003 · 2019 · External reference
Predicting science achievement scores with machine learning algorithms: a case study of OECD PISA 2015–2018 data
10.1007/s00521-023-08901-6 · ExternalCitation · doi-reference
A comparative analysis of gradient boosting algorithms
10.1007/s10462-020-09896-5 · ExternalCitation · doi-reference
Stacking: an ensemble learning approach to predict student performance in PISA 2022
10.1007/s10639-024-13110-2 · ExternalCitation · doi-reference
Uncovering student profiles. An explainable cluster analysis approach to PISA 2022
10.1016/j.compedu.2024.105166 · ExternalCitation · doi-reference
The influence of academic self-efficacy on academic performance: A systematic review
10.1016/j.edurev.2015.11.002 · ExternalCitation · doi-reference
Scholarly culture: How books in adolescence enhance adult literacy, numeracy and technology skills in 31 societies
10.1016/j.ssresearch.2018.10.003 · ExternalCitation · doi-reference
Random Forests
10.1023/a:1010933404324 · ExternalCitation · doi-reference
A tutorial on support vector regression
10.1023/b:stco.0000035301.49549.88 · ExternalCitation · doi-reference
Role of self-efficacy and self-concept beliefs in mathematical problem solving: a path analysis
10.1037/0022-0663.86.2.193 · ExternalCitation · doi-reference
From Local Explanations to Global Understanding with Explainable AI for Trees
10.1038/s42256-019-0138-9 · ExternalCitation · doi-reference
Controlling the false discovery rate: a practical and powerful approach to multiple testing
10.1111/j.2517-6161.1995.tb02031.x · ExternalCitation · doi-reference
Assessing the hypothesis of measurement invariance in the context of large-scale international surveys
10.1177/0013164413498257 · ExternalCitation · doi-reference
The measure of socio-economic status in PISA: a review and some suggested improvements
10.1186/s40536-020-00086-x · ExternalCitation · doi-reference
Considerations for the use of plausible values in large-scale assessments
10.1186/s40536-024-00213-y · ExternalCitation · doi-reference
Evaluating uncertainty: the impact of the sampling and assessment design on statistical inference in the context of ILSA
10.1186/s40536-025-00246-x · ExternalCitation · doi-reference
Large-scale assessments for learning: a human-centred AI approach to contextualizing test performance
10.18608/jla.2024.8007 · ExternalCitation · doi-reference
Socioeconomic status and academic achievement: a meta-analytic review of research
10.3102/00346543075003417 · ExternalCitation · doi-reference
Factors influencing secondary school students’ reading literacy: An analysis based on XGBoost and SHAP methods
10.3389/fpsyg.2022.948612 · ExternalCitation · doi-reference
Applying Machine Learning and SHAP Method to Identify Key Influences on Middle-School Students’ Mathematics Literacy Performance
10.3390/jintelligence12100093 · ExternalCitation · doi-reference
Applying a Support Vector Machine (SVM-RFE) Learning Approach to Investigate Students’ Scientific Literacy Development: Evidence from Asia, Europe, and South America
10.3390/jintelligence12110111 · ExternalCitation · doi-reference
