Student and school performance across countries: A machine learning approach
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DOI: 10.1016/j.ejor.2018.02.031
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- Víctor Giménez & Claudio Thieme & Diego Prior & Emili Tortosa-Ausina, 2020. "Evaluation and determinants of pre-school effectiveness in Chile," Working Papers 2020/02, Economics Department, Universitat Jaume I, Castellón (Spain).
- Selin ERDOĞAN & Hüseyin TAŞTAN, 2024. "Predicting Student Achievement via Machine Learning: Evidence from Turkish Subset of PISA," Yildiz Social Science Review, Yildiz Technical University, vol. 10(1), pages 7-27.
- Antonella D’Agostino & Francesco Schirripa Spagnolo & Nicola Salvati, 2022. "Studying the relationship between anxiety and school achievement: evidence from PISA data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 1-20, March.
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- Camanho, Ana S. & Varriale, Luisa & Barbosa, Flávia & Sobral, Thiago, 2021. "Performance assessment of upper secondary schools in Italian regions using a circular pseudo-Malmquist index," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1188-1208.
- Alice Bertoletti & Marta Cannistrà & Melisa Diaz Lema & Chiara Masci & Anna Mergoni & Lidia Rossi & Mara Soncin, 2023. "The Determinants of Mathematics Achievement: A Gender Perspective Using Multilevel Random Forest," Economies, MDPI, vol. 11(2), pages 1-20, January.
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Keywords
Education; Multilevel model; School value-added; Regression trees; Boosting;All these keywords.
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