School Environments, Track Placement, and Achievement Gains: Identifying the Drivers of the Academic Track Advantage in Italy

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Abstract Educational tracking shapes students’ learning opportunities, yet isolating its effects from prior selection remains a key challenge in large-scale assessment research. This study examines both the size and the mechanisms of academic-track advantages by integrating longitudinal population-level administrative data from INVALSI with school- and student-level indicators from PISA 2018 in Italy. Focusing on scientific lyceums versus technical schools, we exploit rich pre-tracking information on achievement, socio-demographic background, and early attitudes, and apply an estimand-based framework using entropy balancing to adjust for selection into tracks. Results show that achievement gaps at Grade 10 are large across domains, but substantially reduced once differences in prior competencies and backgrounds are accounted for. Nonetheless, a meaningful academic-track advantage persists after balancing. Decomposition analyses indicate that this residual gap is largely explained by differences in school environments, particularly school climate and organisational policies, while instructional practices contribute little on average. The findings support a dual interpretation of tracking effects, combining cumulative selection and exposure to differentiated learning contexts, and highlight the value of linking administrative panels with international assessment data to study both outcomes and mechanisms of educational stratification.
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School Environments, Track Placement, and Achievement Gains: Identifying the Drivers of the Academic Track Advantage in Italy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article School Environments, Track Placement, and Achievement Gains: Identifying the Drivers of the Academic Track Advantage in Italy Elisa Sbalchiero, Francesco Balzaretti, Emanuele Fedeli, Moris Triventi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8750598/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Educational tracking shapes students’ learning opportunities, yet isolating its effects from prior selection remains a key challenge in large-scale assessment research. This study examines both the size and the mechanisms of academic-track advantages by integrating longitudinal population-level administrative data from INVALSI with school- and student-level indicators from PISA 2018 in Italy. Focusing on scientific lyceums versus technical schools, we exploit rich pre-tracking information on achievement, socio-demographic background, and early attitudes, and apply an estimand-based framework using entropy balancing to adjust for selection into tracks. Results show that achievement gaps at Grade 10 are large across domains, but substantially reduced once differences in prior competencies and backgrounds are accounted for. Nonetheless, a meaningful academic-track advantage persists after balancing. Decomposition analyses indicate that this residual gap is largely explained by differences in school environments, particularly school climate and organisational policies, while instructional practices contribute little on average. The findings support a dual interpretation of tracking effects, combining cumulative selection and exposure to differentiated learning contexts, and highlight the value of linking administrative panels with international assessment data to study both outcomes and mechanisms of educational stratification. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Full Text Additional Declarations No competing interests reported. Table 1 and 2 are available in the Supplementary Files section. Supplementary Files Table1and2.docx AppendixCopy.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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