[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118536-en":3,"doc-seo-118536-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118536,962075114101,"Seraphina","https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165",8,"Research & Report","The efficiency of Italian lower secondary schools - combination of DEA with a graphical machine learning approach","Machine learning methods are used to improve on classical regression approaches for detecting nonlinear relationships and interaction effects behind the efficiency of educational systems. Efficiency scores for 4,264 Italian public lower secondary schools are estimated via Data Envelopment Analysis (DEA) with a double bootstrap procedure, while Random Forest identifies variables linked to higher scores and visualizes their effects in an interpretable form. Results verify regional efficiency differences, with schools in the South and islands underperforming. Key drivers include school size, class size, and the share of immigrant students; interactions extend relevance to head experience, teacher absence days, and salary-related funding shares. Policy implications conclude the study.","The efficiency of Italian lower secondary schools: combination of DEA with a graphical machine learning approach  \nTESI DI LAUREA MAGISTRALE IN MANAGEMENT ENGINEERING  \nAuthor: Luigi Iorio  \nStudent ID: 10794393  \nAdvisor: Prof. Tommaso Agasisti  \nCo-advisor: Prof. Mara Soncin  \nAcademic Year: 2022-23  \nAi miei genitori:  \nMariarosaria e Raffaele  \nAlla mia famiglia:  \nRita, Ivan, Asia e i Nonni  \nAbstract  \nThis study illustrates the ability of Machine Learning approaches to overcome classical regression techniques in identifying nonlinear relationships and interaction effects of factors influencing the efficiency of educational systems. The efficiency scores of 4264 Italian public lower secondary schools are computed by using Data Envelopment Analysis (DEA) with a double bootstrap procedure, while Random Forest is adopted to identify the variables that are associated with higher scores and visualise their effects in an easily interpretable way. The results confirm the differences in efficiency assessed in previous studies between schools located in different areas of the country, with schools in the South and the islands performing worse than the others. School size, class size and the percentage of immigrant students are the most important factors influencing efficiency. Evaluating interaction effects, it is also possible to consider in the assessment of efficiency the years of experience of the school head, the days of absence of teachers (not due to illness or maternity) and the percentage of funds allocated to pay salaries. Policy implications are presented in the last part of the study.  \nKeywords: school efficiency, data envelopment analysis, machine learning, random forest  \nAbstract in lingua italiana  \nQuesto studio illustra la capacità degli approcci di Machine Learning di superare le classiche tecniche di regressione nell'identificare relazioni non lineari ed effetti di interazione dei fattori che influenzano l'efficienza dei sistemi educativi. I punteggi di efficienza di 4264 scuole secondarie inferiori pubbliche italiane sono calcolati utilizzando la Data Envelopment Analysis (DEA) con una procedura con doppio bootstrap, mentre un algoritmo di Random Forest è adottato per identificare le variabili che sono associate a punteggi più elevati e visualizzarne gli effetti in modo facilmente interpretabile. I risultati confermano le differenze di efficienzariscontrate in studi precedenti tra le scuole situate in diverse aree del Paese, con le scuole del Sud e delle isole che ottengono risultati peggiori rispetto alle altre. Le dimensioni della scuola, le dimensioni della classe e la percentuale di studenti immigrati sono i fattori più importanti che influenzano l'efficienza. Valutando gli effetti di interazione, è possibile includere nellavalutazione dell'efficienza anche gli anni di esperienza del dirigente scolastico, i giorni diassenza dei docenti (non per malattia o maternità) e la percentuale di fondi destinati alpagamento degli stipendi. Le implicazioni politiche sono presentate nell'ultima parte dello studio.  \nParole chiave: efficienza scolastica, data envelopment analysis, machine learning, random forest  \nList of Figures  \nFigure 1. Distribution of private school students ..................................................................... 31  \nFigure 2. Structure of the Italian education system.................................................................. 32  \nFigure 3. OECD member and partner countries in 2018 PISA tests........................................ 35  \nFigure 4. Trends in PISA scores of Italian students ................................................................. 36  \nFigure 5. Graphical construction of Farrell’s definition of efficiency ..................................... 38  \nFigure 6. Production function in the case of two inputs and one output.................................. 39  \nFigure 7 . Efficiency frontiers for input-and output-oriented DEA ................................","cbCairIER1T8eP4V","https://ap.wps.com/l/cbCairIER1T8eP4V","pdf",1781965,1,129,"English","en",105,"# Abstract\n## Abstract in lingua italiana\n## List of Figures","[{\"question\":\"How is educational efficiency measured for Italian lower secondary schools in this study?\",\"answer\":\"Efficiency is quantified for 4,264 Italian public lower secondary schools using Data Envelopment Analysis (DEA) with a double bootstrap procedure.\"},{\"question\":\"What role does Random Forest play in the analysis?\",\"answer\":\"Random Forest is used to identify variables associated with higher efficiency scores and to visualize their effects in an interpretable way.\"},{\"question\":\"Which factors most influence school efficiency according to the results?\",\"answer\":\"School size, class size, and the percentage of immigrant students are identified as the most important factors influencing efficiency.\"}]","The efficiency of Italian lower secondary schools - combination of DEA with a graphical machine learning approach | PDF",1785684036,325,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"the-efficiency-of-italian-lower-secondary-schools-combination-of-dea-with-a-graphical-machine-learning-approach","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/the-efficiency-of-italian-lower-secondary-schools-combination-of-dea-with-a-graphical-machine-learning-approach/118536/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"How is educational efficiency measured for Italian lower secondary schools in this study?","Question",{"text":75,"@type":76},"Efficiency is quantified for 4,264 Italian public lower secondary schools using Data Envelopment Analysis (DEA) with a double bootstrap procedure.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What role does Random Forest play in the analysis?",{"text":80,"@type":76},"Random Forest is used to identify variables associated with higher efficiency scores and to visualize their effects in an interpretable way.",{"name":82,"@type":73,"acceptedAnswer":83},"Which factors most influence school efficiency according to the results?",{"text":84,"@type":76},"School size, class size, and the percentage of immigrant students are identified as the most important factors influencing efficiency.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]