[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127076-en":3,"doc-seo-127076-105":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},127076,5909887256941,"Levi","https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc",8,"Research & Report","Analyzing the Influence of Educational Quality and Socioeconomic Factors on Finland's Economic Growth - a Machine Learning Approach","This study investigates the influence of educational quality and socioeconomic factors on Finland’s economic growth from 1990 to 2023, focusing on relationships among variables and their joint effect on GDP growth. Random Forest, XGBoost, and logistic regression are applied to capture complex dynamics and nonlinear interactions. Results emphasize that Finland’s high-quality education, supported by strong educational attainment and substantial R&D investment, contributes to economic stability and growth. Key socioeconomic predictors include labor force participation, unemployment, and internet penetration, with population growth and digitalization especially influential.","Bachelor’s thesis  \nInformation and Communication Technology 2024  \nMia Nguyên  \nAnalyzing the Influence of Educational Quality and Socioeconomic Factors on Finland's Economic Growth  \n– a Machine Learning Approach  \nBachelor’s Thesis | Abstract  \nTurku University of Applied Sciences Information and Communication Technology 2024 | 36 pages  \nMia Nguyên  \nAnalyzing the Influence of Educational Quality and Socioeconomic Factors on Finland's Economic Growth  \n-A Machine Learning Approach  \nThis study inves7gates the inﬂuence of educa7onal quality and socioeconomic factors on Finland’s economic growth from 1990 to 2023. The research addresses therela7onship between these variables and explores their combined impact on GDP growth.  \nTo analyze the complex dynamics of economic growth, machine learning models such as Random Forest, XGBoost, and logis7c regression were employed. These models allowed for the iden7ﬁca7on of key predictors and the examina7on of nonlinear rela7onships among variables.  \nThe ﬁndings highlight that Finland’s high-quality educa7on system, characterized by strong educa7onal aRainment and signiﬁcant R&D investment, contributes substan7ally to economic stability and growth. Addi7onally, socioeconomic factors—such as labor force par7cipa7on, unemployment, and internet penetra7on—play acri7cal role in inﬂuencing GDP growth. Popula7on growth and digitaliza7on emerged as par7cularly inﬂuen7al predictors, showcasing the importance of combining educa7onaland socioeconomic strategies to drive economic performance.  \nThis research underscores the need for integrated policies that support both educa7on and socioeconomic development to sustain long-term economic growth. The study also demonstrates the poten7al of machine learning methods for uncovering complex, nonlinear rela7onships in economic analysis. Future research should incorporate  \nins7tu7onal quality indicators and expand the analysis to other high-achieving countries to validate and generalize the ﬁndings.  \nKeywords:  \neconomic growth, educa7onal quality, socioeconomic factors, machine learning models, Finland, predic7ve analysis  \nContent  \nList of abbreviations (or) symbols 7  \n1 Introduction 8  \n1.1 Background of the Study 8  \n1.2 Research Problem 9  \n1.3 Research Aim and Objectives 9  \n1.4 Significance of the Study 9  \n1.5 Structure of the Thesis 10  \n2 Literature Review 11  \n2.1 Introduction 11  \n2.2 Theoretical Framework 11  \n2.2.1 Human Capital Theory 11  \n2.2.2 Endogenous Growth Theory 12  \n2.2.3 Socioeconomic Development Theories 12  \n2.3 Educational Quality and Economic Growth 13  \n3 Methodology 15  \n3.1 Data Collection 15  \n3.2 Data Preprocessing 16  \n3.2.1 Data Cleaning 16  \n3.2.2 Feature Engineering 16  \n3.3 Model Architecture 16  \n3.3.1 Model Components 17  \n3.3.2 Hyperparameters 17  \n3.3.3 Training Strategy 17  \n4 Result 19  \n4.1 Descriptive Statistics 19  \n4.2 Correlation analysis 20  \n4.3 Multiple Linear Regression Model 21  \n4.4 Logistic Regression 22  \n4.5 Random Forest Model 24  \n4.6 XGBoost Model 25  \n4.7 Summary performance of Machine Learning Model 26  \n4.8 Predictions using ARIMA Models 26  \n5 Discussion 29  \n6 Conclusion and Recommendations 32  \n6.1 Conclusions 32  \n6.2 Suggestions for Future Research 32  \nReferences 32  \nFigures  \nFigure 1. Finland’s GDP Growth (1990 – 2023) (Source: World Bank (2024)) ... 8  \nFigure 2. Dataset information............................................................................ 15  \nFigure 3. Correlation Matrix of variables ........................................................... 20  \nFigure 4. ROC Curve ........................................................................................ 23  \nFigure 5. Random Forest-Feature Importance ............................................... 24  \nFigure 6. XGBoost-Feature Importance .......................................................... 25  \nFigure 7. Finland's GDP Growth Rate, 1990-2023, reflects several major economic cycles and crises........","cbCaidfx0OiMuUkd","https://ap.wps.com/l/cbCaidfx0OiMuUkd","pdf",1049409,1,35,"English","en",105,"# Introduction\n## Background of the Study\n## Research Problem\n## Research Aim and Objectives\n## Significance of the Study\n## Structure of the Thesis\n# Literature Review\n## Theoretical Framework\n## Educational Quality and Economic Growth\n# Methodology\n## Data Collection\n## Data Preprocessing\n## Model Architecture\n# Result\n## Descriptive Statistics\n## Correlation analysis\n## Multiple Linear Regression Model\n## Logistic Regression\n## Random Forest Model\n## XGBoost Model\n## Summary performance of Machine Learning Model\n## Predictions using ARIMA Models\n# Discussion\n# Conclusion and Recommendations\n## Conclusions\n## Suggestions for Future Research","[{\"question\":\"Which variables are analyzed for their impact on Finland’s GDP growth?\",\"answer\":\"The study analyzes educational quality and socioeconomic factors and how they relate to GDP growth from 1990 to 2023.\"},{\"question\":\"What machine learning models are used in the analysis?\",\"answer\":\"Random Forest, XGBoost, and logistic regression are used to identify key predictors and examine nonlinear relationships among variables.\"},{\"question\":\"What key findings link education and socioeconomic conditions to economic growth?\",\"answer\":\"High-quality education in Finland, including educational attainment and R\\u0026D investment, supports economic stability and growth, while labor force participation, unemployment, and internet penetration significantly influence GDP growth.\"}]","Analyzing the Influence of Educational Quality and Socioeconomic Factors on Finland's Economic Growth - a Machine Learning Approach | PDF",1785936700,88,{"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},"analyzing-the-influence-of-educational-quality-and-socioeconomic-factors-on-finlands-economic-growth-a-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/analyzing-the-influence-of-educational-quality-and-socioeconomic-factors-on-finlands-economic-growth-a-machine-learning-approach/127076/",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","2026-08-05",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},"Which variables are analyzed for their impact on Finland’s GDP growth?","Question",{"text":75,"@type":76},"The study analyzes educational quality and socioeconomic factors and how they relate to GDP growth from 1990 to 2023.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What machine learning models are used in the analysis?",{"text":80,"@type":76},"Random Forest, XGBoost, and logistic regression are used to identify key predictors and examine nonlinear relationships among variables.",{"name":82,"@type":73,"acceptedAnswer":83},"What key findings link education and socioeconomic conditions to economic growth?",{"text":84,"@type":76},"High-quality education in Finland, including educational attainment and R&D investment, supports economic stability and growth, while labor force participation, unemployment, and internet penetration significantly influence GDP growth.","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"]