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En nyttomaximerande skola i det innovationsdrivna samhället
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2016 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
A utility maximizing school in the innovations driven society (English)
Abstract [sv]

Det här kandidatexamensarbetet inom matematisk statistik och industriell ekonomi tar fram ett underlag för hur Sverige och andra innovationsdrivna länder kan agera för att uppnå en nyttomaximerande skola. Detta genom att undersöka vilka faktorer som påverkar resultatet på PISA-testet via användning av multipel linjär regression, samt vilka faktorer som främjar innovation med hjälp av en litteraturstudie. Utifrån fyra perspektiv (generellt-, skol-, lärar- och elevperspektiv) valdes förklaringsvariabler ut för att inkluderas i regressionsanalysen. Resultatet gav att signifikanta variabler återfanns i samtliga perspektiv.  Litteraturstudien utgick från två perspektiv (individ och organisation), där resultatet var i form av en omfattande översikt av innovationsdrivande faktorer. Den dragna slutsatsen var att högre lärarlöner och högre kvalitet på skolmateriel leder till effektivare kunskapsutlärning. Mindre klasstorlekar däremot påverkar inte kunskapsutlärningen, medan längre tid för elever i skolan leder till sämre sådan. Ytterligare konklusioner var att skolan bör fokusera mer på arbete i grupp istället för individuellt arbete, träna elever på att definiera problem och inte bara lösa färdiga sådana samt låta elever kombinera olika ämneskunskaper i större utsträckning.

Abstract [en]

This thesis within mathematical statistics and industrial economics forms a foundation which explains how Sweden and other innovation-driven countries can act to achieve an efficient school. Multiple linear regression is used to identify explanatory variables that affect the results on the PISA test and factors that foster innovation are examined via a literature review. The included variables in the regression analysis were chosen out of four perspectives: general, school, teaching and student. The result showed that significant variables were found in all four perspectives. Moreover, the literature review was based on an individual perspective and an organisational perspective. The results are presented as an extensive overview of factors that affect innovation. A conclusion that higher teacher salaries and better quality of equipment in schools lead to more efficient learning is drawn. However, smaller class sizes do not affect quality of learning and more time spent in school by students affects the quality of learning negatively. Further conclusions are that schools should focus on group-based work instead of individual work. Students should also be taught to redefine problems and combine knowledge from different subjects to a greater extent.

Place, publisher, year, edition, pages
2016.
Series
TRITA-MAT-K, 2016:14
National Category
Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-189009OAI: oai:DiVA.org:kth-189009DiVA: diva2:942668
Subject / course
Applied Mathematical Analysis
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2016-06-26 Created: 2016-06-26 Last updated: 2016-06-26Bibliographically approved

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CiteExportLink to record
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Citation style
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