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School Retention Rates in Portuguese Municipalities

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an School retention rates in Portuguese municipalities A comparative analysis Rita Marques Costa Dissertation presented as a partial requirement for obtaining the Master’s degree in Statistics and Information Management i OVA Information Management School Instituto Superior de Estatística e Gestão de Informação Universidade Nova de Lisboa SCHOOL RETENTION RATES IN PORTUGUESE MUNICIPALITIES: A COMPARATIVE ANALYSIS by Rita Marques Costa Dissertation presented as a partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Information Analysis and Management Advisor: Professor Paulo Pinho Gomes ii June 2019 iii ACKNOWLEDGMENTS First of all, thanks to professor Paulo Pinho Gomes. Who was incredibly generous and always available along the process. Thanks for being demanding, realistic and for always being ready to listen and answer to my questions. This project would not have moved forward without his precious guidance. Special thanks also to professor Jorge Mendes for his advice during the development of this dissertation. The most important lesson I have learned in the past two years was not to give up. I thank Helena for never letting me do so and for her unconditional support; my parents, and my sister for being my greatest inspiration and example of resilience and hard work - I would not be half of what I am today without them; Ricardo for listening to my very specific technical questions; my grandparents and Rafa, for keeping my heart warm; Cláudia and Zara for making this long road so much fun and for teaching me so much. iv ABSTRACT One of the measures used to evaluate the success of an education system is the retention rate. In Portugal, in spite of the progress achieved in the past decades, students’ retention is still a problem. The phenomenon of school failure has been extensively studied throughout the world. Nevertheless, the way it is distributed across the country and the potential reasons that contribute to it being more intense in some areas than in others have not. The idea behind this project is to analyze the retention rates in middle school and in high school in the Portuguese public system, since the beginning of the decade and understand how they are distributed across the territory. The methods used were Principal Components Analysis and cluster analysis. The data related to potentially explanatory indicators of student failure – such as the average number of students per class, percentage of students in families who benefit from social support and the percentage of teachers with a permanent contract – were analyzed. The differences between the north and the south of the country are remarkable. Generally, the retention rates are much higher in the south than in the north. We also conclude that municipalities that are closer to each other have similar behaviors regarding their students’ success or unsuccess in terms of retention rates. Nevertheless, there are exceptions to the rule. For example, in Algarve, São Brás de Alportel stands out as a municipality that does particularly well in a context where retention rates are relatively high. Lastly, in this dissertation, we zoomed in the conurbations of Lisboa and Porto, where almost one in four children was enrolled in 2015/2016. The conclusions are striking: there are schools with some of the lowest retention rates while others, sometimes right across the street, can double the percentage of retained students. KEYWORDS PCA; cluster analysis; school failure; municipalities; geographic distribution v INDEX 1. Introduction .................................................................................................................. 1 2. Literature review .......................................................................................................... 3 2.1. The concept ........................................................................................................... 3 2.2. National and international data ............................................................................ 3 2.3. The impacts ........................................................................................................... 3 2.4. Geographical distribution ...................................................................................... 5 2.5. Priority intervention .............................................................................................. 6 2.6. International examples .......................................................................................... 6 3. Methodology ................................................................................................................ 8 3.1. Data description .................................................................................................... 8 3.2. Principal components analysis ............................................................................ 11 3.3. Cluster analysis .................................................................................................... 11 3.4. Workflow ............................................................................................................. 12 4. Results and discussion ................................................................................................ 13 4.1. Principal components .......................................................................................... 14 4.1.1. First principal component (PC1) ................................................................... 14 4.1.2. Second principal component (PC2) .............................................................. 16 4.1.3. Third principal component (PC3) ................................................................. 18 4.1.4. Fourth principal component (PC4) ............................................................... 19 4.1.5. Fifth principal component (PC5) .................................................................. 21 4.1.6. Sixth principal component (PC6) .................................................................. 22 4.1.7. Seventh principal component (PC7) ............................................................. 24 4.1.8. Eighth principal component (PC8)................................................................ 25 4.1.9. Ninth principal component (PC9) ................................................................. 26 4.1.10. Tenth principal component (PC10)........................................................ 28 4.2. Cluster analysis .................................................................................................... 29 4.2.1. Cluster one: the not so good and not so bad ............................................... 31 4.2.2. Cluster two: the peak in 12th grade between 2010/2011 and 2011/2012 . 32 4.2.3. Cluster three: the peak in 12th grade in 2012/2013 and 2013/2014 .......... 32 4.2.4. Cluster four: bad in 10th and in 12th grade ................................................. 33 4.2.5. Cluster five: the best performing municipalities .......................................... 34 4.2.6. Cluster six: the worst performing municipalities ......................................... 35 4.2.7. Cluster seven: peak in 8th and 9th grade..................................................... 35 vi 4.2.8. Additional data ............................................................................................. 36 4.2.9. A closer look into each territory ................................................................... 37 4.3. Zoom in Lisboa and Porto .................................................................................... 51 4.3.1. Lisboa in middle school ................................................................................ 52 4.3.2. Lisboa in high school .................................................................................... 55 4.3.3. Porto in middle school.................................................................................. 56 4.3.1. Porto in high school ...................................................................................... 59 4.4. TEIP schools ......................................................................................................... 61 5. Conclusions ................................................................................................................. 65 6. Limitations and recommendations for future works ................................................. 66 7. Bibliography ................................................................................................................ 67 8. Appendix ..................................................................................................................... 69 9. Annexes ...................................................................................................................... 77 vii LIST OF FIGURES Figure 1 – Example boxplots for 9th grade 2010/2011 (left) and for 12th grade 2011/2012 (right) .................................................................................................................................. 8 Figure 2 – Evolution of median retention rates in each school level along the years under study ................................................................................................................................. 10 Figure 3 – Workflow ................................................................................................................. 12 Figure 4 – Screeplot .................................................................................................................
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