{"title":"更好地理解教师培训方案的自我选择:以波兰一所著名公立大学为例","authors":"Mikołaj Herbst, Tomasz Zając","doi":"10.2478/ceej-2023-0021","DOIUrl":null,"url":null,"abstract":"Abstract It is difficult to achieve high-quality education without good teachers. Therefore, it is crucial to understand who decides to become a teacher. This study leverages a large-scale administrative dataset comprising detailed records of the educational trajectories of 10 cohorts of students at the University of Warsaw, the largest higher education institution in Poland, in order to investigate self-selection to the teaching profession and to learn whether it depends on the mode of teacher training and the student's primary field of studies. We find that the recruitment of students to the concurrent teacher training programme is characterised by adverse self-selection with respect to prior academic achievements. When it comes to consecutive programmes, pursued as an extension or specialisation within the major programme, the willingness of students to enroll in teacher training is related to their secondary school achievements, but also – and in a distinct way – to their early experience at the university. In the case of STEM and foreign language programmes, we observe adverse selection to teacher training with respect to either the student's pre-university academic outcomes or their achievements during the first year of university studies.","PeriodicalId":9951,"journal":{"name":"Central European Journal of Economic Modelling and Econometrics","volume":"132 1","pages":"0"},"PeriodicalIF":0.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards a better understanding of self-selection to teacher training programmes: A case study of a renowned public university in Poland\",\"authors\":\"Mikołaj Herbst, Tomasz Zając\",\"doi\":\"10.2478/ceej-2023-0021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract It is difficult to achieve high-quality education without good teachers. Therefore, it is crucial to understand who decides to become a teacher. This study leverages a large-scale administrative dataset comprising detailed records of the educational trajectories of 10 cohorts of students at the University of Warsaw, the largest higher education institution in Poland, in order to investigate self-selection to the teaching profession and to learn whether it depends on the mode of teacher training and the student's primary field of studies. We find that the recruitment of students to the concurrent teacher training programme is characterised by adverse self-selection with respect to prior academic achievements. When it comes to consecutive programmes, pursued as an extension or specialisation within the major programme, the willingness of students to enroll in teacher training is related to their secondary school achievements, but also – and in a distinct way – to their early experience at the university. In the case of STEM and foreign language programmes, we observe adverse selection to teacher training with respect to either the student's pre-university academic outcomes or their achievements during the first year of university studies.\",\"PeriodicalId\":9951,\"journal\":{\"name\":\"Central European Journal of Economic Modelling and Econometrics\",\"volume\":\"132 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Central European Journal of Economic Modelling and Econometrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/ceej-2023-0021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Central European Journal of Economic Modelling and Econometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/ceej-2023-0021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
Towards a better understanding of self-selection to teacher training programmes: A case study of a renowned public university in Poland
Abstract It is difficult to achieve high-quality education without good teachers. Therefore, it is crucial to understand who decides to become a teacher. This study leverages a large-scale administrative dataset comprising detailed records of the educational trajectories of 10 cohorts of students at the University of Warsaw, the largest higher education institution in Poland, in order to investigate self-selection to the teaching profession and to learn whether it depends on the mode of teacher training and the student's primary field of studies. We find that the recruitment of students to the concurrent teacher training programme is characterised by adverse self-selection with respect to prior academic achievements. When it comes to consecutive programmes, pursued as an extension or specialisation within the major programme, the willingness of students to enroll in teacher training is related to their secondary school achievements, but also – and in a distinct way – to their early experience at the university. In the case of STEM and foreign language programmes, we observe adverse selection to teacher training with respect to either the student's pre-university academic outcomes or their achievements during the first year of university studies.
期刊介绍:
The Central European Journal of Economic Modelling and Econometrics (CEJEME) is a quarterly international journal. It aims to publish articles focusing on mathematical or statistical models in economic sciences. Papers covering the application of existing econometric techniques to a wide variety of problems in economics, in particular in macroeconomics and finance are welcome. Advanced empirical studies devoted to modelling and forecasting of Central and Eastern European economies are of particular interest. Any rigorous methods of statistical inference can be used and articles representing Bayesian econometrics are decidedly within the range of the Journal''s interests.