Search

Search Results

• VOCATIONAL SCHOOLS PROVIDING SPECIAL TASKS COMPARATIVE ANALYSIS OF ITS DOCUMENTS IN REGIONS WITH DIFFERENT ECONOMIC STATUS

  19-31

  Csilla Rétháti

  Erzsébet Rákó

  Views:

  147

  Vocational schools providing special tasks comparative analysis of its documents in regions with different economic status. The study deals with the examination of dropout reduction strategies of vocational schools in the regions of Northern Hungary, Northern Great Plains and Western Hungary. We are looking for the answer to what pedagogical methods are used by vocational schools and the teachers who teach there to reduce dropout. Our research was a document analysis, which included an overview of the pedagogical/professional programs of vocational schools based on specific criteria. We are looking for an answer to the question, how does disadvantage compensation appear in the pedagogical and professional programs of vocational schools.

• FIRST-GENERATION YOUNG PEOPLE'S CHANCES OF OBTAINING A DEGREE BASED ON A LARGE SAMPLE ANALYSIS

  17-30

  Veronika Bocsi

  Views:

  93

  Thy system of higher education can be analysed from the aspects of inequalities. The chance of attendance, the achievement, the phenomenon of drop-out, and types of training programs are approached from the students’ social background. Our analysis focuses on the chance of graduation of first-in-family people. The relatively rigid feature of Hungarian society and the lower mobility rate create a specific background for our research. Hungarian Youth Survey 2016 and 2020 databases were used during this analysis and we separated the subsample of young people between 25 and 29 (N²⁰¹⁶= 2906, N²⁰²⁰=2874). We try to discover the patterns of parents’ educational reproduction, describe the features of first-in-family people, and identify those factors which can form the chance of graduation. A binary regression model was run by us in which the dependent variable was the obtaining of a degree and the list of independent variables contained socio-demographic variables (sex, type of settlement, the economic situation of the region, economic situation, parental educational level, the type of parental profession), different life events (crises, the number of children, etc.) and the identification with the parental lifestyle. With these results, we can identify such an intersectional life situation (being a woman, habitation in cities, more favourable economic situation, mother’s white collar work, medium parental educational level, without children) in which the chance of graduation is higher.

• THE SOCIO-DEMOGRAPHIC CHARACTERISTICS AND ACADEMIC PREPAREDNESS OF STEM STUDENTS IN HUNGARY

  73-86

  Emese Alter

  Views:

  153

  Although the dropout behavior and labor market opportunities of STEM (Science, Technology, Engineering, and Mathematics) students and the masculinization of STEM fields are all well-researched topics in STEM research, there is a very limited body of literature focusing on the social background and academic preparedness of STEM applicants. Thus, in this research, we compared STEM and non-STEM students based on their type of settlement, type of secondary school program, the rate of students coming from a disadvantaged background, extra points given for academic accomplishments, and total application score. To identify variables that significantly predict getting admitted to a STEM field, we conducted binary logistic regression. During our research, we conducted the analysis using the 2017 Hungarian Admission Database. Our sample consisted of those who got admitted to a full-time BA/BSc or undivided course (N = 41324). According to our results, STEM students cannot be identified as a disadvantaged group either in terms of their social background or their lack of academic preparedness. According to the results of the binary logistic regression, the main predictors of getting admitted to a STEM field are gender (male), having a language certificate, and having a vocational training certificate. The main goal of our research was to explore whether the individual characteristics of STEM students can be the reason behind the high attrition rates specific to STEM fields. Since our results did not support this conclusion, we suppose to further investigate the role of institutional variables (such as climate, the selective approach of college teachers, and high academic expectations) in dropouts.