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The Conceptualisation, Measurement, and Coding of Education in German and Cross-National Surveys (Version 2.0)
[working paper]
Corporate Editor
GESIS - Leibniz-Institut für Sozialwissenschaften
Abstract This contribution provides an overview of the theoretical conceptualisation, empirical operationalisation, and the measurement and coding of education in national and international survey research. In this context, the term "education" refers to the level of education attained by an individual, whic... view more
This contribution provides an overview of the theoretical conceptualisation, empirical operationalisation, and the measurement and coding of education in national and international survey research. In this context, the term "education" refers to the level of education attained by an individual, which must be distinguished from concepts such as competencies, performance at school, and educational disciplines. Because education is often included in statistical models in a merely routine way, emphasis is placed on the connection between the theoretical concept, the indicator, the measurement instrument, and the variable. When doing so, use is made of long-standing social science research on educational returns and educational inequality. A distinction is made between linear, ordinal and categorical concepts of education that have emerged from the different theoretical approaches, and that, to some extent, impose different requirements on data collection and coding. Indeed, it is true to say that there is no consensus as to how education should be conceptualised, measured, compared across countries, and statistically modelled. The contribution does not give a recommendation for a "one size fits all" educational variable that would be appropriate for all studies. Rather, it endeavours to encourage readers to make an informed decision on the measurement of education in the respective educational context and to support them in doing so.... view less
Keywords
survey; questionnaire; data capture; measurement instrument; course of education; educational inequality; level of education; level of education attained; education; indicator; coding; international comparison; survey research
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Document language
English
Publication Year
2016
City
Mannheim
Page/Pages
63 p.
Series
GESIS Survey Guidelines
Status
Primary Publication; peer reviewed
Licence
Creative Commons - Attribution-Noncommercial-No Derivative Works 4.0