Katrin Drasch

Why Do We Collect Data on Educational Histories Over the Life Course the Way We Do ? Core Questionnaire Design Decisions in Starting Cohort 6—Adults

Starting Cohort 6—Adults is one of six samples of the German National Educational Panel Study (NEPS) and covers members of the adult population living in Germany from multiple birth cohorts. It aims at collecting data on educational processes and competence development in adult life as well as on learning environments, decision processes, and returns. To achieve these objectives, it is necessary to gather life-course information, particularly in the area of education and employment. In this chapter, we describe our core questionnaire design and justify why we collect life-course data the way we do. We begin by presenting theoretical principles of life course research and discussing their consequences for questionnaire design. Subsequently, we describe how the process of recalling events and their dating is supported by instrument design in order to guarantee that retrospective life course data will be complete and consistent. Finally, we illustrate the analysis potential of the collected life course data.

Data-Revision Module—A Beneficial Tool to Support Autobiographical Memory in Life-Course Studies

The key objective of the National Educational Panel Study (NEPS) is to enable analyses of the development of competencies, educational processes, educational decisions, and returns to education throughout the life span. These analyses are only possible by collecting complete and consistent educational and employment histories as well as the relevant contexts in which these histories are embedded, in other words, life-course data. In this respect, the most important challenge is remembering life histories retrospectively. To support both the cognitive memory capacity and the temporal integration of reported episodes in the life course, we decided to use a modular technique for collecting life-course data retrospectively. However, modularization makes it more difficult for respondents to recall the temporal integration of the episodes reported in the different life domains. To compensate for this disadvantage, we implemented a data-revision module that integrates all reported episodes from the different life domains immediately after collecting all relevant life-course data. In the data-revision module, the interviewer can edit all existing temporal inconsistencies in the life course in collaboration with the respondent by correcting the time span of episodes, by deleting and inserting episodes, and by clarifying overlaps of episodes. The module also pays attention to episodes with incomplete or missing calendar dates that can—by using estimates—be included in the life-course data and be edited directly during the interview in collaboration with the respondent. The result is a marked improvement in the data quality and validity of the recorded life histories.