EL PLAZO RAZONABLE EN LA JURISPRUDENCIA DEL TRIBUNAL CONSTITUCIONAL PERUANO

4.1. The National Educational Panel Study

All empirical analyses in this study are based on the National Educational Panel Study (NEPS). The Federal Ministry of Education and Research created this nationally representative database to study educational attainment in Germany, to assess the long- term consequences of education, and to describe central educational processes and trajectories from a life-course perspective (Blossfeld, von Maurice and Schneider 2011). Thus the NEPS provides longitudinal information on the educational careers of more than 60,000 individuals and follows a multi-cohort sequence design. It includes six different cohorts: early childhood, kindergarten children, 5th _{graders, 9}th _{graders, first-year higher-}

education students and adults who have left the educational system. All participants are surveyed regularly over an extended period of time using questionnaires and competence tests.

In order to study higher-education non-completion and the first labour market transitions of higher-education dropouts, I use data from the Starting Cohort 6 (SC6) ‘Adult Education and Lifelong learning’ and the Starting Cohort 5 (SC5) ‘First-Year Students’ (Blossfeld, Roßbach and von Maurice 2011).

4.2. Starting Cohort 6

The NEPS SC6 data provide detailed retrospective life history data with comprehensive information on the education and employment biography of each respondent as well as important cross-sectional data on several subjects, such as competence development in adulthood, employment situation, family constellation, and educational choices and participation in further training. The SC6 sample7 used here includes 17,135 respondents born in Germany between 1944 and 1986 who live in private households. 8 _{This sample is}

based on the ‘Working and Learning in a Changing World (ALWA)’ study conducted by

7_{doi:10.5157/NEPS:SC6:5.1.0.}

8 _{For more detailed information on the studies and sampling strategies, see Allmendinger et al.}

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the Institute for Employment Research (IAB) in Nürnberg beginning in 2007/2008 (Wave 1). These data are based on a sample that contains individuals from Germany’s resident population from the birth cohort 1956 to 1986, and was collected by computer-assisted telephone interviews (CATI).

The NEPS (Wave 2) started in 2009/2010 with data collection by taking over respondents from the ALWA study, an augmentation sample of birth cohort 1944 to 1955 as well as a refreshing sample of birth cohorts 1956 to 1986. In Wave 4 (2011/2012) a second refreshing sample was conducted to acquire new respondents, which contained individuals from the birth cohort 1944 to 1986. The SC6 data was collected by CATI and computer-assisted personal interviews (CAPI). The NEPS sample is self-weighted to ensure a representative database (Aust et al. 2011). The SC6 data used in this dissertation comprise data from four annual follow-up surveys (Waves 2 to 5: data collection between 2009/2010 and 2012/2013) plus the data from the ALWA study (Wave 1, 2007/2008).

Table 1: Summary of waves, NEPS SC6

Wave Survey mode Period Number of participants

1 CATI 2007/08 6,7769

2 CATI/CAPI 2009/10 11,649

3 CATI/CAPI 2010/11 9,320

4 CATI/CAPI 2011/12 14,104

5 CATI/CAPI 2012/13 11,696

Source: Hammon et al. (2016).

4.3. Starting Cohort 5

The SC5 ‘First Year Students’ data provide detailed retrospective life history data with information on the students’ pre-tertiary experiences, including secondary school trajectories, and pre-tertiary vocational training. The prospective panel data offer detailed information on educational decisions such as non-completion, including measurements of aspirations and attitudes to specific educational options as well as core concepts of costs, returns and subjective probabilities of success (Aschinger et al. 2011). The dataset also

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contains information about the students’ social and academic integration (Tinto 1975, 1993). In this dissertation, I use data from the NEPS SC510 _{comprising 17,910 first-year}

bachelor students11 enrolled for the first time in officially recognized and state-approved higher-education institutions in Germany, covering the period from 2010/2011 to 2012/2013. Within the randomly drawn sample,12 students who are training to be teachers and students attending private higher-education institutions, that is, private universities and private universities of applied sciences, are oversampled. In Wave 1 a complete survey with non-traditional students13 _{was conducted. The research design includes a}

yearly prospective panel, which was complemented by a retrospective life-course module in the first wave in 2010/2011. Several modes of data collection were used, such as self- administered questionnaires, CATI, online surveys, group-administered tests in classroom settings and online tests (Aschinger et al. 2011).

Table 2: Summary of waves, NEPS SC5

Wave Survey mode Period Number of participants

1 CATI Winter 2010/11 17,910

1 PAPI (competence test) Winter 2010/11 5,949

2 CAWI Autumn 2011 12,273

3 CATI Spring 2012 13,113

4 CAWI Autumn 2012 11,202

5 CATI Spring 2013 12,698

5 PAPI (competence test) Spring 2013 9,482

6 CAWI Autumn 2013 10,185

Sources: Zinn et al. (2016); Roßbach, Maurice and Polgar (2016)

Notes: PAPI = paper and pencil interviews; CAWI = computer-assisted web interviewing.

Additional modes were used, including: paper-based testing with electronic pens, computer-based testing with notebooks, computer-based online testing

10_{doi:10.5157/NEPS:SC5:6.0.0.}

11 _{The data also comprise students studying for a state examination in medicine, law studies,}

pharmacy or teaching, or a diploma or master’s degree in Catholic or Evangelical theology.

12 _{For more detailed information on the sampling strategies, see Aßmann et al. (2011).}

13 _{Students with vocational training qualifications but without higher-education entrance}

39 4.4. Why use the NEPS

Using the NEPS SC6 and SC5 data has several major advantages for the analysis of higher-education non-completion and the first labour market transitions of higher- education dropouts in Germany. In general, the datasets are suitable for examining the above-stated research questions for two reasons. First, the panel data allow the prospective observation of educational and occupational careers. Second, the retrospective module of both datasets surveys the individual’s personal history.

The NEPS SC6 first surveys individuals who have, apart from adult education, completed their education. In contrast to data from official statistics or panel studies, the SC6 offers detailed retrospective data on the respondents’ full educational biographies – including their pre-tertiary educational and occupational background – which enables it to distinguish between permanent dropout and non-completion that is followed by a later course in higher education. Furthermore, in contrast to former data, the NEPS SC6 allows the analysis of real dropout. Most data on higher-education dropouts merely asks about respondents’ plans and expectations to drop out in the future (e.g. Bargel, Ramm and Multrus 2008; Blüthmann, Thiel and Wolfgramm 2011; Fellenberg and Hannover 2006). The NEPS SC6 also surveys transitions into the labour market of individuals with different educational outcomes. While most data focusing on higher-education students do not include information on their labour market careers, the NEPS SC6 dataset facilitates the analysis of the first labour market outcomes of higher-education graduates and dropouts. Furthermore, in contrast to most data – which usually comprise persons who have been enrolled in higher education only – the NEPS SC6 dataset also includes the occupational biographies of other educational leavers, which permits analysis of the impact of different educational credentials on labour market returns.

The NEPS SC5 surveys first-year students and contains detailed information on educational decisions during college including costs, returns and subjective probabilities of success as well as aspirations and attitudes towards specific educational options. Furthermore, it measures the academic and social integration concept of Tinto (1975). Thus the reasons for higher-education non-completion as well as the different impacts of pre-tertiary and in-college factors on higher-education non-completion can be analysed. Finally, in contrast to most data that focus on a specific higher-education system

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(Pohlenz and Tinsner 2004; Pohlenz, Tinsner and Seyfried 2007; Schiefele, Streblow and Brinkmann 2007; Thiel, Blüthmann and Richter 2010), the NEPS SC5 provides a broader picture of non-completion in Germany by using representative nationwide data.

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