The paths of doctoral students obtaining a Ph.D. in Germany are rarely standardized. In addition to very straightforward doctoral paths that are completed within a single context – such as graduate school – there are also doctoral phases with frequent context changes, for example when a doctorate is continued within an employment relationship following a scholarship program. Furthermore, they can vary significantly in length. While some complete their doctorate within a few years, others take considerably longer. This substantial difference in sequence lengths has made it difficult for sequence analyses to identify typical patterns in doctoral trajectories.
To address this challenge, the researchers propose normalizing the sequences. Instead of focusing on the absolute duration of the doctorate, the relative duration of individual episodes within the doctoral trajectories is considered. This means that each episode of a doctoral trajectory is viewed as a percentage of the overall doctorate — regardless of how long the doctorate takes. This normalization makes it possible to compare different doctoral paths directly, without the total duration of the doctorate distorting the results. In this way, patterns and typical trajectories can be better identified.
Sequence normalization offers several advantages, including direct comparability, as doctoral paths of different lengths can be systematically compared. Additionally, it allows for the identification of typical trajectories and patterns, which makes it easier to define ideal doctoral paths. The method also guarantees a better graphical representation of the data.
The researchers developed their method utilizing a panel study’s data of German doctoral graduates created by the German Centre for Higher Education Research and Science Studies (DZHW). The doctoral trajectories of doctoral holders were recorded on a monthly basis. Thanks to sequence normalization, they were able to systematically compare different doctoral paths and identify typical patterns.
Especially in areas where the duration of life trajectories varies greatly, this method of sequence analyses can uncover patterns and enable scientific decisions. The method thus offers great potential for future research and could also be applied to other educational or career trajectories.
If you have any questions regarding this publication, feel free to contact me.
Dr. Susanne de Vogel
Data-Science-Support
Tel. +49 (421) 218 - 63938
E-Mail: devogelprotect me ?!uni-bremenprotect me ?!.de
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