IJPDS International Journal of Population Data Science

Understanding how young people transition from school into the workforce is a crucial aspect of research into education and employment and a new dataset, developed by a researcher from the University of Sheffield, now offers an approach to studying these trajectories.

The dataset captures the education and employment activities of over half a million students in the 2010/11 school-leaver cohort, enabling analysis of post-16 pathways in England. It provides researchers and practitioners with an essential input tool specifically tailored for sequence analysis, a technique used to examine activities over time as part of a continuous process to help find long term patterns.

The school-to-work dataset was carefully constructed using the Department for Education’s Longitudinal Education Outcomes (LEO) using advanced data processing techniques. SQL was used to extract key variables, while further linkage and preprocessing were conducted using R. This ensured that the data was not only structured for sequence analysis but also optimised for regional studies, with the ability to segment by geographic areas.

Despite the growing use of sequence analysis in educational and labour market research, a significant challenge has been the lack of accessible and well-prepared input data. Preparing such datasets is often a time-consuming and complex process. Resources used to teach the sequence analysis method tend to use ‘ideal’ example datasets without addressing the key decisions required to create a suitable input dataset using real-world administrative data.  

Doctoral Researcher, Shivani Sickotra, explained, “This resource provides crucial guidance for researchers and practitioners who may require experience preparing input datasets for sequence analysis, addressing the current gap in available resources. By offering step-by-step instructions and shared code, it empowers users to recreate or adapt the dataset for their specific research needs.”

As interest in sequence analysis methods continues to grow, this dataset ensures that users have the initial input data they need to uncover meaningful school-to-work patterns and drive positive socio-economic change.

 

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Shivani Sickotra, Doctoral Researcher, Sheffield Methods Institute, School of Education, University of Sheffield, UK

Sickotra, S. (2023) “Data Resource Profile: A Guide for Constructing School-to-work Sequence Analysis Trajectories Using the Longitudinal Education Outcomes (LEO) Data”, International Journal of Population Data Science, 8(6). Available at: https://ijpds.org/article/view/2953 (Accessed: 25 March 2025).