This paper focuses on the potentiality of transformation of cross-sectional administrative information into longitudinal sociological data. The case study focuses on the Sapienza University of Rome administrative archives and the strategies of extrapolation and management of its registered students’ information in order to obtain a longitudinal data set. Furthermore, this paper shows the analysis of this longitudinal data set in order to highlight the utility of this kind of data structure and with aimS to: (1) evaluate Italian Higher Education reform policies and their implementation outcomes with reference to their main purposes through a quasi-experimental research; (2) prove that the Sequence Analysis (SA) tools are suitable for studying the complexity of Italian higher education students’ careers; (3) analyse the factors (also contextual) that have had an impact on the success/failure throughout the students’ academic careers (through Event History analysis, EH).
Amico, A., D'Alessandro, G., Decataldo, A. (2017). Advantages of administrative data: Three analyses of students’ careers in higher education. In N. Lauro, E. Amaturo, M. Grassia, B. Aragona, M. Marino (a cura di), Data Science and Social Research. Studies in Classification, Data Analysis, and Knowledge Organization (pp. 131-139). Springer Berlin Heidelberg [10.1007/978-3-319-55477-8_12].
Advantages of administrative data: Three analyses of students’ careers in higher education
Decataldo, A.
2017
Abstract
This paper focuses on the potentiality of transformation of cross-sectional administrative information into longitudinal sociological data. The case study focuses on the Sapienza University of Rome administrative archives and the strategies of extrapolation and management of its registered students’ information in order to obtain a longitudinal data set. Furthermore, this paper shows the analysis of this longitudinal data set in order to highlight the utility of this kind of data structure and with aimS to: (1) evaluate Italian Higher Education reform policies and their implementation outcomes with reference to their main purposes through a quasi-experimental research; (2) prove that the Sequence Analysis (SA) tools are suitable for studying the complexity of Italian higher education students’ careers; (3) analyse the factors (also contextual) that have had an impact on the success/failure throughout the students’ academic careers (through Event History analysis, EH).
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