Sequence Analysis as a useful tool to study university attrition, retention and students’ careers

Journal title RIV Rassegna Italiana di Valutazione
Author/s Giampiero D'Alessandro
Publishing Year 2017 Issue 2016/65 Language Italian
Pages 19 P. 82-100 File size 726 KB
DOI 10.3280/RIV2016-065006
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This paper focuses on the potentiality of the sequence analysis as a tool to study and better understand the university students’ career paths. Compared to the cross-sectional studies, the sequence analysis allows not only a more correct approach to the phenomena of the dispersion within tertiary education, but also an immediate return of the results. Also, through its features, sequence analysis helps the marketability of these results for comparative and/or evaluation purposes. The holistic view lets administrative information into diachronic sociological data. This work shows the suitability of the sequence analysis tools for studying the complexity of the Italian higher education students’ careers, also analysing a case study: the Sapienza University of Rome first time enrolled in AY 2001/2002.

Keywords: Sequence Analysis; Students' Careers; Attrition; Retention; Longitudinal Studies; Drop Out.

  1. Amico A., D’Alessandro G. (2016), Strategie di gestione e analisi di grandi basi di dati amministrativi: l’utilità di trasformare dati sincronici in vettori diacronici. Sociologia e Ricerca Sociale. 109(1): 127-142. DOI: 10.3280/SR2016-109011.
  2. Anvur (2014). Rapporto sullo stato del sistema universitario e della ricerca 2013. --Testo disponibile al sito:http://www.anvur.org/attachments/article/644/Rapporto%20ANVUR%202013_UNIVERSITA%20e%20RICERCA_integrale.pdf. Ultimo accesso: 31 marzo 2016.
  3. Anvur (2016). Rapporto sullo stato del sistema universitario e della ricerca 2016. --Testo disponibile su:http://www.anvur.org/attachments/article/644/Rapporto%20ANVUR%202013_UNIVERSITA%20e%20RICERCA_integrale.pdf. Ultimo accesso: 20 gennaio 2017.
  4. Benvenuto G. (2012). Il monitoraggio di sistema. In Benvenuto G., Decataldo A. e Fasanella A., a cura di (2012). C’era una volta l’università? Analisi longitudinale delle carriere degli studenti prima e dopo la “grande riforma”. Acireale-Roma: Bonanno.
  5. Benvenuto G., Decataldo A. e Fasanella A. a cura di (2012). C’era una volta l’università? Analisi longitudinale delle carriere degli studenti prima e dopo la “grande riforma”. Acireale-Roma: Bonanno.
  6. Biolcati Rinaldi F. (2006). Povertà, teoria e tempo. La valutazione delle politiche di sostegno al reddito. Milano: FrancoAngeli.
  7. Bison I. (2009). OM matters: the interaction effects between indel and substitution costs, Methodological Innovations Online, 4(2): 53-67. --Testo disponibile all’indirizzo http://www.methodologicalinnovations.org.uk/wp-content/uploads/2013/11/5.-Bison-final-August-9-09.pdf. Ultimo accesso: 31 marzo 2016.
  8. Blanchard P., Bühlmann F. and Gauthier J. A., editors (2014). Advances in Sequence Analysis: Theory, Method, Applications. Berlin-Heidelberg: Springer.
  9. Elzinga C.H. (2014). Distance, Similarity and Sequence Comparison». In: Blanchard P., Bühlmann F. e Gauthier J.A., editors, Advances in Sequence Analysis: Theory, Method, Applications. Berlin-Heidelberg: Springer.
  10. Enqa – European association for quality assurance in higher education (2009). Standards and Guidelines for Quality Assurance in Higher Education, 3rd edition. --Testo disponibile al sito http://www.enqa.eu/wp-content/uploads/2013/06/ESG_3edition-2.pdf. Ultimo accesso: 31 marzo 2016.
  11. Enqa – European association for quality assurance in higher education (2015). Standards and Guidelines for Quality Assurance in Higher Education. --Testo disponibile al sito http://www.enqa.eu/wp-content/uploads/2015/11/ESG_2015.pdf. Ultimo accesso: 31 gennaio 2017.
  12. Gabadinho A., Ritschard G., Müller N.S., Studer M. (2009). Mining Sequence Data in R with the TraMineR package: A user's guide, Department of Econometrics and Laboratory of Demography, Geneva, University of Geneva. --Testo disponibile al sito http://mephisto.unige.ch/pub/TraMineR/doc/1.4/TraMineR-1.4-Users-Guide.pdf. Ultimo accesso: 12 gennaio 2016.
  13. Gabadinho A., Ritschard G., Müller, N.S., Studer M. (2011). Analyzing and visualizing state sequences in R with TraMineR. Journal of Statistical Software. 40(4): 1-37.
  14. Fasanella A. (2012). Prospettive metodologiche per l’analisi del cambiamento istituzionale. In Benvenuto G., Decataldo A. e Fasanella A., a cura di (2012). C’era una volta l’università? Analisi longitudinale delle carriere degli studenti prima e dopo la “grande riforma”. Acireale-Roma: Bonanno.
  15. Levine J. (2000). But what have you done for us lately. Sociological Methods & Research, 29(1): 35-40. DOI: 10.1177/0049124100029001002
  16. MacIndoe H. e Abbott A. (2004). Sequence Analysis and Optimal Matching Techniques for Social Science Data. In Hardy M. e Bryman A., editors, The Handbook of Data Analysis. London-Thousand Oaks-New Delhi: Sage.
  17. Menard S., a cura di (2007). Handbook of longitudinal research: design, measurement, and analysis. Amsterdam: Elsevier.
  18. R Core Team (2014). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.
  19. Ruspini E. (2004), La ricerca longitudinale. Milano: FrancoAngeli.
  20. Studer M. (2013). WeightedCluster library manual: A practical guide to creating typologies of trajectories in the social science. Lives Working Papers. 24: 1-32.
  21. Studer M., Ritschard G. (2014), A comparative review of sequence dissimilarity measures. Lives Working Papers, 33: 1-47.
  22. Tanucci G. (2006). Orientamento e carriera universitaria. In Fasanella A. e Tanucci G., a cura di, Orientamento e carriera universitaria. Ingressi ed abbandoni in cinque Facoltà dell’Università di Roma “La Sapienza” nel nuovo assetto didattico. Milano: FrancoAngeli.
  23. Wu L.L. (2000). Some comments on Sequence analysis and optimal matching methods in sociology: Review and prospect. Sociological methods and research, 29(1): 41-64. DOI: 10.1177/0049124100029001003

Giampiero D'Alessandro, La Sequence Analysis come strumento per lo studio delle carriere e della dispersione universitaria in "RIV Rassegna Italiana di Valutazione" 65/2016, pp 82-100, DOI: 10.3280/RIV2016-065006