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How Well Do Student Nurses Write Case Studies? A Cohesion-Centered Textual Complexity Analysis

  • Mihai Dascalu
  • Philippe Dessus
  • Laurent Thuez
  • Stefan Trausan-Matu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10474)

Abstract

Starting from the presumption that writing style is proven to be a reliable predictor of comprehension, this paper investigates the extent to which textual complexity features of nurse students’ essays are related to the scores they were given. Thus, forty essays about case studies on infectious diseases written in French language were analyzed using ReaderBench, a multi-purpose framework relying on advanced Natural Language Processing techniques which provides a wide range of textual complexity indices. While the linear regression model was significant, a Discriminant Function Analysis was capable of classifying students with an 82.5% accuracy into high and low performing groups. Overall, our statistical analysis highlights essay features centered on document cohesion flow and dialogism that are predictive of teachers’ scoring processes. As text complexity strongly influences learners’ reading and understanding, our approach can be easily extended in future developments to e-portfolios assessment, in order to provide customized feedback to students.

Keywords

Health care Nursing school Textual complexity Infectious diseases and hygiene Case analysis 

Notes

Acknowledgements

The authors wish to thank Patrice Lombardo, head of the IFSI, Centre Hospitalier Annecy-Genevois, who helped make this research possible, and Jean-Luc Rinaudo, University of Rouen, for his valuable input all along the phases of this research. This research was partially supported by the FP7 2008-212578 LTfLL project, by the 644187 EC H2020 Realising an Applied Gaming Eco-system (RAGE) project, as well as by University Politehnica of Bucharest through the “Excellence Research Grants” Programs UPB–GEX 12/26.09.2016.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mihai Dascalu
    • 1
    • 2
    • 3
  • Philippe Dessus
    • 3
  • Laurent Thuez
    • 4
  • Stefan Trausan-Matu
    • 1
    • 2
  1. 1.University Politehnica of BucharestBucharestRomania
  2. 2.Academy of Romanian ScientistsBucharestRomania
  3. 3.Laboratoire des Sciences de l’Éducation, Univ. Grenoble AlpesGrenobleFrance
  4. 4.IFSI, Centre Hospitalier Annecy-GenevoisMetz-TessyFrance

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