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

Mihai Dascalu, Philippe Dessus, Laurent Thuez, Stefan Trausan-Matu

Research output: Chapter in Book/Report/Conference proceedingConference Article in proceedingAcademicpeer-review


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.
Original languageEnglish
Title of host publicationData Driven Approaches in Digital Education.
Subtitle of host publication12th European Conference on Technology Enhanced Learning (EC-TEL 2017)
EditorsÉ. Lavoué , H. Drachsler, K. Verbert, J. Broisin, M. Pérez-Sanagustín
ISBN (Electronic)978-3-319-66610-5
ISBN (Print)978-3-319-66609-9
Publication statusPublished - Oct 2017
Externally publishedYes
Event12th European Conference on Technology Enhanced Learning: Data Driven Approaches in Digital Education - Tallinn, Estonia
Duration: 12 Sept 201715 Sept 2017

Publication series

SeriesLecture Notes in Computer Science LNCS


Conference12th European Conference on Technology Enhanced Learning
Abbreviated titleEC-TEL 2017
Internet address


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


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