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2017
- handle: 10670/1.2gonh6
- hal: hal-01584796
- doi: 10.1007/978-3-319-66610-5_4
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-319-66610-5_4
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info:eu-repo/grantAgreement/EC/FP7/212578/EU/Language Technology for Lifelong Learning/LTFLL
Ce document est lié à :
info:eu-repo/grantAgreement//644187/EU/Realising an Applied Gaming Eco-system/RAGE
info:eu-repo/semantics/OpenAccess
Mots-clés
Health Care Nursing School Textual Complexity Infectious Diseases and Hygiene Case AnalysisSujets proches
School life Students--Education Pupils Student life and customs Methods of analysis Analysis and chemistry Analytical methods Chemical analysis Analysis methods Analysis and examinationCiter ce document
Mihai Dascalu et al., « How Well Do Student Nurses Write Case Studies? A Cohesion-Centered Textual Complexity Analysis », HAL-SHS : sciences de l'éducation, ID : 10.1007/978-3-319-66610-5_4
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Résumé
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 multipurpose 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.