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

Abstract

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.

A Data-Driven Approach for the Identification of Features for Automated Feedback on Academic Essays

“…Readerbench provides more than 200 textual complexity indices related to linguistic features of the text including surface, syntactic, morphological, semantic, and discourse features. Using ReaderBench, research to choose features that contribute the most towards the scores given by human raters has already been conducted for the French language [32]. That research uses a different approach, namely Discriminant Function Analysis.…”

Identifying Critical Features for Formative Essay Feedback with Artificial Neural Networks and Backward Elimination

“…Readerbench provides more than 200 textual complexity indices related to linguistic features of the text including surface, syntactic, morphological, semantic, and discourse features. Using ReaderBench, a research to choose features that contribute the most towards the scores given by human raters has already been conducted for the French language [24]. That research uses a different approach, namely Discriminant Function Analysis.…”