P
Philippe Dessus
Researcher at University of Grenoble
Publications - 69
Citations - 957
Philippe Dessus is an academic researcher from University of Grenoble. The author has contributed to research in topics: Latent semantic analysis & Computer-supported collaborative learning. The author has an hindex of 16, co-authored 68 publications receiving 905 citations. Previous affiliations of Philippe Dessus include Institut Universitaire de Formation des Maîtres.
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Journal ArticleDOI
A System To Assess the Semantic Content of Student Essays.
Benoît Lemaire,Philippe Dessus +1 more
TL;DR: A system that can automatically assess a student essay based on its content using Latent Semantic Analysis, a tool which is used to represent the meaning of words as vectors in a high-dimensional space.
Journal ArticleDOI
ReaderBench: Automated evaluation of collaboration based on cohesion and dialogism
TL;DR: Two computational models for assessing collaboration are proposed and validated based on a cohesion graph and a cohesion-based model of discourse, which can be perceived as a longitudinal analysis of the ongoing conversation and enabling a transversal analysis of subsequent discussion slices.
Book ChapterDOI
Mining Texts, Learner Productions and Strategies with ReaderBench
TL;DR: The chapter introduces ReaderBench, a multi-lingual and flexible environment that integrates text mining technologies for assessing a wide range of learners' productions and for supporting teachers in several ways.
Book ChapterDOI
ReaderBench, an Environment for Analyzing Text Complexity and Reading Strategies
TL;DR: ReaderBench covers a complete cycle, from the initial complexity assessment of reading materials, the assignment of texts to learners, the capture of metacognitions reflected in one's textual verbalizations and comprehension evaluation, therefore fostering learner's self-regulation process.
Free-Text Assessment in a Virtual Campus
TL;DR: Apex is presented, a module of a web-based learning environment which is able to assess student knowledge based on the content of free texts and relies on Latent Semantic Analysis, a tool which is used to represent the meaning of words as vectors in a high-dimensional space.