ReaderBench, an Environment for Analyzing Text Complexity and Reading Strategies

Mihai Dascalu 1, 2 Philippe Dessus 3 Stefan Trausan-Matu 1 Maryse Bianco 2 Aurélie Nardy 2
1 Computer Science Department [Bucarest]
2 LSE - Laboratoire des Sciences de l'Éducation (Grenoble)
3 MeTAH
LIG - Laboratoire d'Informatique de Grenoble, LSE - Laboratoire des Sciences de l'Éducation (Grenoble)
Abstract : ReaderBench is a multi-purpose, multi-lingual and flexible environment that enables the assessment of a wide range of learners' productions and their manipulation by the teacher. ReaderBench allows the assessment of three main textual features: cohesion-based assessment, reading strategies identification and textual complexity evaluation, which have been subject to empirical validations. 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.
Keywords : Text Cohesion Reading Strategies Textual Complexity Latent Semantic Analysi Latent Dirichlet Allocation Support Vector Machines
Type de document :
Communication dans un congrès
H. Chad Lane, Kalina Yacef, Jack Mostow, Philip Pavlik. AIED 13 - 16th International Conference on Artificial Intelligence in Education, Jul 2013, Memphis, TN, United States. Springer, 7926, pp.379-388, 2013, Lecture Notes in Computer Science (LNCS). 〈10.1007/978-3-642-39112-5_39〉
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https://hal.archives-ouvertes.fr/hal-00871568
Contributeur : Denis Bouhineau <>
Soumis le : mardi 15 octobre 2013 - 18:29:04
Dernière modification le : jeudi 11 janvier 2018 - 06:27:14

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TICE | LIG_SIC_METAH | LIG | LIG_SIC | UGA | LSE | LIG_SRCPR

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Mihai Dascalu, Philippe Dessus, Stefan Trausan-Matu, Maryse Bianco, Aurélie Nardy. ReaderBench, an Environment for Analyzing Text Complexity and Reading Strategies. H. Chad Lane, Kalina Yacef, Jack Mostow, Philip Pavlik. AIED 13 - 16th International Conference on Artificial Intelligence in Education, Jul 2013, Memphis, TN, United States. Springer, 7926, pp.379-388, 2013, Lecture Notes in Computer Science (LNCS). 〈10.1007/978-3-642-39112-5_39〉. 〈hal-00871568〉

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