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Candidate sentence selection for language learning exercises: From a comprehensive framework to an empirical evaluation

Journal article
Authors Ildikó Pilán
Elena Volodina
Lars Borin
Published in Revue Traitement Automatique des Langues. Special issue on NLP for Learning and Teaching
Volume 57
Issue 3
Pages 67-91
Publication year 2017
Published at Department of Swedish
Pages 67-91
Language en
Links www.atala.org/content/talp-et-didac...
www.atala.org/revuetal
Keywords Corpus example selection, Exercise generation, User-based evaluation, language technology, second-language acquisition
Subject categories Linguistics, Computational linguistics, Language Technology (Computational Linguistics), Swedish language

Abstract

We present a framework and its implementation relying on Natural Language Processing methods, which aims at the identification of exercise item candidates from corpora. The hybrid system combining heuristics and machine learning methods includes a number of relevant selection criteria. We focus on two fundamental aspects: linguistic complexity and the dependence of the extracted sentences on their original context. Previous work on exercise generation addressed these two criteria only to a limited extent, and a refined overall candidate sentence selection framework appears also to be lacking. In addition to a detailed description of the system, we present the results of an empirical evaluation conducted with language teachers and learners which indicate the usefulness of the system for educational purposes. We have integrated our system into a freely available online learning platform.

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