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We present a framework and its implementation relying on Natural LanguageProcessing methods, which aims at the identification of exercise itemcandidates from corpora. The hybrid system combining heuristics and machinelearning methods includes a number of relevant selection criteria. We focus ontwo fundamental aspects: linguistic complexity and the dependence of theextracted sentences on their original context. Previous work on exercisegeneration addressed these two criteria only to a limited extent, and a refinedoverall candidate sentence selection framework appears also to be lacking. Inaddition to a detailed description of the system, we present the results of anempirical evaluation conducted with language teachers and learners whichindicate the usefulness of the system for educational purposes. We haveintegrated our system into a freely available online learning platform.

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