Towards Effective Tutorial Feedback for Explanation Questions: A Dataset and Baselines

Myroslava O. Dzikovska, Rodney D. Nielsen, Chris Brew

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a new shared task on grading student answers with the goal of enabling well-targeted and flexible feedback in a tutorial dialogue setting. We provide an annotated corpus designed for the purpose, a precise specification for a prediction task and an associated evaluation methodology. The task is feasible but non-trivial, which is demonstrated by creating and comparing three alternative baseline systems. We believe that this corpus will be of interest to the researchers working in tex-tual entailment and will stimulate new developments both in natural language processing in tutorial dialogue systems and textual entailment, contradiction detection and other techniques of interest for a variety of computational linguistics tasks.
Original languageEnglish
Title of host publicationProceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Place of PublicationMontréal, Canada
PublisherAssociation for Computational Linguistics
Pages200-210
Number of pages11
ISBN (Print)978-1-937284-20-6
Publication statusPublished - 1 Jun 2012

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