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Dialogue Act Classification In Human-to-Human Tutorial Dialogues

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Part of the book series: Lecture Notes in Educational Technology ((LNET))

Abstract

We present in this paper preliminary results with dialogue act classification in human-to-human tutorial dialogues. Dialogue acts are ways to characterize the actions of tutors and students based on the language-as-action theory. This work serves our larger goal of identifying patterns of tutors’ actions, in the form of dialogue acts, that relate to learning. The preliminary results we obtained for dialogue act classification using a machine learning approach are promising.

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References

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  5. Morrison, D. M., Nye, B., Samei, B., Datla, V. V., Kelly, C., & Rus, V. (2014). Building an Intelligent PAL from the Tutor.com Session Database-Phase 1: Data Mining. The 7th International Conference on Educational Data Mining, 335-336.

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Correspondence to Vasile Rus .

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© 2017 Springer Science+Business Media Singapore

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Rus, V., Maharjan, N., Banjade, R. (2017). Dialogue Act Classification In Human-to-Human Tutorial Dialogues. In: Popescu, E., et al. Innovations in Smart Learning. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-10-2419-1_25

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  • DOI: https://doi.org/10.1007/978-981-10-2419-1_25

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2418-4

  • Online ISBN: 978-981-10-2419-1

  • eBook Packages: EducationEducation (R0)

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