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Towards an Automatic Q&A Generation for Online Courses - A Pipeline Based Approach

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Book cover Artificial Intelligence in Education (AIED 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11626))

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Abstract

Personalization of online courses is one of the challenges of the 21st century. Although different methodologies for personalization in educational contexts are already existing, there is a bottleneck: personalization by context is always limited to existing learning material; creation of those is a time-consuming task. In this paper we introduce a pipeline to generate questions and valid answers based on educational texts, limited to factual questions for given sentences. We combined NLP technologies with an efficient methodology that is normally used in bioinformatics and adjusted it to generate Q&A-pairs. Instructors can suggest corrections in natural language. Our system generates questions and corresponding answers based on sentences of which 70% make sense.

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Acknowledgments

This work was supported by the German Federal Ministry of Education and Research (BMBF), grant number 16DII116 (Weizenbaum-Institute). The responsibility for the content of this publication remains with the authors.

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Authors and Affiliations

  1. Humboldt-Universität zu Berlin, Berlin, Germany

    Sylvio Rüdian & Niels Pinkwart

  2. Weizenbaum Institute for the Networked Society, Berlin, Germany

    Sylvio Rüdian & Niels Pinkwart

Authors
  1. Sylvio Rüdian
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  2. Niels Pinkwart
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Corresponding author

Correspondence to Sylvio Rüdian .

Editor information

Editors and Affiliations

  1. University of Sao Paulo, Sao Paulo, Brazil

    Seiji Isotani

  2. University of Malaga, Málaga, Spain

    Eva Millán

  3. Carnegie Mellon University, Pittsburgh, PA, USA

    Amy Ogan

  4. DePaul University, Chicago, IL, USA

    Peter Hastings

  5. Carnegie Mellon University, Pittsburgh, PA, USA

    Bruce McLaren

  6. University College London, London, UK

    Rose Luckin

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Rüdian, S., Pinkwart, N. (2019). Towards an Automatic Q&A Generation for Online Courses - A Pipeline Based Approach. In: Isotani, S., Millán, E., Ogan, A., Hastings, P., McLaren, B., Luckin, R. (eds) Artificial Intelligence in Education. AIED 2019. Lecture Notes in Computer Science(), vol 11626. Springer, Cham. https://doi.org/10.1007/978-3-030-23207-8_44

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  • DOI: https://doi.org/10.1007/978-3-030-23207-8_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-23206-1

  • Online ISBN: 978-3-030-23207-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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