• DocumentCode
    3474870
  • Title

    Captivate short answer evaluator

  • Author

    Srivastava, Vishnu ; Bhattacharyya, Chandranath

  • Author_Institution
    Adobe Captivate, Adobe Syst. India Pvt. Ltd., Bangalore, India
  • fYear
    2013
  • fDate
    20-22 Dec. 2013
  • Firstpage
    114
  • Lastpage
    119
  • Abstract
    We propose a model for automatically scoring short textual responses in e-learning content. Natural Language Processing (NLP) techniques are used to extract syntactic and semantic structures from the content, which are used to build the model. The proposed approach is planned to be implemented in Adobe Captivate - a popular end-to-end e-learning tool.
  • Keywords
    computer aided instruction; natural language processing; Adobe Captivate; NLP techniques; automatic short textual response scoring; captivate short answer evaluator; e-learning content; end-to-end e-learning tool; natural language processing techniques; semantic structure extraction; syntactic structure extraction; Accuracy; Compounds; Context; Engines; Feature extraction; Nitrogen; Pigments; auto evaluation; captivate; eLearning; short answer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    MOOC Innovation and Technology in Education (MITE), 2013 IEEE International Conference in
  • Conference_Location
    Jaipur
  • Print_ISBN
    978-1-4799-1625-2
  • Type

    conf

  • DOI
    10.1109/MITE.2013.6756317
  • Filename
    6756317