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N-Gram Based Approach for Automatic Prediction of Essay Rubric Marks

  • Magdalena JankowskaEmail author
  • Colin Conrad
  • Jabez Harris
  • Vlado Kešelj
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10832)

Abstract

Automatic Essay Scoring, applied to the prediction of grades for dimensions of a scoring rubric, can provide automatic detailed feedback on students’ written assignments. We apply a character and word n-gram based technique proposed originally for authorship identification—Common N-Gram (CNG) classifier—to this task. We report promising results for the rubric mark prediction for essays by CNG, and perform analysis of suitability of different types of n-grams for the task.

Keywords

Automatic Essay Scoring Text classification Character n-grams 

Notes

Acknowledgement

The project was supported by the NSERC Engage grant EGP/507291-2016 with industry partner, D2L Corporation. The authors would like to thank D2L members: Brian Cepuran, VP, D2L Labs and Rose Kocher, Director, Grant & Research Programs, for their guidance in the project and the feedback on the paper. The authors would also like to acknowledge a support from Killam Predoctoral Scholarship.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Magdalena Jankowska
    • 1
    Email author
  • Colin Conrad
    • 1
  • Jabez Harris
    • 1
  • Vlado Kešelj
    • 1
  1. 1.Faculty of Computer ScienceDalhousie UniversityHalifaxCanada

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