ReaderBench Learns Dutch: Building a Comprehensive Automated Essay Scoring System for Dutch Language

Mihai Dascalu, W. Westera, Stefan Ruseti, Stefan Trausan-Matu, H.J. Kurvers

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

Automated Essay Scoring has gained a wider applicability and usage with the integration of advanced Natural Language Processing techniques which enabled in-depth analyses of discourse in order capture the specificities of written texts. In this paper, we introduce a novel Automatic Essay Scoring method for Dutch language, built within the Readerbench framework, which encompasses a wide range of textual complexity indices, as well as an automated segmentation approach. Our method was evaluated on a corpus of 173 technical reports automatically split into sections and subsections, thus forming a hierarchical structure on which textual complexity indices were subsequently applied. The stepwise regression model explained 30.5% of the variance in students’ scores, while a Discriminant Function Analysis predicted with substantial accuracy (75.1%) whether they are high or low performance students.
Original languageEnglish
Title of host publicationArtificial Intelligence in Education
Subtitle of host publication18th International Conference, AIED 2017, Wuhan, China, June 28 – July 1, 2017, Proceedings
EditorsElisabeth André , Ryan Baker, Xiangen Hu, Ma. Mercedes T. Rodrigo , Benedict du Boulay
PublisherSpringer International Publishing AG
Pages52-63
Edition1
ISBN (Electronic)978-3-319-61425-0
ISBN (Print)978-3-319-61424-3
DOIs
Publication statusPublished - 2017
EventArtificial Intelligence in Education: 18th International Conference, AIED 2017, Wuhan, China, June 28 – July 1, 2017 - Wuhan, China
Duration: 28 Jun 20171 Jul 2017
http://119.97.166.163/

Publication series

SeriesLecture Notes in Artificial Intelligence (subseries)
Volume10331

Conference

ConferenceArtificial Intelligence in Education
Abbreviated titleAIED 2017
CountryChina
CityWuhan
Period28/06/171/07/17
Internet address

Keywords

  • Automated essay scoring
  • textual complexity assessment
  • academic performance
  • Readerbench framework
  • Dutch semantic models
  • Games
  • Learning

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    Cite this

    Dascalu, M., Westera, W., Ruseti, S., Trausan-Matu, S., & Kurvers, H. J. (2017). ReaderBench Learns Dutch: Building a Comprehensive Automated Essay Scoring System for Dutch Language. In E. André , R. Baker, X. Hu, M. M. T. Rodrigo , & B. du Boulay (Eds.), Artificial Intelligence in Education: 18th International Conference, AIED 2017, Wuhan, China, June 28 – July 1, 2017, Proceedings (1 ed., pp. 52-63). [5] Springer International Publishing AG. Lecture Notes in Artificial Intelligence (subseries), Vol.. 10331 https://doi.org/10.1007/978-3-319-61425-0_5