EssayCritic: Writing to learn with a knowledge-based design critiquing system

Anders I. Mørch*, Irina Engeness, Victor C. Cheng, William K. Cheung, Kelvin C. Wong

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

23 Citations (Scopus)
25 Downloads (Pure)


This article presents a study of EssayCritic, a computer-based writing aid for English as a foreign language (EFL) that provides feedback on the content of English essays. We compared two feedback conditions: automated feedback from EssayCritic (target class) and feedback from collaborating peers (comparison class). We used a mixed methods approach to collect and analyze the data, combining interaction analysis of classroom conversations during the writing process and statistical analysis of students' grades. The grades of students in both classes improved from pre-test to post-test but in different ways. The students in the target class included more ideas (content) in their essays, whereas the students in the co mparison class put more emphasis on the organization of their ideas. We discuss our findings to identify strengths and weaknesses of our approach, and we end the paper by suggesting some directions for further research.

Original languageEnglish
Pages (from-to)213-223
Number of pages11
JournalEducational Technology and Society
Issue number2
Publication statusPublished - Apr 2017

Scopus Subject Areas

  • Education
  • Sociology and Political Science
  • Engineering(all)

User-Defined Keywords

  • Automated feedback
  • Collaboration
  • Decision tree learning
  • Design critiquing framework
  • English as a foreign language (EFL)
  • Essay writing
  • Learning analytics (LA)
  • Machine learning
  • Methods for using LA in EFL
  • peer feedback


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