Analysing Semantic Flow in Academic Writing

  • Authors:
  • Stephen T. O'Rourke;Rafael A. Calvo

  • Affiliations:
  • School of Electrical and Information Engineering, The University of Sydney;School of Electrical and Information Engineering, The University of Sydney

  • Venue:
  • Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
  • Year:
  • 2009

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Abstract

Many approaches have been proposed for providing feedback in academic writing, however, few of them are visually based. We describe a novel visualisation method for providing feedback to support formative essay assessment. The visualisation method makes use of text mining techniques to provide insight on the semantics of the topics in an essay. We propose that visualisation can be used to mitigate many of the problems associated with the subjectivity of formative essay assessment. The visualisation method involves a process of non-negative matrix factorisation (NMF), to uncover topics in an essay, followed by multidimensional scaling, to map the essay topics to a 2-dimensional representation. We evaluate our approach with a subset of the British Academic Written English corpus of 2761 assignments written by university students.