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A new method for parsing student text to support computer-assisted assessment of free text answers
conference contribution
posted on 2009-04-24, 14:00 authored by Elizabeth Guest, Sally BrownDue to current trends in staff-student ratios, the assessment burden on staff
will increase unless either students are assessed less, or alternative
approaches are used. Much research and effort has been aimed at automated
assessment but to date the most reliable method is to use variations of
multiple choice questions. However, it is hard and time consuming to design
sets of questions that foster deep learning. Although methods for assessing
free text answers have been proposed, these are not very reliable because
they either involve pattern matching or the analysis of frequencies in a “bag of
words”.
The first step towards automatic marking of free text answers by comparing
the meaning of student answers with a single model answer is to parse the
student work. However, because not all students are good at writing
grammatically correct English, it is vital that any parsing algorithm can handle
ungrammatical text. In this paper, we present preliminary results of using a
relatively new linguistic theory, Role and Reference Grammar, to parse
student texts and show that ungrammatical sentences can be parsed.
History
School
- University Academic and Administrative Support
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- Professional Development
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- CAA Conference
Citation
GUEST, E. and BROWN, S., 2007. A new method for parsing student text to support computer-assisted assessment of free text answers. IN: Khandia, F. (ed.). 11th CAA International Computer Assisted Conference: Proceedings of the Conference on 10th & 11th July 2007 at Loughborough University, Loughborough, pp. 223-236.Publisher
© Loughborough UniversityVersion
- VoR (Version of Record)
Publication date
2007Notes
This is a conference paper.ISBN
0953957268Language
- en
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