Thomas, Pete; Smith, Neil and Waugh, Kevin
(2009).
![[img]](http://oro.open.ac.uk/style/images/fileicons/application_pdf.png)
|
PDF (Accepted Manuscript)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (103Kb) |
| URL: | http://www.ou.nl/Docs/Campagnes/ICDE2009/Papers/Fi... |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
The ability to draw diagrams in free-form is rarely found in e-assessment systems. This paper examines one crucial area which needs to be well understood if automatic marking of diagrams is to be feasible: the analysis of labels. Graph-based diagrams include geometrical elements of differing shapes connected by lines to carry the semantics of the domain being modelled. Some diagrams also use the
relative location of elements to express information. Labels play a central role in providing meaning both as identifiers, distinguishing between geometric elements, and the values of attributes of elements. Such information is central to the process of comparing two diagrams when marking student-drawn diagrams.
Student-drawn diagrams likely to contain errors – they are imprecise. The aim, therefore, is, in the presence of imprecision, to match a student diagram with a model solution and award a mark which is close to that which an expert human would give. This paper explores the specific problem of determining the similarity of labels in diagrams which has been successfully employed in marking student diagrams in a formative environment.
| Item Type: | Conference Item |
|---|---|
| Copyright Holders: | 2009 The Authors |
| Academic Unit/Department: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Related URLs: | |
| Item ID: | 19217 |
| Depositing User: | Kevin Waugh |
| Date Deposited: | 16 Dec 2009 10:44 |
| Last Modified: | 06 Aug 2016 10:00 |
| URI: | http://oro.open.ac.uk/id/eprint/19217 |
| Share this page: |     |
Download history for this item
These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.