EDM12.pdf (396.05 kB)
Using edit distance to analyse errors in a natural language to logic translation corpus
presentation
posted on 2023-06-08, 12:17 authored by Dave Barker-Plummer, Robert Dale, Richard CoxWe have assembled a large corpus of student submissions to an automatic grading system, where the subject matter involves the translation of natural language sentences into propositional logic. Of the 2.3 million translation instances in the corpus, 286,000 (approximately 12%) are categorized as being in error. We want to understand the nature of the errors that students make, so that we can develop tools and supporting infrastructure that help students with the problems that these errors represent. With this aim in mind, this paper describes an analysis of a significant proportion of the data, using edit distance between incorrect answers and their corresponding correct solutions, and the associated edit sequences, as a means of organising the data and detecting categories of errors. We demonstrate that a large proportion of errors can be accounted for by means of a small number of relatively simple error types, and that the method draws attention to interesting phenomena in the data set.
History
Publication status
- Published
Page range
134-141Presentation Type
- paper
Event name
The 5th International Conference on Educational Data Mining (EDM 2012)Event location
Chania, GreeceEvent type
conferenceEvent date
19-21st JuneDepartment affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2012-08-22Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC