Back to Search
Start Over
Grammatical error diagnosis in fluid construction grammar: a case study in L2 Spanish verb morphology
- Source :
- Vrije Universiteit Brussel
- Publication Year :
- 2012
- Publisher :
- Informa UK Limited, 2012.
-
Abstract
- Construction grammar (CG) has been proposed as an adequate grammatical formalism for building intelligent language tutoring systems because it is highly compatible with the learning strategies observed in Second Language Learning. Unfortunately, the lack of computational CG implementations has made it impossible in the past to corroborate these proposals with actual language tutoring prototypes. However, recent advances in Fluid Construction Grammar (FCG) now offer exciting new ways of operationalizing robust and open-ended language processing within a construction grammar approach. This paper demonstrates its adequacy for CALL applications through a case study on error diagnosis in the domain of Spanish tense, aspect and modal morphology. The performance of the FCG tutor is tested on the Spanish Learner Language Oral Corpus (SPLOCC 2). This first FCG Spanish error diagnostic prototype achieves an accuracy of 70% on a total of 500 conjugation errors in four oral tasks carried out by 20 low intermediate and 20advanced English learners of Spanish. Follow- up experiments will test this prototype on larger learner corpora of differing proficiency levels.
- Subjects :
- Linguistics and Language
Computer science
media_common.quotation_subject
computer.software_genre
Language and Linguistics
Morpheme
Language proficiency
TUTOR
error analysis
computer.programming_language
media_common
Grammar
business.industry
Construction grammar
Linguistics
Computer Science Applications
L2 Spanish verb morphology
Modal
Task analysis
Artificial intelligence
Computational linguistics
business
computer
Natural language processing
Fluid Construction Grammar
Robust parsing
Subjects
Details
- ISSN :
- 17443210 and 09588221
- Volume :
- 27
- Database :
- OpenAIRE
- Journal :
- Computer Assisted Language Learning
- Accession number :
- edsair.doi.dedup.....571215aa8930730e0c5752d6843d813c