Use this URL to cite or link to this record in EThOS:
Title: Computational support for learners of Arabic
Author: Al-Liabi, Majda Majeed
ISNI:       0000 0004 2733 6815
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2012
Availability of Full Text:
Access from EThOS:
Access from Institution:
This thesis documents the use of Natural Language Processing (NLP) in Computer Assisted Language Learning (CALL) and its contribution to the learning experience of students studying Arabic as a foreign language. The goal of this project is to build an Intelligent Computer Assisted Language Learning (ICALL) system that provides computational assistance to learners of Arabic by teaching grammar, producing homework and issuing students with immediate feedback. To produce this system we use the Parasite system, which produces morphological, syntactic and semantic analysis of textual input, and extend it to provide error detection and diagnosis. The methodology we adopt involves relaxing constraints on unification so that correct information contained in a badly formed sentence may still be used to obtain a coherent overall analysis. We look at a range of errors, drawn from experience with learners at various levels, covering word internal problems (addition of inappropriate affixes, failure to apply morphotactic rules properly) and problems with relations between words (local constraints on features, and word order problems). As feedback is an important factor in learning, we look into different types of feedback that can be used to evaluate which is the most appropriate for the aim of our system.
Supervisor: Ramsay, Allan Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Arabic Language ; aRaBCALL ; ICALL ; CALL ; Assessment ; Homework ; Feedback ; Evaluation ; Grammar ; Soft Parsing ; NLP ; HPSG ; Parasite ; Morphosyntax Error ; Parser ; Log File ; Classification of Learner Errors