Error analysis

Shaalan, K., M. Magdy, and A. Fahmy, "Morphological Analysis of Ill-formed Arabic Verbs for Second Language Learners", Applied Natural Language Processing: Identification, Investigation and Resolution, issue Hershey, PA, USA, PA, USA, IGI Global, pp. 1 - 659, 2012. Abstract978-1-60960-741-8.ch022.pdf

Arabic is a language of rich and complex morphology. The nature and peculiarity of Arabic make its morphological and phonological rules confusing for second language learners (SLLs). The conjugation of Arabic verbs is central to the formulation of an Arabic sentence because of its richness of form and meaning. In this research, we address issues related to the morphological analysis of ill-formed Arabic verbs in order to identify the source of errors and provide an informative feedback to SLLs of Arabic. The edit distance and constraint relaxation techniques are used to demonstrate the capability of the proposed system in generating all possible analyses of erroneous Arabic verbs written by SLLs. Filtering mechanisms are applied to exclude the irrelevant constructions and determine the target stem which is used as the base for constructing the feedback to the learner. The proposed system has been developed and effectively evaluated using real test data. It achieved satisfactory results in terms of the recall rate.

Shaalan, K., and H. Talhami, "Arabic Error Feedback in an Online Arabic Learning System", Advances in Natural Language Processing, Research in Computing Science (RCS) Journal, vol. 18, pp. 203-212, 2006. Abstracterror_feedback_2006.pdf

Arabic is a Semitic language that is rich in its morphology and syntax. The very numerous and complex grammar rules of the language could be confusing even for Arabic native speakers. Many Arabic intelligent computer assisted language-learning (ICALL) systems have neither deep error analysis nor sophisticated error handling. In this paper, we report an attempt at developing an error analyzer and error handler for Arabic as an important part of the Arabic ICALL system. In this system, the learners are encouraged to construct sentences freely in various contexts and are guided to recognize by themselves the errors or inappropriate usage of their language constructs. We used natural language processing (NLP) tools such as a morphological analyzer and a syntax analyzer for error analysis and to give feedback to the learner.
Furthermore, we propose a mechanism of correction by the learner, which allows the learner to correct the typed sentence independently. This will result in the learner being able to figure out what the error is. Examples of error analysis and error handling will be given and will illustrate how the system works.

Magdy, M., K. Shaalan, and A. Fahmy, "Lexical Error Diagnosis for Second Language Learners of Arabic", The Seventh Conference on Language Engineering, Egyptian Society of Language Engineering (ELSE), Cairo, Egypt, Dec., 2007. Abstractlexical_error_diagnosis_nle.pdf

This paper addresses the development of an automated lexical error diagnosis system, which helps Arabic second language learners to learn well-formed weak verbs. The learners are encouraged to produce input freely in various situations and contexts and guided to recognize by themselves the erroneous or inappropriate functions of their misused expressions. In this system, we successfully used constraint relaxation and edit-distance techniques to provide error-specific diagnosis and feedback to second language learners of Arabic. We demonstrated the capabilities of these techniques to diagnose errors related to the Arabic weak verb which is formed using complex morphological rules. Furthermore, the developed system allows for individualization of the learning process by providing feedback that conforms to the learner’s expertise. Inexperienced learners might require detailed instruction while experienced learners benefit from higher level reminders and explanations.

Shaalan, K., and H. Talhami, "Error analysis and handling in Arabic ICALL systems", IASTED International Conference on Artificial Intelligence and Applications (AIA 2006), Innsbruck, Austria, ACTA Press, pp. 109–114, Febrauray, 2006. Abstracterror_analysis_icall.pdf

Arabic is a Semitic language that is rich in its morphology and syntax. The very numerous and complex grammar rules of the language could be confusing even for Arabic native speakers. Many Arabic intelligent computer-assisted language-learning (ICALL) systems have neither deep error analysis nor sophisticated error handling. In this paper, we report an attempt at developing an error analyzer and error handler for Arabic as an important part of the Arabic ICALL system. In this system, the learners are encouraged to construct sentences freely in various contexts and are guided to recognize by themselves the errors or inappropriate usage of their language constructs. We used natural language processing (NLP) tools such as a morphological analyzer and a syntax analyzer for error analysis and to give feedback to the learner. Furthermore, we propose a mechanism of correction by the learner, which allows the learner to correct the typed sentence independently. This will result in the learner being able to figure out what the error is. Examples of error analysis and error handling will be given and will illustrate how the system works.