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Accepting Inferred Student Solutions by Tutoring System in an Ill-Defined Domain
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 94 - Number 18 |
| Year of Publication: 2014 |
| Authors: Hameedullah Kazi, Asia Kainat Awan |
10.5120/16457-5544
|
Hameedullah Kazi, Asia Kainat Awan . Accepting Inferred Student Solutions by Tutoring System in an Ill-Defined Domain. International Journal of Computer Applications. 94, 18 ( May 2014), 8-11. DOI=10.5120/16457-5544
Abstract
Intelligent Tutoring Systems have made great advances in providing assessment and useful feedback in domains with well-structured problems, where start state, rules, or goals of a problem are well formalized and used to reach an unambiguously correct or incorrect solution. The problems of ill-defined domain often possess multiple solutions. Plausible student solutions of ill-defined problems are deemed wrong by tutoring system if they do not match the known solution accepted by the system. This paper describes a mechanism and the results of a tutoring system in an ill-defined domain such as the English language, for accepting plausible student solutions for ill-defined problems. The WordNet is deployed as a knowledge base, which is a lexical resource of English language database. Semantic similarity measure technique uses WordNet ontology hierarchy to accept the student plausible solutions. The student solutions of cloze passages were evaluated by a group of English experts and compared against a semantic similarity measure. The experts agreed among themselves with a correlation of 0. 7 with p<0. 05. The correlation between semantic similarity and experts is 0. 58 with p<0. 05 to indicate valid hypothesis. The area under the curve of ROC is 0. 76.
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