Journal of Computer Science


Ali Muftah Ben Omran and Mohd Juzaiddin Ab Aziz

DOI : 10.3844/jcssp.2013.1369.1382

Journal of Computer Science

Volume 9, Issue 10

Pages 1369-1382


Automatic Essay Grading (AEG) system is defined as the computer technology that evaluates and grades written prose. The short essay answer, where the essay is written in short sentences where it has two types the open ended short answer and the close ended short answer where it is our research domain based on the computer subject. The Marking of short essay answers automatically is one of the most complicated domains because it is relying heavily on the semantic similarity in meaning refers to the degree to which two sentences are similar in the meaning where both used similar words in the meaning, in this case Humans are able to easily judge if a concepts are related to each other, there for is a problem when Student use a synonym words during the answer in case they forget the target answer and they use their alternative words in the answer which will be different from the Model answer that prepared by the structure. The Standard text similarity measures perform poorly on such tasks. Short answer only provides a limited content, because the length of the text is typically short, ranging from a single word to a dozen words. This research has two propose; the first propose is Alternative Sentence Generator Method in order to generate the alternative model answer by connecting the method with the synonym dictionary. The second proposed three algorithms combined together in matching phase, Commons Words (COW), Longest Common Subsequence (LCS) and Semantic Distance (SD), these algorithms have been successfully used in many Natural Language Processing systems and have yielded efficient results. The system was manually tested on 40 questions answered by three students and evaluated by teacher in class. The proposed system has yielded %82 correlation-style with human grading, which has made the system significantly better than the other state of the art systems.


© 2013 Ali Muftah Ben Omran and Mohd Juzaiddin Ab Aziz. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.