Automated Essay Evaluation Based on Fusion of Fuzzy Ontology and Latent Semantic Analysis

Abstract

New learning researches proved that creativity is an essential concern in the arena of education. The best means to evaluate learning outcomes and students’ creativity is essay questions. However, to evaluate these questions is a time-consuming task and subjectivity in scoring assessments remains inevitable. Automated essay evaluation systems (AEE) provide a cost-effective and consistent alternative to human marking. Therefore, numerous automatic essay-grading systems have been developed to lessen the demands of manual essay grading. However, these systems concentrate on syntax and vocabulary, and no consideration is paid to the semantic and coherence of the essay. Moreover, few of the existing systems are able to give informative feedback that is based on extensive domain knowledge to students. In this paper, a system is evolved that uses latent semantic analysis (LSA) and fuzzy ontology to evaluate essays, where LSA will be responsible for checking the semantic. Fuzzy ontology is used to check the consistency and coherence of the essay as it is the best way to overcome the vagueness of the language, and the system will also provide a score with feedback to the student. Experimental results were good in evaluating the essay syntactically and semantically.