Computerized evaluation of subjective answers using hybrid technique

Abstract

To ensure quality in education, this paper proposes and implements a hybrid technique for computerized evaluation of subjective answers containing only text. The evaluation is performed using statistical techniques—Latent semantic analysis (LSA) and bilingual evaluation understudy (BLEU) along with soft computing technique, fuzzy logic. LSA is used to identify the semantic similarity between two concepts. BLEU helps prevent overrating a student answer. Fuzzy logic is used to map the outputs of LSA and BLEU. The hybrid technique is implemented using Java programming language, MatLab, Java open source libraries, and WordNet—a lexical database of English words. A database of 50 questions from different subjects of Computer Science along with answers is collected for testing purpose. The accuracy of the results varied from 0.72 to 0.99. The results are encouraging when compared with existing techniques. The tool can be used as preliminary step for evaluation.