Assessing Students' Answers to Open Questions

Abstract

A number of Learning Management Systems (LMSs) exist on the market today. A subset of a LMS is the component in which student assessment is managed. In some forms of assessment, such as open questions, the LMS is incapable of evaluating the students’ responses and therefore human intervention is necessary. This study leverages the research conducted in recent studies in the area of Natural Language Processing, Information Extraction and Information Retrieval in order to provide a fair, timely and accurate assessment of student responses to open questions based on the semantic meaning of those responses. A component-based system utilizing a Text Pre-Processing phase and a Word/Synonym Matching phase has been developed to automate the open question assessment process. A small sample of student responses were tested against the system revealing areas in which the system could be improved.