Analyze and evaluate student responses to open-ended questions using natural language processing (NLP)

Abstract

Using Natural Language Processing (NLP) to analyse and evaluate student responses to open-ended questions marks a significant advancement in educational technology. Lots of examination testing require manual evaluation and rating, which is time-consuming and potentially error-prone. Natural language processing (NLP) should be used to automatically analyse free-text answers to support the review process .

Several studies have demonstrated the efficacy and challenges of using NLP in educational settings. For example, research on automated essay scoring systems has shown that they can provide scores comparable to human graders in terms of reliability and validity. However, these studies also highlight the importance of combining NLP tools with human oversight to ensure fair and accurate assessments.