Enhancing NLP-Based Educational Assessment: A Node-Based Graph Approach for Analyzing Freeform Student Texts

This paper introduces a software tool designed to elevate the assessment of student-submitted freeform text through a node-based graph approach leveraging large language models and customizable natural language processing (NLP) techniques. It combines directed feedback for students with a scoring system to provide a comprehensive understanding of the submitted responses. The node-based approach further allows educators to create tailored assignments with reusable evaluation strategies. This tool aims to scale up individualized feedback efficiently, addressing the challenges posed by large student numbers, thus alleviating the time investment of educators. This capability is particularly vital in scenarios where manual evaluation of numerous freeform submissions is impractical or unfeasible. This paper focuses on the software’s architecture and the integration of node-based NLP practices in freeform text analysis.