Automated Grading of Students’ Short Answers Using Language Models

Abstract

Methods of assessing student answers using language models are currently being studied by various specialists. The results of automated assessment depend on the subject area and characteristics of the academic discipline. This paper analyzes students’ answers received during a Computer Graphics and Design course. It is proposed to determine the cosine similarity of document vectors obtained using language models and refine the estimates by checking keywords. The results obtained can be used for preliminary assessment of students’ answers and form the basis for further research.