Enacting textual entailment and ontologies for automated essay grading in chemical domain

TL;DR

This paper presents an automated essay grading system for chemistry that uses ontologies and textual entailment to compare student answers with model answers derived from domain knowledge.

Contribution

It introduces a novel approach combining ontologies and textual entailment for automated essay assessment in specialized scientific domains.

Findings

Effective comparison of student and model answers using textual entailment

Validated system achieves promising accuracy on chemistry essays

Integrates domain ontologies to enhance grading consistency

Abstract

We propose a system for automated essay grading using ontologies and textual entailment. The process of textual entailment is guided by hypotheses, which are extracted from a domain ontology. Textual entailment checks if the truth of the hypothesis follows from a given text. We enact textual entailment to compare students answer to a model answer obtained from ontology. We validated the solution against various essays written by students in the chemistry domain.