Authors:
Olawande Daramola
;
Ibukun Afolabi
;
Ibidapo Akinyemi
and
Olufunke Oladipupo
Affiliation:
Covenant University, Nigeria
Keyword(s):
Ontology, Ontology-based Information Extraction, Automatic Essay Scoring, Subject-based Automatic Scoring.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Biomedical Engineering
;
Collaboration and e-Services
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Expert Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Natural Language Processing
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Pattern Recognition
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
The procedure for the grading of students’ essays in subject-based examinations is quite challenging particularly when dealing with large number of students. Hence, several automatic essay-grading systems have been designed to alleviate the demands of manual subject grading. However, relatively few of the existing systems are able to give informative feedbacks that are based on elaborate domain knowledge to students, particularly in subject-based automatic grading where domain knowledge is a major factor. In this work, we discuss the vision of subject-based automatic essay scoring system that leverages on semi-automatic creation of subject ontology, uses ontology-based information extraction approach to enable automatic essay scoring, and gives informative feedback to students.