A semantic assessment framework for e-learning systems

Abstract

Semantic web technologies are applied in a wide spectrum of applications including search engines, web services discovery and composition, semantic tags and electronic assessment of e-learning systems. Recently, the field of electronic assessment has grabbed the attention of many researchers. Electronic assessment is a real challenge taking to consideration the diversity of question types. E-assessment of answers to open questions has created new challenges regarding extracting students' answers using natural language processing techniques and infer new knowledge using description logic reasoning. To be able to automate the process of assessing the students' answers, they have to be annotated with semantics. This paper presents a thorough survey of significant research efforts that adopt semantic annotation to enhance the process of e-assessment. Moreover, in this paper, we propose a semantic-based framework that automates the process of electronically assessing the answers of questions on e-learning systems based on their semantic descriptions.