Title :
Intelligent short text assessment in eMax
Author :
Sima, D. ; Schmuck, B. ; Szollosi, S.
Author_Institution :
Budapest Tech., Budapest
Abstract :
Rapidly increasing student numbers and spreading distance learning systems strengthen the urgent need for effective knowledge assessment systems (KAS\´s). Recent KAS\´s have however, the deficiency of not providing intelligent assessment modules for eg the evaluation of freely formulated short answers including a few sentences or partially solved mathematical problems. The eMax KAS, developed at the Intelligent Knowledge Management Innovation Center of IBM Hungary and the John von Neumann Faculty of Informatics at Budapest Tech, aims to provide these capabilities. Our paper gives an introduction to the intelligent assessment of short texts component of eMax by presenting the approach used for the formal description of the "answer space" defined as well as the methods chosen for the syntactic analysis, semantic analysis and scoring. The a version of eMax is now completed and is in testing.
Keywords :
distance learning; educational administrative data processing; knowledge based systems; semantic networks; distance learning systems; eMax KAS; intelligent short text assessment; knowledge assessment systems; semantic analysis; syntactic analysis; Computer aided instruction; Informatics; Intelligent systems; Knowledge management; Natural language processing; Performance evaluation; Research and development; System testing; Technological innovation; Tree graphs; Answer Space; Intelligent Assessment Systems; Knowledge Assessment Systems; Semi-automatic assessment; Short Text Evaluation;
Conference_Titel :
AFRICON 2007
Conference_Location :
Windhoek
Print_ISBN :
978-1-4244-0987-7
Electronic_ISBN :
978-1-4244-0987-7
DOI :
10.1109/AFRCON.2007.4401593