Authors:
Patrick Siehndel
1
;
Ricardo Kawase
1
;
Bernardo Pereira Nunes
2
and
Eelco Herder
1
Affiliations:
1
Leibniz University Hannover, Germany
;
2
PUC-Rio, Brazil
Keyword(s):
Learning Support, Learning Pathways, Digital Libraries.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Data Engineering
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Metadata and Metamodeling
;
Ontologies and the Semantic Web
;
Recommendation Systems
;
Society, e-Business and e-Government
;
Software Agents and Internet Computing
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
Abstract:
Learning material usually has a logical structure, with a beginning
and an end, and lectures or sections that build upon one another. However, in informal
Web-based learning this may not be the case. In this paper, we present a method
for automatically calculating a tentative order in which objects should be
learned based on the estimated complexity of their contents. Thus, the proposed
method is based on a process that enriches textual objects with links to
Wikipedia articles, which are used to calculate a complexity score for each
object. We evaluated our method with two different datasets: Wikipedia articles
and online learning courses. For Wikipedia data we achieved correlations
between the ground truth and the predicted order of up to 0.57 while for
subtopics inside the online learning courses we achieved correlations of 0.793.