Title
Personalising learning through prerequisite structures derived from concept maps
Abstract
Current developments in Web-based learning are especially focusing on personalising learning by adapting the learning process to the student's prior knowledge, learning progress, learning goal, and possibly further characteristics. For creating personalised learning paths and efficiently uncovering the knowledge or competence level of a learner, prerequisite structures on learning objects and assessment problems, or on skills underlying those entities, are extremely useful. Knowledge Space Theory and its competence-based extensions provide a sound mathematical psychological framework that is based upon such prerequisite structures. Concept maps or semantic networks representing domain ontologies offer a valuable source of information for establishing prerequisite structures. This paper outlines approaches on the use of concept maps for deriving prerequisite relations and structures, which can subsequently serve as a basis for implementing personalisation and adaptivity in Web-based learning.
Year
DOI
Venue
2007
10.1007/978-3-540-78139-4_5
ICWL
Keywords
Field
DocType
competence level,personalising learning,current development,prerequisite structure,web-based learning,assessment problem,competence-based extension,knowledge space theory,prerequisite relation,prior knowledge,concept map,personalisation,semantic network
Robot learning,Ontology (information science),Concept map,Computer science,Knowledge management,Semantic network,Knowledge space theory,Personalization
Conference
Volume
ISSN
ISBN
4823
0302-9743
3-540-78138-2
Citations 
PageRank 
References 
6
0.63
3
Authors
2
Name
Order
Citations
PageRank
Christina M. Steiner18314.93
Dietrich Albert243063.65