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Prior knowledge is often argued to be an important determinant in hypermedia learning, and may be thought of as including two important elements: domain expertise and system expertise. However, there has been a lack of research considering these issues together. In an attempt to address this shortcoming, this paper presents a study that examines how domain(More)
South Africa, and the PhD degree, also in Computer Science, from the University of Reading in the United Kingdom. His research interests span multimedia (especially perpetual aspects), Quality of Service, as well as computer networking and security issues. He is a member of the IEEE. His home page is at Her major research interests focus on hypermedia-based(More)
Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital(More)
This study introduces the development of a Web-based assessment system, the Web-based Assessment and Test Analyses (WATA) system, and examines its impacts on teacher education. The WATA system is a follow-on system, which applies the Triple-A Model (assembling, administering, and appraising). Its functions include (1) an engine for teachers to administer(More)
Spatial ability is a critical skill in geometric learning. Several studies investigate how to use digital games to improve spatial abilities. However, not every learner favors this kind of support. To this end, there is a need to examine how human factors affect learners' reactions to the use of a digital game to support geometric learning. In this vein,(More)
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Adaptive Hypermedia systems are becoming more important in our everyday activities and users are expecting more intelligent services from them. The key element of a generic adaptive hypermedia system is the user model. Traditional machine learning techniques used to create user models are usually too rigid to capture the inherent uncertainty of human(More)