This chapter presents an adaptive predictive model for a student modeling prediction task in the context of an adaptive educational hypermedia system (AEHS). The task, that consists in determining what kind of learning resources are more appropriate to a particular learning style, presents two issues that are critical. The first is related to the uncertainty of the information about the student...

This paper reports on action research activities during 2000-2001, involving first-year engineering students in an extended study programme of the School of Engineering at the University of Pretoria. Students in the participating group were enrolled for a support course aimed at facilitating the fundamental concepts underpinning a study in calculus as well as complementing the development of pe...

The article encompasses the theoretical background and practical concept of teaching/learning through online courses as an example of smart solution of e-learning system adjusting to individual learning preferences, including students’ reflection on the individualized online instruction. First, the ‘Unlocking the Will to Learn’ concept by C.A. Johnston is introduced and implemented in the resea...

Recently, research in individual differences and in particular, learning and cognitive style, has been used as a basis to consider learner preferences in a web-based educational context. Modelling style in a web-based learning environment demands that developers build a specific framework describing how to design a variety of options for learners with different approaches to learning. In this p...

Background: In the face of severe faculty shortages in constrained countries' resource-, electronic learning (elearning) was providing the chance for improving access to nursing education. Utilization of elearning can result in greater educational opportunities for students, and enhancing faculty effectiveness and efficiency. Learning styles could be unique to every individual. Therefore, it is...

individuals act differently in learning, this being due to the difference in learning styles of persons. learning styles affect optimum learning and the efficiency in educational output. therefore an identification of the learning styles of learners as related to teaching and learning activities is most important. the purpose of this study was to investigate the learning styles of agricultural ...

Personalized access to e-learning contents is based on suggesting routes to users considering their preferences. Recent studies show that navigation styles can content much of the information related to cognitive learning styles and preferences. These navigation styles can be defined by means of different parameters. In this work, we focus on the parameter that defines if the navigation style i...

Experiential learning theory (ELT), a theory developed by David Kolb that considers experience to be very important for learning, classifies learners into four categories: Divergers, Assimilators, Convergers, and Accommodators. Kolb used his Learning Style Inventory (LSI) to validate ELT. Knowing the learning styles of students facilitates their understanding of themselves and thereby increases...