E-learning systems are changing education and organizational training considerably. With the advancement of online-based learning systems, learner control of the instructional process has emerged as a decisive factor inherent to technology-based learning. However, the conceptual work on the role of learner control in e-learning has not advanced sufficiently to predict how learner control impact...

Electronic learning systems and virtual learning environments for education or training are increasingly gaining attention in educational organizations as well as in industry. An important dimension in the evaluation of a virtual learning environment is the assessment of e-learner satisfaction. Critical elements in the assessment procedure are the learner interface, the course content, the acce...

Learners are assessed by several systems during their lifelong learning. Those systems can maintain fragments of information about a learner derived from his learning performance and/or assessment in that particular system. Customization services would perform better if they would be able to exchange as many relevant fragments of information about the learner as possible. This paper presents th...

|We propose a new method of classiication built as a cascade of a distributed learner and a local learner. The distributed learner generalizes to learn the \rule" and the local learner learns the \exceptions" not covered by the \rule." We show how such a system can be trained using cross-validation. We use a multi-layer perceptron with sigmoidal hidden units as the rule-learner and a k-nearest ...

Emerging MOOC platforms capture huge amounts of learner data. This paper presents our MOOClm platform, for transforming data from MOOCs into independent learner models that can drive personalisation and support reuse of the learner model, for example in an Open Learner Model (OLM). We describe the MOOClm architecture and demonstrate how we have used it to build OLMs.

We consider open learner models (OLM) with reference to adaptive navigation support and learner control. Our purpose is to assess the potential of a greater range of OLMs in adaptive educational hypermedia. We introduce five OLMs, discuss how these might be applied, and present learner reactions.