Advances in ubiquitious and mobile technologies have facilitated learners to continue their learning outside their classrooms, when and where they desire. Learners are now able to access their learning resources and interact with their peers and teachers through technology. The design and creation of such learning spaces pose many challenges. The learner’s context defines the needs of the learn...

There is an extensive body of work on Intelligent Tutoring Systems: computer environments for education, teaching and training that adapt to the needs of the individual learner. Work on personalisation and adaptivity has included research into allowing the student user to enhance the system’s adaptivity by improving the accuracy of the underlying learner model. Open Learner Modelling, where the...

Background: The present study aimed to investigate and rank the effective success factors for e-learning based on the perspectives of the faculty members, students, and technical specialists of Tehran University of Medical Sciences, Tehran, Iran. Methods: This descriptive survey was conducted using the qualitative-quantitative method. At the first stage of the qualitative approach, 15 specialis...

The Learner Model of an Intelligent Tutoring System (ITS) may be made visible (opened) to its users. An Open Learner Model (OLM) may also become a learning resource in its own right, independently of an ITS. OLMs offer potential for learner reflection and support to metacognitive skills such as self-assessment, in addition to improving learner model accuracy. This paper describes an evaluation ...

Learners who use educational applications need to get suitable learning material in their concerned domain. However, their level of knowledge, preferences and interests are different. The e-learning system should be able to deliver suitable learning materials based on learner’s preferences and knowledge. The solution is knowledge based personalized model-driven approach. The learner-model and d...