One of the most important features which e-learning tools and environments must possess within the scope of lifelong learning is self-directed learning, which can be considered as a form of self-learning. The aim of this study was to determine, based on the views and recommendations of experts, interface design principles for the development of…

This study examines the relationships between cognitive styles of field dependent learners with their attitudes towards e-learning (distance education) and instructional behavior in e-learning instruction. The Group Embedded Figures Test (GEFT) and the attitude survey (for students' preferences) towards e-learning instruction as distance education…

The majority of adaptive and intelligent tutoring systems (AITS) are dedicated to a specific domain, allowing them to offer accurate models of the domain and the learner. The analysis produced from traces left by the users is didactically very precise and specific to the domain in question. It allows one to guide the learner in case of difficulty…

Implementing Web-based educational environment requires not only developing appropriate architectures, but also incorporating human factors considerations. User interface becomes the major channel to convey information in e-learning context: a well-designed and friendly enough interface is thus the key element in helping users to get the best…

This paper attempts to harness the opportunities for mobility and the new user interfaces that handheld touch screen devices offer, in a non-formal learning context, with a view to developing spatial ability. This research has addressed two objectives: first, analyzing the effects that training can have on spatial visualisation using the…

Purpose: The purpose of this paper is to analyze the usability of a remote learning system in its initial development phase, using a quantitative usability evaluation method through Markov models. Design/methodology/approach: The paper opted for an exploratory study. The data of interest of the research correspond to the possible accesses of users…

In this paper, we present a data-based user modeling framework that uses both unsupervised and supervised classification to build student models for exploratory learning environments. We apply the framework to build student models for two different learning environments and using two different data sources (logged interface and eye-tracking data).…