Collaborative trails in e-learning environments

This deliverable focuses on collaboration within groups of learners, and hence collaborative trails. We begin by reviewing the theoretical background to collaborative learning and looking at the kinds of support that computers can give to groups of learners working collaboratively, and then look more deeply at some of the issues in designing environments to support collaborative learning trails and at tools and techniques, including collaborative filtering, that can be used for analysing collaborative trails. We then review the state-of-the-art in supporting collaborative learning in three different areas – experimental academic systems, systems using mobile technology (which are also generally academic), and commercially available systems. The final part of the deliverable presents three scenarios that show where technology that supports groups working collaboratively and producing collaborative trails may be heading in the near future

Visual Focus of Attention Actively Associates Relevancy in Eye Movements

Advancements in the studies of eye movements have excelled beyond frontiers and transited into the phase of next generation splendidly. The business applications, like online shopping, advertisement, web designing, search engine optimization, of eye movement studies in real world scenarios have started to dominate as well. Tracking of eye movements can communicate the underlying mechanism of visual perception and dynamics of humans’ cognition that are of prime concerns for a number of social, economic, and scientific purposes. In this study, we conducted a series of eye tracking experiments to verify our hypothesis that during human eye movements, the visual focus of attention dynamically associated relevant constituents of artistic portrait. We collected the eye movement data of participants who regarded artistic portraits during active viewing. The trails produced from eye tracking system during portrait viewing traced connected focuses of attention in eye movements based on relevancy in visual contexts. These experimental facts validated the hypothesis that visual focus of attention actively associated relevancy in eye movements

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Web navigation for individuals with dyslexia: An exploratory study

In this paper, we present an exploratory study of the web navigation experiences of dyslexic users. Findings indicate that dyslexics exhibit distinctive web navigation behaviour and preferences. We believe that the outcomes of this study add to our understanding of the particular needs of this web user population and have implications for the design of effective navigation structures

Replication of the Climbing Post on Mount Arjuno Using Augmented Reality (AR) With the Open Asset Import Library Method: Replikasi Pos Pendakian Di Gunung Arjuno Menggunakan Augmented Reality (AR) Dengan Metode Open Asset Import Library

Mount Arjuno is a 3,339 meter high cone-shaped volcano located in East Java, Indonesia. At this time, information about climbers that is spread in online media makes it easy, there are many features that can be used to find climbing information on Mount Arjuno. Making this Arjuno augmented reality application uses the Rapid Application Development model with the main goal of producing high quality and quantity. Where this method places more emphasis on working on application software and user feedback in the planner. And testing for the tracking distance of the camera to the marker, to ensure the distance that can be traveled by the camera when scanning objects to targets. By creating an android application that uses the Marker Based Tracking method which can assist climbers in choosing hiking trails on Mount Arjuno so that climbers know the distance of the path traveled when climbing