Research and design challenges for developing personalised eLearning systems

While E-learning technologies are continuously developing, there are number of emerging issues and challenges that have significant impact on e-learning research and design. These include educational, technological, sociological, and psychological viewpoints. The extant literature points out that a large number of existing E-learning systems have problems with offering reusable, personalized and learner-centric content. While developers are placing emphasis on the technology aspects of e-learning, critical conceptual and pedagogical issues are often ignored. This paper will reports on our research in design and development of personalised e-learning systems and some of the challenges and issues faced.

Evaluation of a suitable learning style for iLearn: a personalised e-learning platform

Brusilovsky and Millan (2007) state that learning styles are typically defined as the way people prefer to learn. Learning styles and how we learn is a vast research area and many research projects (SMILE, INSPIRE, iWeaver amongst others) attempt to incorporate these learning styles into e-Learning systems. This paper describes commonly used learning styles and how they are currently being used within the area of adaptive e-Learning. This work also builds upon current research and evaluates learning styles using criteria proposed by Sampson and Karagiannidis (2004) in order to select a suitable learning methodology for the iLearn e-Learning platform. The Sampson and Karagiannidis (2004) criteria is adapted for the purpose of the research and describes the measurability, time effectiveness and descriptiveness and prescriptiveness of the specific learning style. A suitable learning style for the iLearn e-Learning platform is then proposed within the paper and finally the research briefly introduces how the chosen learning style will be used for the proposed e-Learning platform.

Personalised e-learning, semantic web and learning ontologies

Kurzel(2004) points out that researchers in e-learning and educational technologists, in a quest to provide improved Learning Environments (LE) for students are focusing on personalising the experience through a Learning Management System (LMS) that attempts to tailor the LE to the individual (see amongst others Eklund & Brusilovsky, 1998; Kurzel, Slay, & Hagenus, 2003; Martinez,2000; Sampson, Karagiannidis, & Kinshuk, 2002; Voigt & Swatman; 2003). According to Kurzel (2004) this tailoring can have an impact on content and how it’s accessed; the media forms used; method of instruction employed and the learning styles supported. This project is aiming to move personalisation forward to the next generation, by tackling the issue of Personalised e-Learning platforms as pre-requisites for building and generating individualised learning solutions. The proposed development is to create an e-learning platform with personalisation built-in. This personalisation is proposed to be set from different levels of within the system starting from being guided by the information that the user inputs into the system down to the lower level of being set using information inferred by the system’s processing engine. This paper will discuss some of our early work and ideas.

Creating a suitable and successful solution for the integration of podcasting and vidcasting in a higher education e-learning environment

A small research project is currently taking place within a department of the University of Greenwich. The project involves using current technology (Apple’s xServe, iPhones, iPod touch, Podcast Producer application and some 3rd party capture software) with the intention to provide a solution for quick and simple podcasting. This paper also aims to investigate the use of podcasting to help promote and extend the e-learning provision within the school. In short this project aims to justify the use of podcasting as a teaching and learning tool to help enhance student learning while identifying the most appropriate manner to integrate podcasting within an e-learning environment.

The collection of pre-evacuation times from evacuation trials involving a Hospital Outpatient area and a University Library facility

This paper presents data relating to occupant pre-evacuation times from a university and a hospital outpatient facility. Although the two structures are entirely different they do employ relatively similar procedures: members of staff sweeping areas of the structure to encourage individuals to evacuate. However, the manner in which the dependent population reacts to these procedures is quite different. In the hospital case the patients only evacuated once a member of the nursing staff had instructed them to do so while in the university evacuation the students were less dependent upon the actions of the staff with over 50% of them evacuating with no prior prompting. Although this data may be useful in a variety of areas, it was collected primarily for use within evacuation models.