Chapter 1 : Learning Online

The OTiS (Online Teaching in Scotland) programme, run by the now defunct Scotcit programme, ran an International e-Workshop on Developing Online Tutoring Skills which was held between 8–12 May 2000. It was organised by Heriot–Watt University, Edinburgh and The Robert Gordon University, Aberdeen, UK. Out of this workshop came the seminal Online Tutoring E-Book, a generic primer on e-learning pedagogy and methodology, full of practical implementation guidelines. Although the Scotcit programme ended some years ago, the E-Book has been copied to the SONET site as a series of PDF files, which are now available via the ALT Open Access Repository. The editor, Carol Higgison, is currently working in e-learning at the University of Bradford (see her staff profile) and is the Chair of the Association for Learning Technology (ALT)

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

Learning design approaches for personalised and non-personalised e-learling systems

Recognizing the powerful role that technology plays in the lives of people, researchers are increasingly focusing on the most effective uses of technology to support learning and teaching. Technology enhanced learning (TEL) has the potential to support and transform students’ learning and allows them to choose when, where and how to learn. This paper describes two different approaches for the design of personalised and non-personalised online learning environments, which have been developed to investigate whether personalised e-learning is more efficient than non-personalised e-learning, and discuss some of the student’s experiences and assessment test results based on experiments conducted so far

Culture and E-Learning: Automatic Detection of a Users’ Culture from Survey Data

Knowledge about the culture of a user is especially important for the design of e-learning applications. In the experiment reported here, questionnaire data was used to build machine learning models to automatically predict the culture of a user. This work can be applied to automatic culture detection and subsequently to the adaptation of user interfaces in e-learning

Flexibility and Interaction at a Distance: A Mixed-Model Environment For Language Learning

This article reports on the process of design and development of two language courses for university students at beginning levels of competence. Following a preliminary experience in a low-tech environment for distance language learning and teaching, and a thorough review of the available literature, we identified two major challenges that would need to be addressed in our design: (1) a necessity to build sufficient flexibility into the materials to cater to a variety of learners' styles, interests and skill levels, therefore sustaining learners' motivation; and (2) a need to design materials that would present the necessary requisites of authenticity and interactivity identified in the examined literature, in spite of the reduced opportunities for face-to-face communication. In response to these considerations, we designed and developed learning materials and tasks to be distributed on CD-ROM, complemented by a WebCT component for added interactivity and task authenticity. Although only part of the original design was implemented, and further research is needed to assess the impact of our environment on learning outcomes, the results of preliminary evaluations are encouraging

Data mining technology for the evaluation of learning content interaction

Interactivity is central for the success of learning. In e-learning and other educational multimedia environments, the evaluation of interaction and behaviour is particularly crucial. Data mining – a non-intrusive, objective analysis technology – shall be proposed as the central evaluation technology for the analysis of the usage of computer-based educational environments and in particular of the interaction with educational content. Basic mining techniques are reviewed and their application in a Web-based third-level course environment is illustrated. Analytic models capturing interaction aspects from the application domain (learning) and the software infrastructure (interactive multimedia) are required for the meaningful interpretation of mining results