User-centred design of flexible hypermedia for a mobile guide: Reflections on the hyperaudio experience

A user-centred design approach involves end-users from the very beginning. Considering users at the early stages compels designers to think in terms of utility and usability and helps develop the system on what is actually needed. This paper discusses the case of HyperAudio, a context-sensitive adaptive and mobile guide to museums developed in the late 90s. User requirements were collected via a survey to understand visitors’ profiles and visit styles in Natural Science museums. The knowledge acquired supported the specification of system requirements, helping defining user model, data structure and adaptive behaviour of the system. User requirements guided the design decisions on what could be implemented by using simple adaptable triggers and what instead needed more sophisticated adaptive techniques, a fundamental choice when all the computation must be done on a PDA. Graphical and interactive environments for developing and testing complex adaptive systems are discussed as a further step towards an iterative design that considers the user interaction a central point. The paper discusses how such an environment allows designers and developers to experiment with different system’s behaviours and to widely test it under realistic conditions by simulation of the actual context evolving over time. The understanding gained in HyperAudio is then considered in the perspective of the developments that followed that first experience: our findings seem still valid despite the passed time

Adaptive hypermedia for education and training

Adaptive hypermedia (AH) is an alternative to the traditional, one-size-fits-all approach in the development of hypermedia systems. AH systems build a model of the goals, preferences, and knowledge of each individual user; this model is used throughout the interaction with the user to adapt to the needs of that particular user (Brusilovsky, 1996b). For example, a student in an adaptive educational hypermedia system will be given a presentation that is adapted specifically to his or her knowledge of the subject (De Bra & Calvi, 1998; Hothi, Hall, & Sly, 2000) as well as a suggested set of the most relevant links to proceed further (Brusilovsky, Eklund, & Schwarz, 1998; Kavcic, 2004). An adaptive electronic encyclopedia will personalize the content of an article to augment the user's existing knowledge and interests (Bontcheva & Wilks, 2005; Milosavljevic, 1997). A museum guide will adapt the presentation about every visited object to the user's individual path through the museum (Oberlander et al., 1998; Stock et al., 2007). Adaptive hypermedia belongs to the class of user-adaptive systems (Schneider-Hufschmidt, Kühme, & Malinowski, 1993). A distinctive feature of an adaptive system is an explicit user model that represents user knowledge, goals, and interests, as well as other features that enable the system to adapt to different users with their own specific set of goals. An adaptive system collects data for the user model from various sources that can include implicitly observing user interaction and explicitly requesting direct input from the user. The user model is applied to provide an adaptation effect, that is, tailor interaction to different users in the same context. In different kinds of adaptive systems, adaptation effects could vary greatly. In AH systems, it is limited to three major adaptation technologies: adaptive content selection, adaptive navigation support, and adaptive presentation. The first of these three technologies comes from the fields of adaptive information retrieval (IR) and intelligent tutoring systems (ITS). When the user searches for information, the system adaptively selects and prioritizes the most relevant items (Brajnik, Guida, & Tasso, 1987; Brusilovsky, 1992b)

Adaptive Educational Hypermedia based on Multiple Student Characteristics

The learning process in Adaptive Educational Hypermedia (AEH) environments is complex and may be influenced by aspects of the student, including prior knowledge, learning styles, experience and preferences. Current AEH environments, however, are limited to processing only a small number of student characteristics. This paper discusses the development of an AEH system which includes a student model that can simultaneously take into account multiple student characteristics. The student model will be developed to use stereotypes, overlays and perturbation techniques. Keywords: adaptive educational hypermedia, multiple characteristics, student model

Design of the CAM model and authoring tool

Students benefit from personalised attention; however, often teachers are unable to provide this. An Adaptive Hypermedia (AH) system can offer a richer learning experience in an educational environment, by giving personalised attention to students. On-line courses are becoming increasingly popular by means of Learning Management Systems (LSM). The aim of the GRAPPLE project is to integrate an AH with major LMS, to provide an environment that delivers personalised courses in a LMS interface. However, designing an AH is a much more complex and time-consuming task, than creating a course in a LMS. Several models and systems were developed previously, but the (re)-usability by educational authors of the adaptation remains limited. To simplify adaptive behaviour authoring for an educational author, a visual environment was selected as being most intuitive. This paper describes a reference model for authoring in a visual way and introduces an authoring tool based upon this model

Hypertext 2008: A Great Safari (ACM SIGWEB Trip Report)

The 21st ACM Conference on Hypertext and Hypermedia was held in Pittsburgh, PA from June 19th to 21st of 2008. Like all great coming-of-age parties it was a mix of celebrating the past and looking forward with excitement to the future. Over the last few years the conference has grown in scope to cover a wide range of trends and technologies concerned with connecting information and people. This year the main themes were Information Linking and Organization, Social Linking, Applications of Hypertext, and Hypertext, Culture and Communications; once more attracting a fascinating mix of people from both the technical and literary worlds

Perspectives for Electronic Books in the World Wide Web Age

While the World Wide Web (WWW or Web) is steadily expanding, electronic books (e-books) remain a niche market. In this article, it is first postulated that specialized contents and device independence can make Web-based e-books compete with paper prints; and that adaptive features that can be implemented by client-side computing are relevant for e-books, while more complex forms of adaptation requiring server-side computations are not. Then, enhancements of the WWW standards (specifically of XML, XHTML, of the style-sheet languages CSS and XSL, and of the linking language XLink) are proposed for a better support of client-side adaptation and device independent content modeling. Finally, advanced browsing functionalities desirable for e-books as well as their implementation in the WWW context are described

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

Empirical evaluation of an adaptive e-learning system and the effects of knowledge, learning styles and multimedia mode on student achievement

This paper presents an empirical evaluation of an adaptive e-learning system (AES). The system was evaluated in an experimental research. During the 9 weeks of experimentation, the students studied the learning material in two randomly allocated groups, an experimental group using the AES and a control group using the non-AES. Research findings are described as follows. Students who learned using the AES performed better significantly than those who learned using the non-AES. The implementation of test repetition as a function of knowledge adaptation in the AES increased student achievement significantly. When the effect of test repetition was removed, the implementation of learning style and multimedia mode adaptation in the AES was still found to have significant effect upon student performance. Students whose learning style and multimedia preferences were matched with the system achieved better results