Robert D. Macredie

Cognitive styles and hypermedia navigation: development of a learning model

There has been an increased growth in the use of hypermedia to deliver learning and teaching material. However, much remains to be learned about how different learners perceive such systems. Therefore, it is essential to build robust learning models to illustrate how hypermedia features are experienced by different learners. Research into individual differences suggests cognitive styles have a significant effect on student learning in hypermedia systems. In particular, Witkins Field Dependence has been extensively examined in previous studies. This article reviews the published findings from empirical studies of hypermedia learning. Specifically, the review classifies the research into five themes: nonlinear learning, learner control, navigation in hyperspace, matching and mismatching, and learning effectiveness. A learning model, developed from an analysis of findings of the previous studies, is presented. Finally, implications for the design of hypermedia learning systems are discussed.

Effective Communication in Requirements Elicitation: A Comparison of Methodologies

The elicitation or communication of user requirements comprises an early and critical but highly error-prone stage in system development. Socially oriented methodologies provide more support for user involvement in design than the rigidity of more traditional methods, facilitating the degree of user–designer communication and the ‘capture’ of requirements. A more emergent and collaborative view of requirements elicitation and communication is required to encompass the user, contextual and organisational factors. From this accompanying literature in communication issues in requirements elicitation, a four-dimensional framework is outlined and used to appraise comparatively four different methodologies seeking to promote a closer working relationship between users and designers. The facilitation of communication between users and designers is subject to discussion of the ways in which communicative activities can be ‘optimised’ for successful requirements gathering, by making recommendations based on the four dimensions to provide fruitful considerations for system designers.

Communication issues in requirements elicitation: a content analysis of stakeholder experiences

Abstract The gathering of stakeholder requirements comprises an early, but continuous and highly critical stage in system development. This phase in development is subject to a large degree of error, influenced by key factors rooted in communication problems. This pilot study builds upon an existing theory-based categorisation of these problems through presentation of a four-dimensional framework on communication. Its structure is validated through a content analysis of interview data, from which themes emerge, that can be assigned to the dimensional categories, highlighting any problematic areas. The paper concludes with a discussion on the utilisation of the framework for requirements elicitation exercises.

Modeling human behavior in user-adaptive systems: Recent advances using soft computing techniques

Adaptive Hypermedia systems are becoming more important in our everyday activities and users are expecting more intelligent services from them. The key element of a generic adaptive hypermedia system is the user model. Traditional machine learning techniques used to create user models are usually too rigid to capture the inherent uncertainty of human behavior. In this context, soft computing techniques can be used to handle and process human uncertainty and to simulate human decision-making. This paper examines how soft computing techniques, including fuzzy logic, neural networks, genetic algorithms, fuzzy clustering and neuro-fuzzy systems, have been used, alone or in combination with other machine learning techniques, for user modeling from 1999 to 2004. For each technique, its main applications, limitations and future directions for user modeling are presented. The paper also presents guidelines that show which soft computing techniques should be used according to the task implemented by the application.

Migrating agile methods to standardized development practice

Situated process and quality frameworks offer a way to resolve the tensions that arise when introducing agile methods into standardized software development engineering. For these to be successful, however, organizations must grasp the opportunity to reintegrate software development management, theory, and practice.

Visualizing and tracking the growth of competing paradigms: two case studies

In this article we demonstrate the use of an integrative approach to visualizing and tracking the development of scientific paradigms. This approach is designed to reveal the long-term process of competing scientific paradigms. We assume that a cluster of highly cited and cocited scientific publications in a cocitation network represents the core of a predominant scientific paradigm. The growth of a paradigm is depicted and animated through the rise of citation rates and the movement of its core cluster towards the center of the cocitation network. We study two cases of competing scientific paradigms in the real world: (1) the causes of mass extinctions, and (2) the connections between mad cow disease and a new variant of a brain disease in humans — vCJD. Various theoretical and practical issues concerning this approach are discussed.

Web-based interaction: A review of three important human factors

With the rapid development of information technology, the World Wide Web has been widely used in various applications, such as search engines, online learning and electronic commerce. These applications are used by a diverse population of users with heterogeneous backgrounds, in terms of their knowledge, skills, and needs. Therefore, human factors are key issues for the development of Web-based applications, leading research into human factors to grow significantly in the past decade. This paper identifies and reviews three important human factors that have been examined in existing empirical studies, including gender differences, prior knowledge, and cognitive styles. The main results from the analysis include that: (a) females have more disorientation problems than males; (b) flexible paths are more beneficial to experts while structured content is more useful to novices; and (c) Field Dependent and Field Independent users prefer to employ different search strategies. In addition to reviewing the existing empirical studies, this paper also highlights areas of future research.

Understanding the business-IT relationship

The relationship between the business and IT departments in the context of the organisation has been characterised as highly divisive. Contributing problems appear to revolve around the failure to adequately communicate and understand the required information for the alignment of business and IT strategies and infrastructures. This study takes a communication-based view on the concept of alignment, in terms of the relationship between the retail business and IT within a major high street UK bank. A research framework (PICTURE) is used to provide insight into this relationship and guide the analysis of interviews with 29 individuals on mid-high management level for their thematic content. The paper highlights the lessons that can be derived from the study of the BIT relationship and how possible improvements could be made.

Editorial: Data mining for understanding user needs

Data mining and data analysis have a long history in human-computer interaction, starting with early interests in tracking the users then trying to infer models of users for adaptive systems [Benyon and Murray 1993; Fischer 1993], to more recent interests in attentional user interfaces, notifier systems, and recommenders. Recommender systems have emerged as a research area meriting a conference series since 2007, while attentional UIs have been the subject of several special issues [Horvitz et al. 2003; McCrickard et al. 2003b]. The convergence of analytic techniques for establishing patterns and orders in large datasets—data mining—and using such analysis to improve the responsiveness, user fit, and functionality of interactive systems has not been explicitly synthesized even though it has been a persistent interest in HCI. This special issue is therefore timely in bringing the fields of data mining and HCI together, As technology has developed over the past few decades, vast amounts of data have been generated as a result of users’ interactions with a range of applications from e-commerce to social networking sites. Analyzing this data can help in understanding the users’ needs and evaluating the effectiveness of user interaction. In turn, this can be used to improve the interface and interaction design, determine more suitable content, and develop useful services targeted at individual users. Data mining, also known as knowledge discovery [Fayyad and Uthurusamy 1996], is the process of extracting valuable information from large amounts

Automated user modeling for personalized digital libraries

Digital libraries (DLs) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from DLs. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in DLs has been user driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct DLs that satisfy a users necessity for information: Adaptive DLs, libraries that automatically learn user preferences and goals and personalize their interaction using this information.