Linking Theory and Practice: Performing a Reality Check on a Model of IS Success

The issue of ‘rigour vs. relevance’ in IS research has generated an intense, heated debate for over a decade. It is possible to identify, however, only a limited number of contributions on how to increase the relevance of IS research without compromising its rigour. Based on a lifecycle view of IS research, we propose the notion of ‘reality checks’ in order to review IS research outcomes in the light of actual industry demands. We assume that five barriers impact the efficient transfer of IS research outcomes; they are lack of awareness, lack of understandability, lack of relevance, lack of timeliness, and lack of applicability. In seeking to understand the effect of these barriers on the transfer of mature IS research into practice, we used focus groups. We chose DeLone and McLean’s IS success model as our stimulus because it is one of the more widely researched areas of IS.

The Figmentum Project: appropriating information and communication technologies to animate our urban fabric

This paper explores how we may design located information and communication technologies (ICTs) to foster community sentiment. It focuses explicitly on possibilities for ICTs to create new modalities of place through exploring key factors such as shared experiences, shared knowledge and shared authorship. To contextualise this discussion in a real world setting, this paper presents FIGMENTUM, a situated generative art application that was developed for and installed in a new urban development. FIGMENTUM is a non-authoritative, non-service based application that aims to trigger emotional and representational place-based communities. Out of this practice-led research comes a theory and a process for designing creative place-based ICT’s to animate our urban communities.

An innovative learning model for teaching architectural technology using building information modelling : a Queensland University of Technology perspective

In architecture courses, instilling a wider understanding of the industry specific representations practiced in the Building Industry is normally done under the auspices of Technology and Science subjects. Traditionally, building industry professionals communicated their design intentions using industry specific representations. Originally these mainly two dimensional representations such as plans, sections, elevations, schedules, etc. were produced manually, using a drawing board. Currently, this manual process has been digitised in the form of Computer Aided Design and Drafting (CADD) or ubiquitously simply CAD. While CAD has significant productivity and accuracy advantages over the earlier manual method, it still only produces industry specific representations of the design intent. Essentially, CAD is a digital version of the drawing board. The tool used for the production of these representations in industry is still mainly CAD. This is also the approach taken in most traditional university courses and mirrors the reality of the situation in the building industry. A successor to CAD, in the form of Building Information Modelling (BIM), is presently evolving in the Construction Industry. CAD is mostly a technical tool that conforms to existing industry practices. BIM on the other hand is revolutionary both as a technical tool and as an industry practice. Rather than producing representations of design intent, BIM produces an exact Virtual Prototype of any building that in an ideal situation is centrally stored and freely exchanged between the project team. Essentially, BIM builds any building twice: once in the virtual world, where any faults are resolved, and finally, in the real world. There is, however, no established model for learning through the use of this technology in Architecture courses. Queensland University of Technology (QUT), a tertiary institution that maintains close links with industry, recognises the importance of equipping their graduates with skills that are relevant to industry. BIM skills are currently in increasing demand throughout the construction industry through the evolution of construction industry practices. As such, during the second half of 2008, QUT 4th year architectural students were formally introduced for the first time to BIM, as both a technology and as an industry practice. This paper will outline the teaching team’s experiences and methodologies in offering a BIM unit (Architectural Technology and Science IV) at QUT for the first time and provide a description of the learning model. The paper will present the results of a survey on the learners’ perspectives of both BIM and their learning experiences as they learn about and through this technology.

The information systems discipline in Australian universities : a contextual framework

This chapter presents the contextual framework for the second phase of a multi-method, multiple study of the information systems (IS) academic discipline in Australia. The chapter outlines the genesis of a two-phase Australian study, and positions the study as the precursor to a larger Pacific-Asia study. Analysis of existing literature on the state of IS and on relevant theory underpins a series of individual Australian state case studies summarised in this chapter and represented as separate chapters in the book. This chapter outlines the methodological approach employed, with emphasis on the case-study method of the multiple state studies. The process of multiple peer review of the studies is described. Importantly, this chapter summarises and analyses each of the subsequent chapters of this book, emphasising the role of a framework developed to guide much of the data gathering and analysis. This chapter also highlights the process involved in conducting the meta-analysis reported in the final chapter of this book, and summarises some of the main results of the meta-analysis.

Information for regulating action in sport : metastability and emergence of tactical solutions under ecological constraints

The aims of this chapter are twofold. First, we show how experiments related to nonlinear dynamical systems theory can bring about insights on the interconnectedness of different information sources for action. These include the amount of information as emphasised in conventional models of cognition and action in sport and the nature of perceptual information typically emphasised in the ecological approach. The second aim was to show how, through examining the interconnectedness of these information sources, one can study the emergence of novel tactical solutions in sport; and design experiments where tactical/decisional creativity can be observed. Within this approach it is proposed that perceptual and affective information can be manipulated during practice so that the athlete's cognitive and action systems can be transposed to a meta-stable dynamical performance region where the creation of novel action information may reside.

Imaginary relish and exquisite torture : the elaborated intrusion theory of desire

The authors argue that human desire involves conscious cognition that has strong affective connotation and is potentially involved in the determination of appetitive behavior rather than being epiphenomenal to it. Intrusive thoughts about appetitive targets are triggered automatically by external or physiological cues and by cognitive associates. When intrusions elicit significant pleasure or relief, cognitive elaboration usually ensues. Elaboration competes with concurrent cognitive tasks through retrieval of target related information and its retention in working memory. Sensory images are especially important products of intrusion and elaboration because they simulate the sensory and emotional qualities of target acquisition. Desire images are momentarily rewarding but amplify awareness of somatic and emotional deficits. Effects of desires on behavior are moderated by competing incentives, target availability, and skills. The theory provides a coherent account of existing data and suggests new directions for research and treatment.

Critical Systems Theory: A Political Economy of Language, Thought, and Technology

An emergent form of political economy, facilitated by information and communication technologies (ICTs), is widely propagated as the apotheosis of unmitigated social, economic, and technological progress. Meanwhile, throughout the world, social degradation and economic inequality are increasing logarithmically. Valued categories of thought are, axiomatically, the basic commodities of the “knowledge economy”. Language is its means of exchange. This paper proposes a sociolinguistic method with which to critically engage the hyperbole of the “Information Age”. The method is grounded in a systemic social theory that synthesises aspects of autopoiesis and Marxist political economy. A trade policy statement is analysed to exemplify the sociolinguistically created aberrations that are today most often construed as social and political determinants.

The self-Googling phenomenon : investigating the performance of personalized information resources

This paper investigates self–Googling through the monitoring of search engine activities of users and adds to the few quantitative studies on this topic already in existence. We explore this phenomenon by answering the following questions: To what extent is the self–Googling visible in the usage of search engines; is any significant difference measurable between queries related to self–Googling and generic search queries; to what extent do self–Googling search requests match the selected personalised Web pages? To address these questions we explore the theory of narcissism in order to help define self–Googling and present the results from a 14–month online experiment using Google search engine usage data.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).