An interpretative phenomenological analysis of adult clients’ experience of My Career Chapter

This paper presents an investigation into the properties of a new narrative technique for career assessment and counselling, My Career Chapter: A Dialogical Autobiography. This technique is used to facilitate clients’ construction of a meaningful career-related autobiography. Previous research indicates the usefulness of My Career Chapter for adult clients and its alignment with recommendations for the development and application of qualitative assessment and counselling techniques. This study specifically commences research into the technique’s applicability for adolescents. A focus group, comprised of guidance counselling professionals whose work primarily pertained to the needs of adolescents, found that there is potential to develop a version of My Career Chapter that is suitable for adolescents.

Context and models for the analysis of individual and group needs

This paper summarizes the papers presented in the thematic stream Models for the Analysis of Individual and Group Needs, at the 2007 IAEVG-SVP-NCDA Symposium: Vocational Psychology and Career Guidance Practice: An International Partnership. The predominant theme which emerged from the papers was that theory and practice need to be positioned within their contexts. For this paper, context has been formulated as a dimension ranging from the individual’s experience of himself or herself in conversations, including interpersonal transactions and body culture, through to broad higher levels of education, work, nation, and economy.

Using ontology for the representational analysis of process modelling techniques

Selecting an appropriate business process modelling technique forms an important task within the methodological challenges of a business process management project. While a plethora of available techniques has been developed over the last decades, there is an obvious shortage of well-accepted reference frameworks that can be used to evaluate and compare the capabilities of the different techniques. Academic progress has been made at least in the area of representational analyses that use ontology as a benchmark for such evaluations. This paper reflects on the comprehensive experiences with the application of a model based on the Bunge ontology in this context. A brief overview of the underlying research model characterizes the different steps in such a research project. A comparative summary of previous representational analyses of process modelling techniques over time gives insights into the relative maturity of selected process modelling techniques. Based on these experiences suggestions are made as to where ontology-based representational analyses could be further developed and what limitations are inherent to such analyses.

Application of the analytic hierarchy process (AHP) in multi-criteria analysis of the selection of intelligent building systems

The availability of innumerable intelligent building (IB) products, and the current dearth of inclusive building component selection methods suggest that decision makers might be confronted with the quandary of forming a particular combination of components to suit the needs of a specific IB project. Despite this problem, few empirical studies have so far been undertaken to analyse the selection of the IB systems, and to identify key selection criteria for major IB systems. This study is designed to fill these research gaps. Two surveys: a general survey and the analytic hierarchy process (AHP) survey are proposed to achieve these objectives. The first general survey aims to collect general views from IB experts and practitioners to identify the perceived critical selection criteria, while the AHP survey was conducted to prioritize and assign the important weightings for the perceived criteria in the general survey. Results generally suggest that each IB system was determined by a disparate set of selection criteria with different weightings. ‘Work efficiency’ is perceived to be most important core selection criterion for various IB systems, while ‘user comfort’, ‘safety’ and ‘cost effectiveness’ are also considered to be significant. Two sub-criteria, ‘reliability’ and ‘operating and maintenance costs’, are regarded as prime factors to be considered in selecting IB systems. The current study contributes to the industry and IB research in at least two aspects. First, it widens the understanding of the selection criteria, as well as their degree of importance, of the IB systems. It also adopts a multi-criteria AHP approach which is a new method to analyse and select the building systems in IB. Further research would investigate the inter-relationship amongst the selection criteria.

Electronic workplace surveillance and employee privacy : a comparative analysis of privacy protection in Australia and the United States

More than a century ago in their definitive work “The Right to Privacy” Samuel D. Warren and Louis D. Brandeis highlighted the challenges posed to individual privacy by advancing technology. Today’s workplace is characterised by its reliance on computer technology, particularly the use of email and the Internet to perform critical business functions. Increasingly these and other workplace activities are the focus of monitoring by employers. There is little formal regulation of electronic monitoring in Australian or United States workplaces. Without reasonable limits or controls, this has the potential to adversely affect employees’ privacy rights. Australia has a history of legislating to protect privacy rights, whereas the United States has relied on a combination of constitutional guarantees, federal and state statutes, and the common law. This thesis examines a number of existing and proposed statutory and other workplace privacy laws in Australia and the United States. The analysis demonstrates that existing measures fail to adequately regulate monitoring or provide employees with suitable remedies where unjustifiable intrusions occur. The thesis ultimately supports the view that enacting uniform legislation at the national level provides a more effective and comprehensive solution for both employers and employees. Chapter One provides a general introduction and briefly discusses issues relevant to electronic monitoring in the workplace. Chapter Two contains an overview of privacy law as it relates to electronic monitoring in Australian and United States workplaces. In Chapter Three there is an examination of the complaint process and remedies available to a hypothetical employee (Mary) who is concerned about protecting her privacy rights at work. Chapter Four provides an analysis of the major themes emerging from the research, and also discusses the draft national uniform legislation. Chapter Five details the proposed legislation in the form of the Workplace Surveillance and Monitoring Act, and Chapter Six contains the conclusion.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Identification and analysis of business and software services : A consolidated approach

Although the benefits of service orientation are prevalent in literature, a review, analysis, and evaluation of the 30 existing service analysis approaches presented in this paper have shown that a comprehensive approach to the identification and analysis of both business and supporting software services is missing. Based on this evaluation of existing approaches and additional sources, we close this gap by proposing an integrated, consolidated approach to business and software service analysis that combines and extends the strengths of the examined methodologies.

Service analysis : A critical assessment of the state of the art

The service-orientation paradigm has not only become prevalent in the software systems domain in recent years, but is also increasingly applied on the business level to restructure organisational capabilities. In this paper, we present the results of an extensive literature review of 30 approaches related to service identification and analysis for both domains. Based on the consolidation of a superset of comparison criteria for service-oriented methodologies found in related literature, we compare and evaluate the different characteristics of service engineering methods with a focus on service analysis. Although a close business and IT alignment is regarded as one of the core beneficial promises of service-orientation, our analysis suggests that there is a lack of unified, comprehensive methodology for service identification and analysis integrating and addressing both domains. Thus, we discuss how our results can inform directions for future research in this area.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Negotiating multiple identities between school and the outside world : A critical discourse analysis

This article examines interview talk of three students in an Australian high school to show how they negotiate their young adult identities between school and the outside world. It draws on Bakhtin’s concepts of dialogism and heteroglossia to argue that identities are linguistically and corporeally constituted. A critical discourse analysis of segments of transcribed interviews and student-related public documents finds a mismatch between a social justice curriculum at school and its transfer into students’ accounts of outside school lived realities. The article concludes that a productive social justice pedagogy must use its key principles of (con)textual interrogation to engage students in reflexive practice about their positioning within and against discourses of social justice in their student and civic lives. An impending national curriculum must decide whether or not it negotiates the discursive divide any better.

Multi-outcome construction policies : comparative analysis of western australian and queensland policies

This document provides an overview of the differences and similarities in the objectives and implementation frameworks of the training and employment policies applying to public construction projects in Western Australia and Queensland. The material in the document clearly demonstrates the extent to which approaches to the pursuit of training objectives in particular have been informed by the experiences of other jurisdictions. The two State governments now have very similar approaches to the promotion of training with the WA government basing a good part of its policy approach on the “Queensland model”. As the two States share many similar economic and other characteristics, and have very similar social and economic goals, this similarity is to be expected. The capacity to benefit from the experiences of other jurisdictions is to be welcomed. The similarity in policy approach also suggests a potential for ongoing collaborations between the State governments on research aimed at further improving training and employment outcomes via public construction projects.

"Well, now I'm upset": Moral and social orders in the playground

There is much still to learn about how young children’s membership with peers shapes their constructions of moral and social obligations within everyday activities in the school playground. This paper investigates how a small group of girls, aged four to six years, account for their everyday social interactions in the playground. They were video-recorded as they participated in a pretend game of school. Several days later, a video-recorded excerpt of the interaction was shown to them and invited to comment on what was happening in the video. This conversation was audio-recorded. Drawing on a conversation analysis approach, this chapter shows that, despite their discontent and complaining about playing the game of school, the girls’ actions showed their continued orientation to the particular codes of the game, of ‘no going away’ and ‘no telling’. By making relevant these codes, jointly constructed by the girls during the interview, they managed each other’s continued participation within two arenas of action: the pretend, as a player in a pretend game of school; and the real, as a classroom member of a peer group. Through inferences to explicit and implicit codes of conduct, moral obligations were invoked as the girls attempted to socially exclude or build alliances with others, and enforce their own social position. As well, a shared history that the girls re-constructed has moral implications for present and future relationships. The girls oriented to the history as an interactional resource for accounting for their actions in the pretend game. This paper uncovers how children both participate in, and shape, their everyday social worlds through talk and interaction and the consequences a taken-for-granted activity such as playing school has for their moral and social positions in the peer group.

Whole of life cycle cost analysis in bridge rehabilitation

The report presents a methodology for whole of life cycle cost analysis of alternative treatment options for bridge structures, which require rehabilitation. The methodology has been developed after a review of current methods and establishing that a life cycle analysis based on a probabilistic risk approach has many advantages including the essential ability to consider variability of input parameters. The input parameters for the analysis are identified as initial cost, maintenance, monitoring and repair cost, user cost and failure cost. The methodology utilizes the advanced simulation technique of Monte Carlo simulation to combine a number of probability distributions to establish the distribution of whole of life cycle cost. In performing the simulation, the need for a powerful software package, which would work with spreadsheet program, has been identified. After exploring several products on the market, @RISK software has been selected for the simulation. In conclusion, the report presents a typical decision making scenario considering two alternative treatment options.