820 resultados para knowledge framework


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Information graphics have become increasingly important in representing, organising and analysing information in a technological age. In classroom contexts, information graphics are typically associated with graphs, maps and number lines. However, all students need to become competent with the broad range of graphics that they will encounter in mathematical situations. This paper provides a rationale for creating a test to measure students’ knowledge of graphics. This instrument can be used in mass testing and individual (in-depth) situations. Our analysis of the utility of this instrument informs policy and practice. The results provide an appreciation of the relative difficulty of different information graphics; and provide the capacity to benchmark information about students’ knowledge of graphics. The implications for practice include the need to support the development of students’ knowledge of graphics, the existence of gender differences, the role of cross-curriculum applications in learning about graphics, and the need to explicate the links among graphics.

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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.

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Review of Haunting the Knowledge Economy by Jane Kenway, Elizabeth Bullen, Johannah Fahey with Simon Robb. London: Routledge, 2006; for the journal of the Higher Education Research & Development Society of Australia.

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Ethnography has gained wide acceptance in the industrial design profession and curriculum as a means of understanding the user. However, there is considerable confusion about the particularities of its practice accompanied by the absence of an interoperable vocabulary. The consequent interdisciplinary effort is a power play between disciplines whereby the methodological view of ethnography marginalises its theoretical and analytical components. In doing so, it restricts the potential of ethnography suggesting the need for alternative methods of informing the design process. This article suggests that activity theory, with an emphasis on human activity as the fundamental unit of study, is an appropriate methodology for the generation of user requirements. The process is illustrated through the adaptation of an ethnographic case study, for the design of classroom furniture in India.

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This thesis examines the changing relationships between television, politics, audiences and the public sphere. Premised on the notion that mediated politics is now understood “in new ways by new voices” (Jones, 2005: 4), and appropriating what McNair (2003) calls a “chaos theory” of journalism sociology, this thesis explores how two different contemporary Australian political television programs (Sunrise and The Chaser’s War on Everything) are viewed, understood, and used by audiences. In analysing these programs from textual, industry and audience perspectives, this thesis argues that journalism has been largely thought about in overly simplistic binary terms which have failed to reflect the reality of audiences’ news consumption patterns. The findings of this thesis suggest that both ‘soft’ infotainment (Sunrise) and ‘frivolous’ satire (The Chaser’s War on Everything) are used by audiences in intricate ways as sources of political information, and thus these TV programs (and those like them) should be seen as legitimate and valuable forms of public knowledge production. It therefore might be more worthwhile for scholars to think about, research and teach journalism in the plural: as a series of complementary or antagonistic journalisms, rather than as a single coherent entity.

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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.

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The weaknesses of ‗traditional‘ modes of instruction in accounting education have been widely discussed. Many contend that the traditional approach limits the ability to provide opportunities for students to raise their competency level and allow them to apply knowledge and skills in professional problem solving situations. However, the recent body of literature suggests that accounting educators are indeed actively experimenting with ‗non-traditional‘ and ‗innovative‘ instructional approaches, where some authors clearly favour one approach over another. But can one instructional approach alone meet the necessary conditions for different learning objectives? Taking into account the ever changing landscape of not only business environments, but also the higher education sector, the premise guiding the collaborators in this research is that it is perhaps counter productive to promote competing dichotomous views of ‗traditional‘ and ‗non-traditional‘ instructional approaches to accounting education, and that the notion of ‗blended learning‘ might provide a useful framework to enhance the learning and teaching of accounting. This paper reports on the first cycle of a longitudinal study, which explores the possibility of using blended learning in first year accounting at one campus of a large regional university. The critical elements of blended learning which emerged in the study are discussed and, consistent with the design-based research framework, the paper also identifies key design modifications for successive cycles of the research.

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This document outlines a framework that could be used by government agencies in assessing policy interventions aimed at achieving social outcomes from government construction contracts. The framework represents a rational interpretation of the information gathered during the multi-outcomes construction policies project. The multi-outcomes project focused on the costs and benefits of using public construction contracts to promote the achievement of training and employment and public art objectives. The origin of the policy framework in a cost-benefit appraisal of current policy interventions is evidenced by its emphasis on sensitivity to policy commitment and project circumstances (especially project size and scope).The quantitative and qualitative analysis conducted in the multi-outcomes project highlighted, first, that in the absence of strong industry commitment to policy objectives, policy interventions typically result in high levels of avoidance activity, substantial administrative costs and very few benefits. Thus, for policy action on, for example, training or local employment to be successful compliance issues must be adequately addressed. Currently it appears that pre-qualification schemes (similar to the Priority Access Scheme) and schemes that rely on measuring, for example, the training investments of contractors within particular projects do not achieve high levels of compliance and involve significant administrative costs. Thus, an alternative is suggested in the policy framework developed here: a levy on each public construction project – set as a proportion of the total project costs. Although a full evaluation of this policy alternative was beyond the scope of the multi-outcomes construction policies project, it appears to offer the potential to minimize the transaction costs on contractors whilst enabling the creation of a training agency dedicated to improving the supply of skilled construction labour. A recommendation is thus made that this policy alternative be fully researched and evaluated. As noted above, the outcomes of the multi-outcomes research project also highlighted the need for sensitivity to project circumstances in the development and implementation of polices for public construction projects. Ideally a policy framework would have the flexibility to respond to circumstances where contractors share a commitment to the policy objectives and are able to identify measurable social outcomes from the particular government projects they are involved in. This would involve a project-by-project negotiation of goals and performance measures. It is likely to only be practical for large, longer term projects.

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The K-Adv has been developed around the concept that it comprises an ICT enabling infrastructure that encompasses ICT hardware and software infrastructure facilities together with an enabling ICT support system; a leadership infrastructure support system that provides the vision for its implementation and the realisation capacity for the vision to be realised; and the necessary people infrastructure that includes the people capabilities and capacities supported by organisational processes that facilitates this resource to be mobilised.

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Australia’s civil infrastructure assets of roads, bridges, railways, buildings and other structures are worth billions of dollars. Road assets alone are valued at around A$ 140 billion. As the condition of assets deteriorate over time, close to A$10 billion is spent annually in asset maintenance on Australia's roads, or the equivalent of A$27 million per day. To effectively manage road infrastructures, firstly, road agencies need to optimise the expenditure for asset data collection, but at the same time, not jeopardise the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates could be accurately estimated. And finally, the prediction of budgets for maintenance and rehabilitation must provide a certain degree of reliability. A procedure for assessing investment decision for road asset management has been developed. The procedure includes: • A methodology for optimising asset data collection; • A methodology for calibrating deterioration prediction models; • A methodology for assessing risk-adjusted estimates for life-cycle cost estimates. • A decision framework in the form of risk map

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The aim of this project is to develop a systematic investment decision-making framework for infrastructure asset management by incorporation economic justification, social and environmental consideration in the decision-making process. This project assesses the factors that are expected to provide significant impacts on the variability of expenditures. A procedure for assessing risk and reliability for project investment appraisals will be developed. The project investigates public perception, social and environmental impacts on road infrastructure investment. This research will contribute to the debate about how important social and environmental issues should be incorporated into the investment decision-making process for infrastructure asset management.

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This project aims to assess the extent of economic sustainability of working in international markets by Australian construction design-related firms. This investigation also identified barriers and success factors firms experience, which ultimately increases or reduces their exposure to financial risk. This study explored new research territory by developing a detailed understanding of the way three successful firms have maintained their longevity in various international markets. The firms are not considered to be large firms by international standards. The manner in which the firms achieve long term sustainability, deal with problems and barriers in international markets and develop successful strategies rely upon being adaptable to different markets and changes within markets. A model was developed based upon a critical analysis of the literature. An adaptive performance framework for sustainability was developed which had three key areas; internationalisation process, market knowledge and design management. The sustainable business model is underpinned by the management of non-economic factors, which include social, cultural and intellectual capital. The ultimate aim of any firm and the ultimate indicator of success is financial capital. Firms typically develop their own highly sophisticated financial measures themselves however have only an implicit understanding of other softer and less tangible factors that impact upon sustainability. Adaptive performance is the firm’s continual adaptivity of business practices to respond to and thereby achieve client satisfaction by a combination of self, market and project needs assessment.