352 resultados para Knowledge (Theory)


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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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In the context of a multi-paper special issue of TVNM on the future of media studies, this paper traces the tradition of ‘active audience’ theory in TV scholarship, arguing that it has much to offer in the study of new digital media, especially an approach to user-created content and dynamics of change. The paper argues for a ‘cultural science’ approach to ‘active audiences’ in order to analyse and understand how non-professionals and consumers contribute to the growth of knowledge in complex open media systems.

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Professional coaching is a rapidly expanding field with interdisciplinary roots and broad application. However, despite abundant prescriptive literature, research into the process of coaching is minimal. Similarly, although learning is inherently recognised in the process of coaching, the process of learning in coaching is little understood and learning theory makes up only a small part of the evidence-based coaching literature. In this grounded theory study of coaches and their clients, the process of learning in coaching across a range of coaching models is examined and discussed. The findings demonstrate how learning in coaching emerged as a process of discovering, applying and integrating new knowledge, which culminated in a process of developing. This process occurred through eight key coaching processes shared between coaches and clients and combined a multitude of learning theories.

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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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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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Sleeper is an 18'00" musical work for live performer and laptop computer which exists as both a live performance work and a recorded work for audio CD. The work has been presented at a range of international performance events and survey exhibitions. These include the 2003 International Computer Music Conference (Singapore) where it was selected for CD publication, Variable Resistance (San Francisco Museum of Modern Art, USA), and i.audio, a survey of experimental sound at the Performance Space, Sydney. The source sound materials are drawn from field recordings made in acoustically resonant spaces in the Australian urban environment, amplified and acoustic instruments, radio signals, and sound synthesis procedures. The processing techniques blur the boundaries between, and exploit, the perceptual ambiguities of de-contextualised and processed sound. The work thus challenges the arbitrary distinctions between sound, noise and music and attempts to reveal the inherent musicality in so-called non-musical materials via digitally re-processed location audio. Thematically the work investigates Paul Virilio’s theory that technology ‘collapses space’ via the relationship of technology to speed. Technically this is explored through the design of a music composition process that draws upon spatially and temporally dispersed sound materials treated using digital audio processing technologies. One of the contributions to knowledge in this work is a demonstration of how disparate materials may be employed within a compositional process to produce music through the establishment of musically meaningful morphological, spectral and pitch relationships. This is achieved through the design of novel digital audio processing networks and a software performance interface. The work explores, tests and extends the music perception theories of ‘reduced listening’ (Schaeffer, 1967) and ‘surrogacy’ (Smalley, 1997), by demonstrating how, through specific audio processing techniques, sounds may shifted away from ‘causal’ listening contexts towards abstract aesthetic listening contexts. In doing so, it demonstrates how various time and frequency domain processing techniques may be used to achieve this shift.

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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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This study contributes to the growth of design knowledge in China, where vehicle design for the local, older user is in its initial developmental stages. Therefore, this research has explored the travel needs of older Chinese vehicle users in order to assist designers to better understand users’ current and future needs. A triangulation method consisting of interviews, logbook and co-discovery was used to collect multiple forms of data and so explore the research question. Grounded theory has been employed to analyze the research data. This study found that users’ needs are reflected through various ‘meanings’ that they attach to vehicles – meanings that give a tangible expression to their experiences. This study identified six older-user need categories: (i) safety, (ii) utility, (iii) comfort, (iv) identity, (v) emotion and (vi) spirituality. The interrelationships among these six categories are seen as an interactive structure, rather than as a linear or hierarchical arrangement. Chinese cultural values, which are generated from particular local context and users’ social practice, will play a dynamic role in linking and shaping the travel needs of older vehicle users in the future. Moreover, this study structures the older-user needs model into three levels of meaning, to give guidance to vehicle design direction: (i) the practical meaning level, (ii) the social meaning level and (ii) the cultural meaning level. This study suggests that a more comprehensive explanation exists if designers can identify the vehicle’s meaning and property associated with the fulfilled older users’ needs. However, these needs will vary, and must be related to particular technological, social, and cultural contexts. The significance of this study lies in its contributions to the body of knowledge in three areas: research methodology, theory and design. These theoretical contributions provide a series of methodological tools, models and approaches from a vehicle design perspective. These include a conditional/consequential matrix, a travel needs identification model, an older users’ travel-related needs framework, a user information structure model, and an Older-User-Need-Based vehicle design approach. These models suggest a basic framework for the new design process which might assist in the design of new vehicles to fulfil the needs of future, aging Chinese generations. The models have the potential to be transferred to other design domains and different cultural contexts.

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Principal Topic The study of the origin and characteristics of venture ideas - or ''opportunities'' as they are often called - and their contextual fit are key research goals in entrepreneurship (Davidsson, 2004). We define venture idea as ''the core ideas of an entrepreneur about what to sell, how to sell, whom to sell and how an entrepreneur acquire or produce the product or service which he/she sells'' for the purpose of this study. When realized the venture idea becomes a ''business model''. Even though venture ideas are central to entrepreneurship yet its characteristics and their effect to the entrepreneurial process is mysterious. According to Schumpeter (1934) entrepreneurs could creatively destruct the existing market condition by introducing new product/service, new production methods, new markets, and new sources of supply and reorganization of industries. The introduction, development and use of new ideas are generally called as ''innovation'' (Damanpour & Wischnevsky, 2006) and ''newness'' is a property of innovation and is a relative term which means that the degree of unfamiliarity of venture idea either to a firm or to a market. However Schumpeter's (1934) discusses five different types of newness, indicating that type of newness is an important issue. More recently, Shane and Venkataraman (2000) called for research taking into consideration not only the variation of characteristics of individuals but also heterogeneity of venture ideas, Empirically, Samuelson (2001, 2004) investigated process differences between innovative venture ideas and imitative venture ideas. However, he used only a crude dichotomy regarding the venture idea newness. According to Davidsson, (2004) as entrepreneurs could introduce new economic activities ranging from pure imitation to being new to the entire world market, highlighting that newness is a matter of degree. Dahlqvist (2007) examined the venture idea newness and made and attempt at more refined assessment of the degree and type of newness of venture idea. Building on these predecessors our study refines the assessment of venture idea newness by measuring the degree of venture idea newness (new to the world, new to the market, substantially improved while not entirely new, and imitation) for four different types of newness (product/service, method of production, method of promotion, and customer/target market). We then related type and degree of newness to the pace of progress in nascent venturing process. We hypothesize that newness will slow down the business creation process. Shane & Venkataraman (2000) introduced entrepreneurship as the nexus of opportunities and individuals. In line with this some scholars has investigated the relationship between individuals and opportunities. For example Shane (2000) investigates the relatedness between individuals' prior knowledge and identification of opportunities. Shepherd & DeTinne (2005) identified that there is a positive relationship between potential financial reward and the identification of innovative venture ideas. Sarasvathy's 'Effectuation Theory'' assumes high degree of relatedness with founders' skills, knowledge and resources in the selection of venture ideas. However entrepreneurship literature is scant with analyses of how this relatedness affects to the progress of venturing process. Therefore, we assess the venture ideas' degree of relatedness to prior knowledge and resources, and relate these, too, to the pace of progress in nascent venturing process. We hypothesize that relatedness will increase the speed of business creation. Methodology For this study we will compare early findings from data collected through the Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE). CAUSEE is a longitudinal study whose primary objective is to uncover the factors that initiate, hinder and facilitate the process of emergence and development of new firms. Data were collected from a representative sample of some 30,000 households in Australia using random digit dialing (RDD) telephone survey interviews. Through the first round of data collection identified 600 entrepreneurs who are currently involved in the business start-up process. The unit of the analysis is the emerging venture, with the respondent acting as its spokesperson. The study methodology allows researchers to identify ventures in early stages of creation and to longitudinally follow their progression through data collection periods over time. Our measures of newness build on previous work by Dahlqvist (2007). Our adapted version was developed over two pre-tests with about 80 participants in each. The measures of relatedness were developed through the two rounds of pre-testing. The pace of progress in the venture creation process is assessed with the help of time-stamped gestation activities; a technique developed in the Panel Study of Entrepreneurial Dynamics (PSED). Results and Implications We hypothesized that venture idea newness slows down the venturing process whereas relatedness facilitates the venturing process. Results of 600 nascent entrepreneurs in Australia indicated that there is marginal support for the hypothesis that relatedness assists the gestation progress. Newness is significant but is the opposite sign to the hypothesized. The results give number of implications for researchers, business founders, consultants and policy makers in terms of better knowledge of the venture creation process.