915 resultados para Aboriginal knowledge domain
Resumo:
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.
Resumo:
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.
Resumo:
Controlling the definition of what was essentially a subjugated culture, the colonisers reserve the power to distinguish authentic aspects of the living traditions of the colonised. If the colonised argue political demands by reference to their culture, the colonisers are quick to adjudicate what is genuine in such claims. (Fannon, 1967) Since colonial invasions, Australia’s Indigenous people have weathered rapid change. While the origins of Australia’s Indigenous peoples continues to be an archaeological interest for many, how Indigenous cultures have survived, transformed and retained a sense of ‘difference’ is fundamental to understanding the diversity of Aboriginal and Torres Strait Islander cultures within this continent as both contemporaneous and historical. It is important that teachers, students and researchers within Indigenous studies remind themselves that much of the literature on Aboriginal and Torres Strait Islanders can be ideologically traced back to the emergence of ‘knowledge’ about native peoples in the context of European imperialism and expansion from the fifteenth century. Care must therefore be taken in not conveying ‘scientific’ rational knowledge as perhaps the hidden agenda or notion of assumptions of European ‘superiority’ and non-European inferiority. The recognition by the High Court of Australia (1992) abandoned the legal myth of terra nullius which based the dispossession of Indigenous land on the basis of it being considered an empty land. It could also be argued that this decision recognised that distinct customs and traditions continue to exist within the social and cultural ‘knowledge’ of Indigenous peoples of Australia. General issues and concerns relating to research design, methodology and articulation within QUT are not just confined to this university and the research project presented as a case study but are important in dealing with how Aboriginal and Torres Strait Islander students and academics participate or are employed within the university. We feel that the design and methodology of research that either covertly or overtly focuses on Indigenous Australians can no longer presume that all research will naturally follow protocols that are culturally appropriate as this appropriateness is usually defined by the institution. By no means do we feel that research should be debilitated as a result of raising these issues, but that collaborative approaches within the ‘process’ of research will address Aboriginal and Torres Strait Islander people and communities as much as the intended outcomes of research itself.
Resumo:
Over the last two decades, the notion of teacher leadership has emerged as a key concept in both the teaching and leadership literature. While researchers have not reached consensus regarding a definition, there has been some agreement that teacher leadership can operate at both a formal and informal level in schools and that it includes leadership of an instructional, organisational and professional development nature (York-Barr & Duke, 2004). Teacher leadership is a construct that tends not to be applied to pre-service teachers as interns, but is more often connected with the professional role of mentors who collaborate with them as they make the transition to being a beginning teacher. We argue that teacher leadership should be recognised as a professional and career goal during this formative learning phase and that interns should be expected to overtly demonstrate signs, albeit early ones, of leadership in instruction and other professional areas of development. The aim of this paper is to explore the extent to which teacher education interns at one university in Queensland reported on activities that may be deemed to be ‘teacher leadership.’ The research approach used in this study was an examination of 145 reflective reports written in 2008 by final Bachelor of Education (primary) pre-service teachers. These reports recorded the pre-service teachers’ perceptions of their professional learning with a school-based mentor in response to four outcomes of internship that were scaffolded by their mentor or initiated by them. These outcomes formed the bases of our research questions into the professional learning of the interns and included, ‘increased knowledge and capacity to teach within the total world of work as a teacher;’ ‘to work autonomously and interdependently’; to make ‘growth in critical reflectivity’, and the ‘ability to initiate professional development with the mentoring process’. Using the approaches of the constant comparative method of Strauss and Corbin (1998) key categories of experiences emerged. These categories were then identified as belonging to main meta-category labelled as ‘teacher leadership.’ Our research findings revealed that five dimensions of teacher leadership – effective practice in schools; school curriculum work; professional development of colleagues; parent and community involvement; and contributions to the profession – were evident in the written reports by interns. Not surprisingly, the mentor/intern relationship was the main vehicle for enabling the intern to learn about teaching and leadership. The paper concludes with some key implications for developers of preservice education programmes regarding the need for teacher leadership to be part of the discourse of these programmes.
Resumo:
With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.
Resumo:
Major global changes are placing new demands on the Australian education system. Recent statements by the Prime Minister, together with current education policy and national curriculum documents available in the public domain, look to education’s role in promoting economic prosperity and social cohesion. Collectively, they emphasise the need to equip young Australians with the knowledge, understandings and skills required to compete in the global economy and participate as engaged citizens in a culturally diverse world. However, the decision to prioritise discipline-based learning in the forthcoming Australian history curriculum without specifically encompassing culture as a referent, raises the following question. How will students acquire the cultural knowledge, understandings and skills necessary for this process? This paper addresses this question by situating the current push for a national history curriculum, with specific reference to the study of Indigenous history and the study of Asia in Australia.
Resumo:
This is a book review of Indigenous Peoples: Self-Determination Knowledge Indigeneity. Edited by Henry Minde in collaboration with Harald Gaski, Svein Jentoft and Georges Midre. Published by Eburon Academic Publishers in Delft, the Netherlands. Paperback, 382 pages, no index. AUD. $79.99. ISBN 978-90-5972-204-0.
Resumo:
The International Network of Indigenous Health Knowledge and Development (INIHKD) Conference was held from Monday 24 May to Friday 28 May 2010 at Kiana Lodge, Port Madison Indian Reservation, Suquamish Nation, Washington State, United States of America. The overall theme for the 4th Biennial Conference was ‘Knowing Our Roots: Indigenous Medicines, Health Knowledges and Best Practices’. This article details the experience of participants who were at the INIHKD Conference. It concludes with an encouragement to people to attend the 5th INIHKD Conference in Australia in 2012.
Resumo:
Mathematics education literature has called for an abandonment of ontological and epistemological ideologies that have often divided theory-based practice. Instead, a consilience of theories has been sought which would leverage the strengths of each learning theory and so positively impact upon contemporary educational practice. This research activity is based upon Popper’s notion of three knowledge worlds which differentiates the knowledge shared in a community from the personal knowledge of the individual, and Bereiter’s characterisation of understanding as the individual’s relationship to tool-like knowledge. Using these notions, a re-conceptualisation of knowledge and understanding and a subsequent re-consideration of learning theories are proposed as a way to address the challenge set by literature. Referred to as the alternative theoretical framework, the proposed theory accounts for the scaffolded transformation of each individual’s unique understanding, whilst acknowledging the existence of a body of domain knowledge shared amongst participants in a scientific community of practice. The alternative theoretical framework is embodied within an operational model that is accompanied by a visual nomenclature with which to describe consensually developed shared knowledge and personal understanding. This research activity has sought to iteratively evaluate this proposed theory through the practical application of the operational model and visual nomenclature to the domain of early-number counting, addition and subtraction. This domain of mathematical knowledge has been comprehensively analysed and described. Through this process, the viability of the proposed theory as a tool with which to discuss and thus improve the knowledge and understanding with the domain of mathematics has been validated. Putting of the proposed theory into practice has lead to the theory’s refinement and the subsequent achievement of a solid theoretical base for the future development of educational tools to support teaching and learning practice, including computer-mediated learning environments. Such future activity, using the proposed theory, will advance contemporary mathematics educational practice by bringing together the strengths of cognitivist, constructivist and post-constructivist learning theories.
Resumo:
Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.
Resumo:
Towards the last decade of the last millennium, Indigenous knowledge has been central to scholarly debates relating to decolonising knowledge on a global level. Much of these debates were advanced by Indigenous scholars in colonised countries particularly Australia, New Zealand, Canada and the United States. Indigenous scholars argue for the location of Indigenous knowledge as the epistemological standpoint (Battiste, Bell and Findlay, 2002; Kai’a, 2005; Nakata 2002, 2007) for intellectual engagements and methodology for resisting colonial constructions of the colonised other (Rigney, 1997; Smith, 1999, 2005). However, the challenge to engage Indigenous knowledge to inform research and educational processes, in many respects, is still a contested debate in western-oriented universities and institutions of higher education. The place of Indigenous knowledge in Australian secondary and primary schools remains vague, while efforts to embed Indigenous perspectives in the curriculum continue to be made by both government and private educational providers. Educational funding for Indigenous education continues to operate from a ‘deficiency’ model, whereby educational outcomes are often measured against set criteria, reflecting a pass/fail structure, than a more comprehensive investigation of educational outcomes and quality of learning experiences. Teacher knowledge, effective parental and community engagement into students’ learning and students’ experiences of schooling continue to be secondary to students’ final results. This paper presents preliminary findings of Parent School Partnership Initiative (PSPI) project conducted by the Oodgeroo Unit at the Queensland University of Technology in partnerships with the Aboriginal and Torres Strait Islander Education Focus Group for the Caboolture Shire, in South East Queensland. The state government sponsored initiative was to examine factors that promote and enhance parent/school engagement with their students’ schooling, and to contribute to Aboriginal and Torres Strait Islander students’ learning and completion of secondary schooling within the participating schools in a more holistic way. We present four school case studies and discuss some of the early findings. We conclude by arguing the importance of the recognition of Indigenous knowledge and its place in enhancing parent – schools partnerships.
Resumo:
This special issue presents an excellent opportunity to study applied epistemology in public policy. This is an important task because the arena of public policy is the social domain in which macro conditions for ‘knowledge work’ and ‘knowledge industries’ are defined and created. We argue that knowledge-related public policy has become overly concerned with creating the politico-economic parameters for the commodification of knowledge. Our policy scope is broader than that of Fuller (1988), who emphasizes the need for a social epistemology of science policy. We extend our focus to a range of policy documents that include communications, science, education and innovation policy (collectively called knowledge-related public policy in acknowledgement of the fact that there is no defined policy silo called ‘knowledge policy’), all of which are central to policy concerned with the ‘knowledge economy’ (Rooney and Mandeville, 1998). However, what we will show here is that, as Fuller (1995) argues, ‘knowledge societies’ are not industrial societies permeated by knowledge, but that knowledge societies are permeated by industrial values. Our analysis is informed by an autopoietic perspective. Methodologically, we approach it from a sociolinguistic position that acknowledges the centrality of language to human societies (Graham, 2000). Here, what we call ‘knowledge’ is posited as a social and cognitive relationship between persons operating on and within multiple social and non-social (or, crudely, ‘physical’) environments. Moreover, knowing, we argue, is a sociolinguistically constituted process. Further, we emphasize that the evaluative dimension of language is most salient for analysing contemporary policy discourses about the commercialization of epistemology (Graham, in press). Finally, we provide a discourse analysis of a sample of exemplary texts drawn from a 1.3 million-word corpus of knowledge-related public policy documents that we compiled from local, state, national and supranational legislatures throughout the industrialized world. Our analysis exemplifies a propensity in policy for resorting to technocratic, instrumentalist and anti-intellectual views of knowledge in policy. We argue that what underpins these patterns is a commodity-based conceptualization of knowledge, which is underpinned by an axiology of narrowly economic imperatives at odds with the very nature of knowledge. The commodity view of knowledge, therefore, is flawed in its ignorance of the social systemic properties of knowing’.
Resumo:
This paper, which is abstracted from a larger study into the acquisition and exercise of nephrology nursing expertise, aims to explore the role of knowledge in expert practice. Using grounded theory methodology, the study involved 17 registered nurses who were practicing in a metropolitan renal unit in New South Wales, Australia. Concurrent data collection and analysis was undertaken, incorporating participants' observations and interviews. Having extensive nephrology nursing knowledge was a striking characteristic of a nursing expert. Expert nurses clearly relied on and utilized extensive nephrology nursing knowledge to practice. Of importance for nursing, the results of this study indicate that domain-specific knowledge is a crucial feature of expert practice.
Resumo:
Early-number is a rich fabric of interconnected ideas that is often misunderstood and thus taught in ways that do not lead to rich understanding. In this presentation, a visual language is used to describe the organisation of this domain of knowledge. This visual language is based upon Piaget’s notion of reflective abstraction (Dubinsky, 1991; Piaget, 1977/2001), and thus captures the epistemological associations that link the problems, concepts and representations of the domain. The constructs of this visual language are introduced and then applied to the early-number domain. The introduction to this visual language may prompt reflection upon its suitability and significance to the description of other domains of knowledge. Through such a process of analysis and description, the visual language may serve as a scaffold for enhancing pedagogical content knowledge and thus ultimately improve learning outcomes.