Dancing between diversity and consistency : refining assessment in postgraduate degrees in dance

This publication is the culmination of a 2 year Australian Learning and Teaching Council's Project Priority Programs Research Grant which investigates key issues and challenges in developing flexible guidelines lines for best practice in Australian Doctoral and Masters by Research Examination, encompassing the two modes of investigation, written and multi-modal (practice-led/based) theses, their distinctiveness and their potential interplay. The aims of the project were to address issues of assessment legitimacy raised by the entry of practice-orientated dance studies into Australian higher degrees; examine literal embodiment and presence, as opposed to cultural studies about states of embodiment; foreground the validity of questions around subjectivity and corporeal intelligence/s and the reliability of artistic/aesthetic communications, and finally to celebrate ‘performance mastery’(Melrose 2003) as a rigorous and legitimate mode of higher research. The project began with questions which centred around: the functions of higher degree dance research; concepts of 'master-ness’ and ‘doctorateness’; the kinds of languages, structures and processes which may guide candidates, supervisors, examiners and research personnel; the purpose of evaluation/examination; addressing positive and negative attributes of examination. Finally the study examined ways in which academic/professional, writing/dancing, tradition/creation and diversity/consistency relationships might be fostered to embrace change. Over two years, the authors undertook a qualitative national study encompassing a triangulation of semi-structured face to face interviews and industry forums to gather views from the profession, together with an analysis of existing guidelines, and recent literature in the field. The most significant primary data emerged from 74 qualitative interviews with supervisors, examiners, research deans and administrators, and candidates in dance and more broadly across the creative arts. Qualitative data gathered from the two primary sources, was coded and analysed using the NVivo software program. Further perspectives were drawn from international consultant and dance researcher Susan Melrose, as well as publications in the field, and initial feedback from a draft document circulated at the World Dance Alliance Global Summit in July 2008 in Brisbane. Refinement of data occurred in a continual sifting process until the final publication was produced. This process resulted in a set of guidelines in the form of a complex dynamic system for both product and process oriented outcomes of multi-modal theses, along with short position papers on issues which arose from the research such as contested definitions, embodiment and ephemerality, ‘liveness’ in performance research higher degrees, dissolving theory/practice binaries, the relationship between academe and industry, documenting practices and a re-consideration of the viva voce.

Refining animal models in fracture research: Seeking consensus in optimising both animal welfare and scientific validity for appropriate biomedical use

Background In an attempt to establish some consensus on the proper use and design of experimental animal models in musculoskeletal research, AOVET (the veterinary specialty group of the AO Foundation) in concert with the AO Research Institute (ARI), and the European Academy for the Study of Scientific and Technological Advance, convened a group of musculoskeletal researchers, veterinarians, legal experts, and ethicists to discuss, in a frank and open forum, the use of animals in musculoskeletal research. Methods The group narrowed the field to fracture research. The consensus opinion resulting from this workshop can be summarized as follows: Results & Conclusion Anaesthesia and pain management protocols for research animals should follow standard protocols applied in clinical work for the species involved. This will improve morbidity and mortality outcomes. A database should be established to facilitate selection of anaesthesia and pain management protocols for specific experimental surgical procedures and adopted as an International Standard (IS) according to animal species selected. A list of 10 golden rules and requirements for conduction of animal experiments in musculoskeletal research was drawn up comprising 1) Intelligent study designs to receive appropriate answers; 2) Minimal complication rates (5 to max. 10%); 3) Defined end-points for both welfare and scientific outputs analogous to quality assessment (QA) audit of protocols in GLP studies; 4) Sufficient details for materials and methods applied; 5) Potentially confounding variables (genetic background, seasonal, hormonal, size, histological, and biomechanical differences); 6) Post-operative management with emphasis on analgesia and follow-up examinations; 7) Study protocols to satisfy criteria established for a "justified animal study"; 8) Surgical expertise to conduct surgery on animals; 9) Pilot studies as a critical part of model validation and powering of the definitive study design; 10) Criteria for funding agencies to include requirements related to animal experiments as part of the overall scientific proposal review protocols. Such agencies are also encouraged to seriously consider and adopt the recommendations described here when awarding funds for specific projects. Specific new requirements and mandates related both to improving the welfare and scientific rigour of animal-based research models are urgently needed as part of international harmonization of standards.

Refining a teaching pattern: Reflection around artefacts

This book is about understanding the nature and application of reflection in higher education. It provides a theoretical model to guide the implementation of reflective learning and reflective practice across multiple disciplines and international contexts in higher education. The book presents research into the ways in which reflection is both considered and implemented in different ways across different professional disciplines, while maintaining a common purpose to transform and improve learning and/or practice. Chapter 13 'Refining a Teaching Pattern: Reflection Around Artefacts' explores reflective practices of an artefact, in this case fashion design garment samples.

Refining user and item profiles based on multidimensional data for top-n item recommendation

In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.

Refining prognosis and identifying targetable pathways for high-risk endometrial cancer; a TransPORTEC initiative

This study aimed to investigate whether molecular analysis can be used to refine risk assessment, direct adjuvant therapy, and identify actionable alterations in high-risk endometrial cancer. TransPORTEC, an international consortium related to the PORTEC3 trial, was established for translational research in high-risk endometrial cancer. In this explorative study, routine molecular analyses were used to detect prognostic subgroups: p53 immunohistochemistry, microsatellite instability and POLE proofreading mutation. Furthermore, DNA was analyzed for hotspot mutations in 13 additional genes (BRAF, CDKNA2, CTNNB1, FBXW7, FGFR2, FGFR3, FOXL2, HRAS, KRAS, NRAS, PIK3CA, PPP2R1A, and PTEN) and protein expression of ER, PR, PTEN, and ARID1a was analyzed. Rates of distant metastasis, recurrence-free, and overall survival were calculated using the Kaplan-Meier method and log-rank test. In total, samples of 116 high-risk endometrial cancer patients were included: 86 endometrioid; 12 serous; and 18 clear cell. For endometrioid, serous, and clear cell cancers, 5-year recurrence-free survival rates were 68%, 27%, and 50% (P=0.014) and distant metastasis rates 23%, 64%, and 50% (P=0.001), respectively. Four prognostic subgroups were identified: (1) a group of p53-mutant tumors; (2) microsatellite instable tumors; (3) POLE proofreading-mutant tumors; and (4) a group with no specific molecular profile (NSMP). In group 3 (POLE-mutant; n=14) and group 2 (microsatellite instable; n=19) patients, no distant metastasis occurred, compared with 50% distant metastasis rate in group 1 (p53-mutant; n=36) and 39% in group 4 (NSMP; P<0.001). Five-year recurrence-free survival was 93% and 95% for group 3 (POLE-mutant) and group 2 (microsatellite instable) vs 42% (group 1, p53-mutant) and 52% (group 4, NSMP; P<0.001). Targetable FBXW7 and FGFR2 mutations (6%), alterations in the PI3K-AKT pathway (60%) and hormone receptor positivity (45%) were frequently found. In conclusion, molecular analysis of high-risk endometrial cancer identifies four distinct prognostic subgroups, with potential therapeutic implications. High frequencies of targetable alterations were identified and may serve as targets for individualized treatment

Manufacturing challenges with fabrication of large size mechanical harmonic drives

Mechanical harmonic transmissions are relatively new kind of drives having several unusual features. For example, they can provide reduction ratio up to 500:1 in one stage, have very small teeth module compared to conventional drives and very large number of teeth (up to 1000) on a flexible gear. If for conventional drives manufacturing methods are well-developed, fabrication of large size harmonic drives presents a challenge. For example, how to fabricate a thin shell of 1.7m in diameter and wall thickness of 30mm having high precision external teeth at one end and internal splines at the other end? It is so flexible that conventional fabrication methods become unsuitable. In this paper special fabrication methods are discussed that can be used for manufacturing of large size harmonic drive components. They include electro-slag welding and refining, the use of special expandable devices to locate and hold a flexible gear, welding peripheral parts of disks with wear resistant materials with subsequent machining and others. These fabrication methods proved to be effective and harmonic drives built with the use of these innovative technologies have been installed on heavy metallurgical equipment and successfully tested.

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.

Demonstration of Software Agents Prototype System : [AIMM] Agents for Improving Maintenance Management

This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. • Refining the development of a multi agent system for data mining in virtual environments (Active Worlds) by developing and implementing a filtering agent on the results obtained from applying data mining techniques on the maintenance data. • Integrating the filtering agent within the multi agents system in an interactive networked multi-user 3D virtual environment. • Populating maintenance data and discovering new rules of knowledge.

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.

Towards self-authorship in child care students : implications for working with children and their families

Using self authorship as a theoretical framework, this chapter examines the relationship between personal epistemology and beliefs about children’s learning for students studying to be child care workers in Australia. Scenario-based interviews were used to investigate how students’ views of knowledge, identity and relationships with others were related to beliefs about how children learn. Implications for vocational education are discussed.

Are library and information professionals ready for evidence based practice?

Evidence based practice (EBP) is recognised as a way of improving the quality of professional practice in many disciplines however its adoption within library and information sciences (LIS) has been gradual. The term was first introduced into the library and information profession‟s vocabulary a decade ago but an impediment to its uptake is the lack of clear understanding regarding how LIS practitioners understand the concept. Partridge, Thorpe, Edwards and Hallam (2007) identified the need to understand how LIS professionals experience or understand evidence based practice and proposed a model of four categories of experience to describe how LIS professionals experience EBP. This paper extends that framework by refining the different conceptions of evidence based practice and identifying relationships which exist between the categories of experience to provide a rich description of the EBP phenomenon. The paper also argues that the phrase “evidence based librarianship” and its variations be abandoned as practitioners do not see a distinction between EBP as applied to librarianship and information practice and industry specific jargon like “evidence based library and information practice”. This research will help current and future LIS practitioners, leaders and educators engage more actively in the establishment of an evidence based culture to improve library and information practice in Australia and internationally.

Choreographing research : supervising the dancing thesis

The dancing doctorate is an interrogative endeavour which can but nurture the art form and forge a beneficial dynamism between those who seek and those who assess the emerging knowledges of dance’. (Vincs, 2009) From 2006-2008 three dance academics from Perth, Brisbane and Melbourne undertook a research project entitled Dancing between Diversity and Consistency: Refining Assessment in Postgraduate Degrees in Dance, funded by the ALTC Priority Projects Program. Although assessment rather than supervision was the primary focus of this research, interviews with 40 examiner/supervisors, 7 research deans and 32 candidates across Australia and across the creative arts, primarily in dance, provide an insight into what might be considered best practice in preparing students for higher research degrees, and the challenges that embodied and experiential knowledges present for supervision. The study also gained the industry perspectives of dance professionals in a series of national forums in 5 cities, based around the value of higher degrees in dance. The qualitative data gathered from these two primary sources was coded and analysed using the NVivo system. Further perspectives were drawn from international consultant and dance researcher Susan Melrose, as well as recent publications in the field. Dance is a young addition to academia and consequently there tends to be a close liaison between the academy and the industry, with a relational fluidity that is both beneficial and problematic. This partially explains why dance research higher degrees are predominantly practice-led (or multi-modal, referring to those theses where practice comprises the substantial examinable component). As a physical, embodied art form, dance engages with the contested territory of legitimising alternative forms of knowledge that do not sit comfortably with accepted norms of research. In supporting research students engaged with dance practice, supervisors traverse the tricky terrain of balancing university academic requirements with studies that are emergent, not only in the practice and attendant theory but in their methodologies and open-ended outcomes; and in an art form in which originality and new knowledge also arises from collaborative creative processes. Formal supervisor accreditation through training is now mandatory in most Australian universities, but it tends to be generic and not address supervisory specificity. This paper offers the kind of alternative proposed by Edwards (2002) that improving postgraduate supervision will be effective if supervisors are empowered to generate their own standards and share best practice; in this case, in ways appropriate to the needs of their discipline and alternative modes of thesis presentation. In order to frame the qualities and processes conducive to this goal, this paper will draw on both the experiences of interviewees and on philosophical premises which underpin the research findings of our study. These include the ongoing challenge of dissolving the binary oppositions of theory and practice, especially in creative arts practice where theory resides in and emerges from the doing as much as in articulating reflection about the doing through what Melrose (2003) terms ‘mixed mode disciplinary practices’. In guiding practitioners through research higher degrees, how do supervisors deal with not only different forms of knowledge but indeed differing modes of knowledge? How can they navigate tensions that occur between the ‘incompatible competencies’ (Candlin, 2000) of the ‘spectating’ academic experts with their ‘irrepressible drive ... to inscribe, interpret, and hence to practise temporal closure’, and practitioner experts who create emergent works of ‘residual unfinishedness’ (Melrose 2006) which are not only embodied but ephemeral, as in the case of live performance?