424 resultados para online program development
Resumo:
The present paper describes the development and evaluation of a standardized multi-component therapist training program in guided respiration mindfulness therapy (GRMT). GMRT is a manual-based, experimental clinical intervention involving concentrated focus on sustained self-regulation of breathing, application of mindfulness to emergent somatic experience and relaxation. Therapists (n = 61) new to the approach attended a 2-day experiential workshop and were evaluated pre-post workshop for change in intervention knowledge, as well as change in mindfulness. These trainees also participated in post-workshop focus group sessions to explore perception of the intervention. A subset of 40 therapists participated in a second training component, and 14 of these were rated for competent delivery of the intervention during participation in a clinical trial. During training, therapists personally received the treatment giving the opportunity to assess treatment session (n = 283) impact on sense of wellbeing. Results indicated a brief focused training program can equip therapists with basic knowledge and skills required to deliver the standardized manual-based treatment. Qualitative analysis of focus group sessions showed that therapists endorsed the intervention for clinical use and found it personally beneficial. This research provides a foundation for further evaluation of clinical effectiveness of the intervention.
Resumo:
This paper reports on the design, implementation and outcomes of a mentoring program involving 18 employees in the IT Division of WorkCover Queensland. The paper provides some background information to the development of the program and the design and implementation phases including recruitment and matching of participants, orientation and training, and the mentoring process including transition and/or termination. The paper also outlines the quantitative and qualitative evaluation processes that occurred and the outcomes of that evaluation. Results indicated a wealth of positive individual, mentoring, and organisational outcomes. The organisation and semi-structured processes provided in the program are considered as major contributing factors to the successful outcomes of the program. These outcomes are likely to have long-term benefits for the individuals involved, the IT Division, and the broader organisation
Resumo:
The computing tools and technologies with urban information systems are designed to enhance planners’ capability to deal with complex urban environments and to plan for prosperous and liveable communities. This paper examines the role of Online Urban Information Systems or in another words Internet based Geographic Information Systems as spatial decision support systems to aid local planning process. This paper introduces a prototype Internet GIS model that aims to integrate a public oriented interactive decision support system for urban planning process. This model, referred as a ‘Community based Internet GIS’, incorporates advanced information technologies and community involvement in decision making processes on the web environment. This innovative model has been recently applied to a pilot case in Tokyo and this paper concludes with the preliminary results of this project.
Resumo:
The importance of broadening community participation in environmental decision-making is widely recognized and lack of participation in this process appears to be a perennial problem. In this context, there have been calls from some academics for the more extensive use of geographic information systems (GIS) and distance learning technologies, accessible via the Internet, as a possible means to inform and empower communities. However, a number of problems exist. For instance, at present the scope for online interaction between policy-makers and citizens is currently limited. Contemporary web-based environmental information systems suffer from this lack of interactivity on the one hand and on the other hand from the apparent complexity for the lay user. This paper explores the issue of online community participation at the local level and attempts to construct a framework for a new (and potentially more effective) model of online participatory decision-making. The key components, system architecture and stages of such a model are introduced. This model, referred to as a ‘Community Based Interactive Environmental Decision Support System’, incorporates advanced information technologies, distance learning and community involvement tools which will be applied and evaluated in the field through a pilot project in Tokyo in the summer of 2002.
Resumo:
The use of computing to support environmental planning and the development of land use models dates back to the late 1950s. The main thrust of computing applications, which by the early 1980s increasingly included the use of geospatial technologies, is their contribution to better planning and decision making. The computing tools and technologies are designed to enhance the planners’ capability to deal with complex environments and to plan for prosperous and livable communities. This paper examines the role of Information Technologies (IT) and particularly Internet Based Geographic Information Systems (Internet GIS) as spatial decision support systems to aid community based local decision making. The paper also covers the advantages and challenges of these internet based mapping applications and tools for collaborative decision making on the environment.
Resumo:
Aided by the development of information technology, the balance of power in the market place is rapidly shifting from marketers towards consumers and nowhere is this more obvious than in the online environment (Denegri-Knott, Zwick, & Schroeder, 2006; Moynagh & Worsley, 2002; Newcomer, 2000; Samli, 2001). From the inception and continuous development of the Internet, consumers are becoming more empowered. They can choose what they want to click on the Internet, they can shop and transact payments, watch and download video, chat with others, be it friends or even total strangers. Especially in online communities, like-minded consumers share and exchange information, ideas and opinions. One form of online community is the online brand community, which gathers specific brand lovers. As with any social unit, people form different roles in the community and exert different effects on each other. Their interaction online can greatly influence the brand and marketers. A comprehensive understanding of the operation of this special group form is essential to advancing marketing thought and practice (Kozinets, 1999). While online communities have strongly shifted the balance of power from marketers to consumers, the current marketing literature is sparse on power theory (Merlo, Whitwell, & Lukas, 2004). Some studies have been conducted from an economic point of view (Smith, 1987), however their application to marketing has been limited. Denegri-Knott (2006) explored power based on the struggle between consumers and marketers online and identified consumer power formats such as control over the relationship, information, aggregation and participation. Her study has built a foundation for future power studies in the online environment. This research project bridges the limited marketing literature on power theory with the growing recognition of online communities among marketing academics and practitioners. Specifically, this study extends and redefines consumer power by exploring the concept of power in online brand communities, in order to better understand power structure and distribution in this context. This research investigates the applicability of the factors of consumer power identified by Denegri-Knott (2006) to the online brand community. In addition, by acknowledging the model proposed by McAlexander, Schouten, & Koenig (2002), which emphasized that community study should focus on the role of consumers and identifying multiple relationships among the community, this research further explores how member role changes will affect power relationships as well as consumer likings of the brand. As a further extension to the literature, this study also considers cultural differences and their effect on community member roles and power structure. Based on the study of Hofstede (1980), Australia and China were chosen as two distinct samples to represent differences in two cultural dimensions, namely individualism verses collectivism and high power distance verses low power distance. This contribution to the research also helps answer the research gap identified by Muñiz Jr & O'Guinn (2001), who pointed out the lack of cross cultural studies within the online brand community context. This research adopts a case study methodology to investigate the issues identified above. Case study is an appropriate research strategy to answer “how” and “why” questions of a contemporary phenomenon in real-life context (Yin, 2003). The online brand communities of “Haloforum.net” in Australia and “NGA.cn” in China were selected as two cases. In-depth interviews were used as the primary data collection method. As a result of the geographical dispersion and the preference of a certain number of participants, online synchronic interviews via MSN messenger were utilized along with the face-to-face interviews. As a supplementary approach, online observation was carried over two months, covering a two week period prior to the interviews and a six week period following the interviews. Triangulation techniques were used to strengthen the credibility and validity of the research findings (Yin, 2003). The findings of this research study suggest a new definition of power in an online brand community. This research also redefines the consumer power types and broadens the brand community model developed by McAlexander et al. (2002) in an online context by extending the various relationships between brand and members. This presents a more complete picture of how the perceived power relationships are structured in the online brand community. A new member role is discovered in the Australian online brand community in addition to the four member roles identified by Kozinets (1999), in contrast however, all four roles do not exist in the Chinese online brand community. The research proposes a model which links the defined power types and identified member roles. Furthermore, given the results of the cross-cultural comparison between Australia and China showed certain discrepancies, the research suggests that power studies in the online brand community should be country-specific. This research contributes to the body of knowledge on online consumer power, by applying it to the context of an online brand community, as well as considering factors such as cross cultural difference. Importantly, it provides insights for marketing practitioners on how to best leverage consumer power to serve brand objective in online brand communities. This, in turn, should lead to more cost effective and successful communication strategies. Finally, the study proposes future research directions. The research should be extended to communities of different sizes, to different extents of marketer control over the community, to the connection between online and offline activities within the brand community, and (given the cross-cultural findings) to different countries. In addition, a greater amount of research in this area is recommended to determine the generalizability of this study.
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:
Teacher education programs focussing on the development of specialist teachers for 'the middle years' have proliferated in Australian universities in recent years. This paper provides some insights into middle years' teacher education programs at the University of Queensland, Edith Cowan and Flinders Universities with regard to their: philosophical underpinnings; specific educational context; scope and nature of the program. In addition, some of the research directions and efficacy strategies utilised in conjunction with the programs will be shared, along with some early findings from a longitudinal study in one of the programs. We propose that the pattern of programmatic growth heralds a new time for teacher education, and we speculate about the production of new kinds of teacher identities as graduates take their place in the profession.
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:
The Co-operative Research Centre for Construction Innovation (CRC-CI) is funding a project known as Value Alignment Process for Project Delivery. The project consists of a study of best practice project delivery and the development of a suite of products, resources and services to guide project teams towards the best procurement approach for a specific project or group of projects. These resources will be focused on promoting the principles that underlie best practice project delivery rather than simply identifying an off-the-shelf procurement system. This project builds on earlier work by Sidwell, Kennedy and Chan (2002), on re-engineering the construction delivery process, which developed a procurement framework in the form of a Decision Matrix
Resumo:
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.
Resumo:
Objectives The objectives of this project were two-fold: • Assess the ease with which current architectural CAD systems supported the use ofparametric descriptions in defining building shape, engineering system performance and cost at the early stages of building design; • Assess the feasibility of implementing a software decision support system that allowed designers to trade-off the characteristics and configuration of various engineering systems to move towards a “global optimum” rather than considering each system in isolation and expecting humans to weigh up all of the costs and benefits. The first stage of the project consisted of using four different CAD systems to define building shells (envelopes) with different usages. These models were then exported into a shared database using the IFC information exchange specifications. The second stage involved the implementation of small computer programs that were able to estimate relevant system parameters based on performance requirements and the constraints imposed by the other systems. These are presented in a unified user interface that extracts the appropriate building shape parameters from the shared database Note that the term parametric in this context refers to the relationships among and between all elements of the building model - not just geometric associations - which will enable the desired coordination.