939 resultados para Task-Technology Fit
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BACKGROUND There is little doubt that our engineering graduates’ ability to identify cultural differences and their potential to impact on engineering projects, and to work effectively with these differences is of key importance in the modern engineering practice. Within engineering degree programs themselves there is also a significant need to recognise the impact of changing student and staff profiles on what happens in the classroom. The research described in this paper forms part of a larger project exploring issues of intercultural competence in engineering. PURPOSE This paper presents an observational and survey study of undergraduate and postgraduate engineering students from four institutions working in groups on tasks with a purely technical focus, or with a cultural and humanitarian element. The study sought to explore how students rate their own intercultural competence and team process and whether any differences exist depending on the nature of the task they are working on. We also investigated whether any differences were evident between groups of first year, second year and postgraduate students. DESIGN/METHOD The study used the miniCQS instrument (Ang & Van Dyne, 2008) and a Bales Interaction Process Analysis based scale (Bales, 1950; Carney, 1976) to collect students self ratings of group process, task management, and cultural experience and behaviour. The Bales IPA was also used for coding video observations of students working in groups. Survey data were used to form descriptive variables to compare outcomes across the different tasks and contexts. Observations analysed in Nvivo were used to provide commentary and additional detail on the quantitative data. RESULTS The results of the survey indicated consistent mean scores on each survey item for each group of students, despite vastly different tasks, student backgrounds and educational contexts. Some small, statistically significant mean differences existed, offering some basic insights into how task and student group composition could affect self ratings. Overall though, the results suggest minimal shift in how students view group function and their intercultural experience, irrespective of differing educational experience. CONCLUSIONS The survey results, contrasted with group observations, indicate that either students are not translating their experience (in the group tasks) into critical self assessment of their cultural competence and teamwork, or that they become more critical of team performance and cultural competence as their competence in these areas grows, so their ratings remain consistent. Both outcomes indicate that students need more intensive guidance to build their critical self and peer assessment skills in these areas irrespective of their year level of study.
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There is a growing gap between engineering practice and engineering education that may be contributing to less engineers practicing in industry. Coaching approach to learning and teaching has been proven to be an effective way to develop people in the workplace. A pilot coaching program is offered to Engineering and Technology students in Queensland University of Technology to enable holistic growth in order to better integrate them to the work force and society at large. The results and findings of this program will be published once the program has been completed
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Amongst the most prominent uses of Twitter at present is its role in the discussion of widely televised events: Twitter’s own statistics for 2011, for example, list major entertainment spectacles (the MTV Music Awards, the BET Awards) and sports matches (the UEFA Champions League final, the FIFA Women’s World Cup final) amongst the events generating the most tweets per second during the year (Twitter, 2011). User activities during such televised events constitute a specific, unique category of Twitter use, which differs clearly from the other major events which generate a high rate of tweets per second (such as crises and breaking news, from the Japanese earthquake and tsunami to the death of Steve Jobs), as preliminary research has shown. During such major media events, by contrast, Twitter is used most predominantly as a technology of fandom instead: it serves in the first place as a backchannel to television and other streaming audiovisual media, enabling users offer their own running commentary on the universally shared media text of the event broadcast as it unfolds live. Centrally, this communion of fans around the shared text is facilitated by the use of Twitter hashtags – unifying textual markers which are now often promoted to prospective audiences by the broadcasters well in advance of the live event itself. This paper examines the use of Twitter as a technology for the expression of shared fandom in the context of a major, internationally televised annual media event: the Eurovision Song Contest. It constitutes a highly publicised, highly choreographed media spectacle whose eventual outcomes are unknown ahead of time and attracts a diverse international audience. Our analysis draws on comprehensive datasets for the ‘official’ event hashtags, #eurovision, #esc, and #sbseurovision. Using innovative methods which combine qualitative and quantitative approaches to the analysis of Twitter datasets containing several hundreds of thousands, we examine overall patterns of participation to discover how audiences express their fandom throughout the event. Minute-by-minute tracking of Twitter activity during the live broadcasts enables us to identify the most resonant moments during each event; we also examine the networks of interaction between participants to detect thematically or geographically determined clusters of interaction, and to identify the most visible and influential participants in each network. Such analysis is able to provide a unique insight into the use of Twitter as a technology for fandom and for what in cultural studies research is called ‘audiencing’: the public performance of belonging to the distributed audience for a shared media event. Our work thus contributes to the examination of fandom practices led by Henry Jenkins (2006) and other scholars, and points to Twitter as an important new medium facilitating the connection and communion of such fans.
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While business transformations often primarily focus on technological and methodological solutions, there is consensus that having the right organizational culture is critical for the successful change of business processes.
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The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.
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Science is often considered as one of the cornerstones of human advancement. Despite its importance in our society, science as a subject in schools appears to be losing ground. Lack of relevance, the nature of the curriculum and the pedagogical approach to teaching are some of the reasons which researchers believe are causing a “swing” away from science. This paper will argue for the effectiveness of simple science demonstrations as a feasible pedagogical option with a high task value and which has the potential to reengage and reinvigorate student interest in the subject. This paper describes a case study (N = 25) in which the Integrative problem based learning model for science was implemented in a year nine science class. The study was conducted at a secondary school in Australia. Teacher demonstrations were situated in classroom activities in a “Why is it so?” problem/question format. Qualitative data gathered from students demonstrated a number of benefits of this approach. This paper then explores ways in which Web 2.0 technologies could be incorporated to enhance the value of science demonstrations
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Elaborated Intrusion theory (EI theory; Kavanagh, Andrade, & May, 2005) posits two main cognitive components in craving: associative processes that lead to intrusive thoughts about the craved substance or activity, and elaborative processes supporting mental imagery of the substance or activity. We used a novel visuospatial task to test the hypothesis that visual imagery plays a key role in craving. Experiment 1 showed that spending 10 min constructing shapes from modeling clay (plasticine) reduced participants' craving for chocolate compared with spending 10 min 'letting your mind wander'. Increasing the load on verbal working memory using a mental arithmetic task (counting backwards by threes) did not reduce craving further. Experiment 2 compared effects on craving of a simpler verbal task (counting by ones) and clay modeling. Clay modeling reduced overall craving strength and strength of craving imagery, and reduced the frequency of thoughts about chocolate. The results are consistent with EI theory, showing that craving is reduced by loading the visuospatial sketchpad of working memory but not by loading the phonological loop. Clay modeling might be a useful self-help tool to help manage craving for chocolate, snacks and other foods.
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In this paper, we report on how peer scaffolding was used to effect change in tertiary teaching practice and academic disposition in the use of Information and Communication Technology (ICT) in Science teaching and learning. We present a small-scale case study investigating the practice of one of this paper’s authors. It is told through two salient episodes which narratively describe the scaffolding used to support a teaching experiment. This was made possible through the national Teaching Teachers for the Future Project (2011-2012) which aimed to enhance the technological pedagogical capability of pre-service teachers across Australia. The outcome was a demonstrable shift in the academic’s disposition towards the use and benefits of ICT in teaching science and an increase in skills and confidence for both the academic and his students. This study and its outcomes fit within the contemporary push to “re-imagine” the teaching of Science, and more broadly of STEM, in schools.
Resumo:
In this paper, we report on how peer scaffolding was used to effect change in tertiary teaching practice and academic disposition in the use of Information and Communication Technology (ICT) in Science teaching and learning. We present a small-scale case study investigating the practice of one of this paper’s authors. It is told through two salient episodes which narratively describe the scaffolding used to support a teaching experiment. This was made possible through the national Teaching Teachers for the Future Project (2011-2012) which aimed to enhance the technological pedagogical capability of pre-service teachers across Australia. The outcome was a demonstrable shift in the academic’s disposition towards the use and benefits of ICT in teaching science and an increase in skills and confidence for both the academic and his students. This study and its outcomes fit within the contemporary push to “re-imagine” the teaching of Science, and more broadly of STEM, in schools.
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Twenty first century learners operate in organic, immersive environments. A pedagogy of student-centred learning is not a recipe for rooms. A contemporary learning environment is like a landscape that grows, morphs, and responds to the pressures of the context and micro-culture. There is no single adaptable solution, nor a suite of off-the-shelf answers; propositions must be customisable and infinitely variable. They must be indeterminate and changeable; based on the creation of learning places, not restrictive or constraining spaces. A sustainable solution will be un-fixed, responsive to the life cycle of the components and materials, able to be manipulated by the users; it will create and construct its own history. Learning occurs as formal education with situational knowledge structures, but also as informal learning, active learning, blended learning social learning, incidental learning, and unintended learning. These are not spatial concepts but socio-cultural patterns of discovery. Individual learning requirements must run free and need to be accommodated as the learner sees fit. The spatial solution must accommodate and enable a full array of learning situations. It is a system not an object. Three major components: 1. The determinate landscape: in-situ concrete 'plate' that is permanent. It predates the other components of the system and remains as a remnant/imprint/fossil after the other components of the system have been relocated. It is a functional learning landscape in its own right; enabling a variety of experiences and activities. 2. The indeterminate landscape: a kit of pre-fabricated 2-D panels assembled in a unique manner at each site to suit the client and context. Manufactured to the principles of design-for-disassembly. A symbiotic barnacle like system that attaches itself to the existing infrastructure through the determinate landscape which acts as a fast growth rhizome. A carapace of protective panels, infinitely variable to create enclosed, semi-enclosed, and open learning places. 3. The stations: pre-fabricated packages of highly-serviced space connected through the determinate landscape. Four main types of stations; wet-room learning centres, dry-room learning centres, ablutions, and low-impact building services. Entirely customised at the factory and delivered to site. The stations can be retro-fitted to suit a new context during relocation. Principles of design for disassembly: material principles • use recycled and recyclable materials • minimise the number of types of materials • no toxic materials • use lightweight materials • avoid secondary finishes • provide identification of material types component principles • minimise/standardise the number of types of components • use mechanical not chemical connections • design for use of common tools and equipment • provide easy access to all components • make component size to suite means of handling • provide built in means of handling • design to realistic tolerances • use a minimum number of connectors and a minimum number of types system principles • design for durability and repeated use • use prefabrication and mass production • provide spare components on site • sustain all assembly and material information
Resumo:
Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.
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Waste management and minimisation is considered to be an important issue for achieving sustainability in the construction industry. Retrofit projects generate less waste than demolitions and new builds, but they possess unique features and require waste management approaches that are different to traditional new builds. With the increasing demand for more energy efficient and environmentally sustainable office spaces, the office building retrofit market is growing in capital cities around Australia with a high level of refurbishment needed for existing aging properties. Restricted site space and uncertain delivery process in these projects make it a major challenge to manage waste effectively. The labour-intensive nature of retrofit projects creates the need for the involvement of small and medium enterprises (SMEs) as subcontractors in on-site works. SMEs are familiar with on-site waste generation but are not as actively motivated and engaged in waste management activities as the stakeholders in other construction projects in the industry. SMEs’ responsibilities for waste management in office building retrofit projects need to be identified and adapted to the work delivery processes and the waste management system supported by project stakeholders. The existing literature provides an understanding of how to manage construction waste that is already generated and how to increase the waste recovery rate for office building retrofit projects. However, previous research has not developed theories or practical solutions that can guide project stakeholders to understand the specific waste generation process and effectively plan for and manage waste in ongoing project works. No appropriate method has been established for the potential role and capability of SMEs to manage and minimise waste from their subcontracting works. This research probes into the characteristics of office building retrofit project delivery with the aim to develop specific tools to manage waste and incorporate SMEs in this process in an appropriate and effective way. Based on an extensive literature review, the research firstly developed a questionnaire survey to identify the critical factors of on-site waste generation in office building retrofit projects. Semi-structured interviews were then utilised to validate the critical waste factors and establish the interrelationships between the factors. The interviews served another important function of identifying the current problems of waste management in the industry and the performance of SMEs in this area. Interviewees’ opinions on remedies to the problems were also collected. On the foundation of the findings from the questionnaire survey and semi-structured interviews, two waste planning and management strategies were identified for the dismantling phase and fit-out phase of office building retrofit projects, respectively. Two models were then established to organize SMEs’ waste management activities, including a work process-based integrated waste planning model for the dismantling phase and a system dynamics model for the fit-out phase. In order to apply the models in real practice, procedures were developed to guide SMEs’ work flow in on-site waste planning and management. In addition, a collaboration framework was established for SMEs and other project stakeholders for effective waste planning and management. Furthermore, an organisational engagement strategy was developed to improve SME waste management practices. Three case studies were conducted to validate and finalise the research deliverables. This research extends the current literature that mostly covers waste management plans in new build projects, by presenting the knowledge and understanding of addressing waste problems in retrofit projects. It provides practical tools and guidance for industry practitioners to effectively manage the waste generation processes in office building retrofit projects. It can also promote industry-level recognition of the role of SMEs and their performance in on-site waste management.