309 resultados para Unified User Experience Model


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The importance of the first year experience (FYE) to success at university has been a focus of attention in the Australian higher education sector since the 1990s. For students a successful transition into university during their first year is now regarded as crucial for student engagement, success and retention. In this review we summarise a decade of research into FYE in the Australasian context. We draw on the findings arising from this comprehensive review of FYE programs and practices to describe FYE trends through the dual lenses of the first year curriculum principles and the generational approach to FYE initiatives. We contend that the generational approach to conceptualising the FYE and first year student engagement has made a useful but limited contribution to our understanding of the first year experience. Acknowledging the criticality of student engagement in a successful FYE, we propose an alternative— the Student Engagement Success and Retention Maturity Model (SESR-MM)— as a sophisticated vehicle for achieving whole-of-institution approaches to the FYE. The SESR-MM embodies the aspirations and characteristics of the transition pedagogy, highlights the need for institutional level evaluation of the FYE, focuses attention on the capacity of institutions to mobilise for first year student engagement, and importantly builds on the generational approach to allow an assessment of institutional capacity to initiate, plan, manage, evaluate and review institutional FYE practices.

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Research with typically developing groups has identified loneliness as a significant predictor of a range of physical and mental health problems. This paper reviews research about loneliness in children and adults with intellectual disability. Although a considerable body of evidence has highlighted the difficulties individuals with intellectual disability have with friendships, there is a relative scarcity of research focused explicitly on loneliness. The available evidence suggests that up to half of those with intellectual disability are chronically lonely, compared with around 15-30% of people in the general population. The cognitive, physical and mental health problems already associated with intellectual disability are likely to be compounded by experiences of chronic loneliness. We argue that people with intellectual disability are highly vulnerable to loneliness and present a theoretical model of vulnerability that comprises three reciprocally influencing domains: social attitudes and expectations; opportunities and experiences; and skill deficits associated with intellectual disability. We propose that societal views which have traditionally devalued and stigmatised those with intellectual disability limit their opportunities for experiencing social and emotional connectedness with others. Individual skill deficits in areas such as communication, self-regulation and social understanding, as well as functional difficulties associated with intellectual disability, also potentially influence the opportunities and experiences of people with intellectual disability, both directly and via multiple layers of the social context. In turn, limited opportunities will entrench particular skill deficits and reinforce negative attitudes towards intellectual disability. Future research about loneliness and intellectual disability needs to address the difficulties of measuring emotional isolation in this population, as well as the possibility that people with intellectual disability may understand, experience and interpret loneliness somewhat differently from others. The model proposed in this paper provides a starting point for developing a more sophisticated understanding of the experience of loneliness for individuals with intellectual disability.

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In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.

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While formal definitions and security proofs are well established in some fields like cryptography and steganography, they are not as evident in digital watermarking research. A systematic development of watermarking schemes is desirable, but at present their development is usually informal, ad hoc, and omits the complete realization of application scenarios. This practice not only hinders the choice and use of a suitable scheme for a watermarking application, but also leads to debate about the state-of-the-art for different watermarking applications. With a view to the systematic development of watermarking schemes, we present a formal generic model for digital image watermarking. Considering possible inputs, outputs, and component functions, the initial construction of a basic watermarking model is developed further to incorporate the use of keys. On the basis of our proposed model, fundamental watermarking properties are defined and their importance exemplified for different image applications. We also define a set of possible attacks using our model showing different winning scenarios depending on the adversary capabilities. It is envisaged that with a proper consideration of watermarking properties and adversary actions in different image applications, use of the proposed model would allow a unified treatment of all practically meaningful variants of watermarking schemes.

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The aim of this paper is to aid researchers in undertaking action research within industry with a particular focus on the study of design-led innovation. This paper presents the research design of a case study shaped to solve real world problems concerning a major Australian Airport Corporation by bridging the chasm between academia and industry. The researcher’s role is one of design-innovation catalyst, facilitating the integration of design as a new strategic capability and innovation approach within an organisation’s fabric. A discussion of the researcher experience within industry will provide evidence on the challenges facing such a research role, with strategies for overcoming these barriers presented. Based on the authors’ experience as a researcher within industry and reflection within practice, a project progression model for action research is presented to enable the improved management of industry based research.

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A need to respond to changing legislative requirements, rising expectations from customers and shortages of suitably experienced staff are forcing non-profit organisations in the aged care sector to change. As new customer segments emerge and the existing aged care offering becomes less relevant, organisations must rethink the value they present to market, and adopt innovative strategies and approaches to care delivery in order to have a sustainable future. This paper presents a framework for unpacking a customer journey and experience, developed during a longitudinal study of a non-profit organisation redefining their core purpose and attempting to design a customer-centric business model.

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Curriculum scholars and teachers working for social justice and equity have been caught up in acrimonious and polarizing debates over content, ideology and disciplinary knowledge. At the forefront in cutting through these debates and addressing the practical questions involved, this book is distinctive in looking to the technical form of the curriculum rather than its content for solutions. The editors and contributors, all leading international scholars, advance a unified, principled approach to the design of syllabus documents that aims for high quality/high equity educational outcomes and enhances teacher professionalism.

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Braking is a crucial driving task with a direct relationship with crash risk, as both excess and inadequate braking can lead to collisions. The objective of this study was to compare the braking profile of young drivers distracted by mobile phone conversations to non-distracted braking. In particular, the braking behaviour of drivers in response to a pedestrian entering a zebra crossing was examined using the CARRS-Q Advanced Driving Simulator. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free, and handheld. In addition to driving the simulator, each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The drivers were 18–26 years old and split evenly by gender. A linear mixed model analysis of braking profiles along the roadway before the pedestrian crossing revealed comparatively increased decelerations among distracted drivers, particularly during the initial 20 kph of deceleration. Drivers’ initial 20 kph deceleration time was modelled using a parametric accelerated failure time (AFT) hazard-based duration model with a Weibull distribution with clustered heterogeneity to account for the repeated measures experiment design. Factors found to significantly influence the braking task included vehicle dynamics variables like initial speed and maximum deceleration, phone condition, and driver-specific variables such as licence type, crash involvement history, and self-reported experience of using a mobile phone whilst driving. Distracted drivers on average appear to reduce the speed of their vehicle faster and more abruptly than non-distracted drivers, exhibiting excess braking comparatively and revealing perhaps risk compensation. The braking appears to be more aggressive for distracted drivers with provisional licenses compared to drivers with open licenses. Abrupt or excessive braking by distracted drivers might pose significant safety concerns to following vehicles in a traffic stream.

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In today’s world of information-driven society, many studies are exploring usefulness and ease of use of the technology. The research into personalizing next-generation user interface is also ever increasing. A better understanding of factors that influence users’ perception of web search engine performance would contribute in achieving this. This study measures and examines how users’ perceived level of prior knowledge and experience influence their perceived level of satisfaction of using the web search engines, and how their perceived level of satisfaction affects their perceived intention to reuse the system. 50 participants from an Australian university participated in the current study, where they performed three search tasks and completed survey questionnaires. A research model was constructed to test the proposed hypotheses. Correlation and regression analyses results indicated a significant correlation between (1) users’ prior level of experience and their perceived level of satisfaction in using the web search engines, and (2) their perceived level of satisfaction in using the systems and their perceived intention to reuse the systems. A theoretical model is proposed to illustrate the causal relationships. The implications and limitations of the study are also discussed.

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This research investigated the ways academic libraries are using social media and adopting participatory principles in their programs and services. Using the Grounded Theory method the research developed an empirically derived model for participatory libraries. The research revealed three core categories representing the participatory library: community, empowerment, and experience. The research provides library professionals, researchers and the library community, with a fresh perspective and holistic picture of the contemporary library. The findings can be used to guide the development of participatory libraries in Australia and internationally.

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Rating systems are used by many websites, which allow customers to rate available items according to their own experience. Subsequently, reputation models are used to aggregate available ratings in order to generate reputation scores for items. A problem with current reputation models is that they provide solutions to enhance accuracy of sparse datasets not thinking of their models performance over dense datasets. In this paper, we propose a novel reputation model to generate more accurate reputation scores for items using any dataset; whether it is dense or sparse. Our proposed model is described as a weighted average method, where the weights are generated using the normal distribution. Experiments show promising results for the proposed model over state-of-the-art ones on sparse and dense datasets.

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In a tag-based recommender system, the multi-dimensional <user, item, tag> correlation should be modeled effectively for finding quality recommendations. Recently, few researchers have used tensor models in recommendation to represent and analyze latent relationships inherent in multi-dimensions data. A common approach is to build the tensor model, decompose it and, then, directly use the reconstructed tensor to generate the recommendation based on the maximum values of tensor elements. In order to improve the accuracy and scalability, we propose an implementation of the -mode block-striped (matrix) product for scalable tensor reconstruction and probabilistically ranking the candidate items generated from the reconstructed tensor. With testing on real-world datasets, we demonstrate that the proposed method outperforms the benchmarking methods in terms of recommendation accuracy and scalability.

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This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment <user, item, tag>, should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

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This paper addresses the regulatory issues arising in developing a new regulatory model for the New South Wales Coal Industry. As such, it identifies the relevant literature on this subject, the options available for reform, and the experience of Australian and key international bodies responsible for the development of regulatory standards in this area. In particular it: Identifies the main shortcomings in the existing regulatory approach; Identifies the potential roles/main strengths and weaknesses of different types of standards (eg specification, performance, process and systems-based rules) and potential “best practice’ combinations of standards; Examines the appropriateness of the current regulatory regime whereby the general OHS legislation (including the general duty provisions) applies to mining in addition to the large body of regulation which is specific to mining; Identifies the importance of, and possible means of addressing, issues of worker participation within the coal mining industry; Draws on the literature on what motivates companies and individuals for the purpose of recommending key provisions for inclusion in new legislation to provide appropriate personal and organisational incentives; Draws on the literature on major hazards facilities to suggest the appropriate roles for OHS management systems and safety reports or comparable approaches (eg mine safety management plans); Draws on the United Kingdom (UK) and United States of America (USA) experience of coal mine safety and its regulation for comparative purposes, and for insights as to what sort of regulation most effectively reduces work related injury and disease in coal mining; Examines the relevant roles of International Labour Organisation (ILO) Conventions; Examines the extent to which different regulatory regimes would be appropriate to open cut and underground coal mining; and Examines options for reform. This paper is focussed specifically on the issues identified above.

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Law schools in Australia and the United Kingdom are increasingly adopting clinical legal education (CLE) as an important part of their curriculum. Models of CLE are emerging in those jurisdictions which draw on local experience and the strong tradition of CLE and community lawyering in the United States. The purpose of this article is to examine the pedagogy that underlies CLE and to consider how it can be applied to newly emerging models of CLE. In particular, it will evaluate a community project legal clinic in which students work on social justice projects in partnership with a range of community organisations, not limited to legal centres, with a view to determining whether pedagogical goals are being met in the way that the course is being delivered. This article argues that community project legal clinics can result in positive student learning outcomes in relation to the development of a pro bono ethos and commitment to social justice, lawyering skills including client communication, and the development of a positive professional legal identity. Part II of the article provides a brief overview of the history of CLE in Australia, the United Kingdom and the United States, noting the trend towards the development of community lawyering clinics. Part III examines the benefits of community lawyering clinics focusing on the benefits for student learning and the service-learning pedagogy applied in community lawyering clinics in the United States. Finally, part IV looks at a case study of a new community project clinic in Australia that draws upon the service-learning pedagogy of community lawyering CLE. In the community project clinic, students engage in service-learning through undertaking projects with not-for-profit community organisations. Community partners identify relevant issues and needs, and the students work in interdisciplinary teams to address these. Law students working in these teams are often exposed to a broader social problem or issue than they would experience in a traditional ‘in-person’ legal clinic. Initial evaluation suggests that this model for community clinics in law schools assists students to develop lawyering skills and a positive legal identity including awareness of and support for pro bono legal work and a sense of belonging in the legal profession.