838 resultados para Information Management Model


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In this paper I will explore some experience-based perspectives on information literacy research and practice. The research based understanding of what information literacy looks like to those experiencing it, is very different from the standard interpretations of information literacy as involving largely text based information searching, interpretation, evaluation and use. It also involves particular understandings of the interrelation between information and learning experiences. In following this thread of the history of information literacy I will reflect on aspects of the past, present and future of information literacy research. In each of these areas I explore experiential, especially phenomenographic approaches to information literacy and information literacy education, to reveal the unfolding understanding of people’s experience of information literacy stemming from this orientation. In addressing the past I will look in particular at the contribution of the seven faces of information literacy and some lessons learned from attending to variation in experience. I will explore important directions and insights that this history may help us to retain; including the value of understanding peoples’ information literacy experience. In addressing the present, I will introduce more recent work that adopts the key ideas of informed learning by attending to both information and learning experiences in specific contexts. I will look at some contemporary directions and key issues, including the reinvention of the phenomenographic, or relational approach to information literacy as informed learning or using information to learn. I will also provide some examples of the contribution of experiential approaches to information literacy research and practice. The evolution and development of the phenomenographic approach to information literacy, and the growing attention to a dual focus on information and learning experiences in this approach will be highlighted. Finally, in addressing the future I will return to advocacy, the recognition and pursuit of the transforming and empowering heart of information literacy; and suggest that for information literacy research, including the experiential, a turn towards the emancipatory has much to offer.

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This paper discusses methodological developments in phenomenography that make it apropos for the study of teaching and learning to use information in educational environments. Phenomenography is typically used to analyze interview data to determine different ways of experiencing a phenomenon. There is an established tradition of phenomenographic research in the study of information literacy (ex: Bruce, 1997; 2008; Lupton, 2008; Webber, Boon, & Johnston, 2005). Drawing from the large body of evidence complied in two decades of research, phenomenographers developed variation theory, which explains what a learner can feasibly learn from a classroom lesson based on how the phenomenon being studied is presented (Marton, Runesson, & Tsui, 2004). Variation theory’s ability to establish the critical conditions necessary for learning to occur has resulted in the use of phenomenographic methods to study classroom interactions by collecting and analyzing naturalistic data through observation, as well as interviews concerning teachers’ intentions and students’ different experiences of classroom lessons. Describing the methodological developments of phenomenography in relation to understanding the classroom experience, this paper discusses the potential benefits and challenges of utilizing such methods to research the experiences of teaching and learning to use information in discipline-focused classrooms. The application of phenomenographic methodology for this purpose is exemplified with an ongoing study that explores how students learned to use information in an undergraduate language and gender course (Maybee, Bruce, Lupton, & Rebmann, in press). This paper suggests that by providing a nuanced understanding of what is intended for students to learn about using information, and relating that to what transpires in the classroom and how students experience these lessons, phenomenography and variation theory offer a viable framework for further understanding and improving how students are taught, and learn to use information.

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Interest in the concept of information literacy in different contexts is a topic that has steadily gained increased attention in information literacy discourse and research efforts over recent years. In particular the emergence of the term ‘health information literacy’ attests to this interest and has elevated awareness about the importance and relevance of information literacy in a health context. This paper reports on research that has taken a relational perspective to explore how people experience health information literacy. Initially established by Bruce (1997) the relational perspective draws from an experiential framework that emphasizes the relationship between users and information when learning in different contexts. This approach seeks outcomes that are deeply embedded in users’ informational life worlds and complements experiential phenomenological perspectives that have been used in health research. In keeping with the relational approach this research interprets health information literacy as being the different ways in which people experience using information to learn about health. Using interpretive phenomenography, this research explored variation in the lived experience of how people use information to learn about their health, and variation in what is constituted as information when learning about their health. Participants included 23 males and females aged between 45 and 64 years. All participants were residents from the Greater Brisbane area of Queensland, Australia. The research used semi-structured interviews for data collection. The types of questions posed during interviews included ‘Can you describe a time when you used information to learn about your health?’ and ‘What kinds of information have you used to learn about your health?’. This paper will focus on presenting one element of research findings that concerns the differences in ‘what’ participants experienced as information. Analysis of interview data identified significant variation in the experienced nature of information, specifically the different qualities or elements that comprised the ‘object’ of information, or in other words, what was perceived as ‘informing’. Illustrations of this variation include information experienced as traditional information sources, facts and experiences, something exhibiting particular qualities, physical or psychological changes, other people and role models. These findings provide new insights into what people may experience as information, and build upon existing literature regarding information as a theoretical construct. In addition the potential implications of these findings with respect to the design and delivery of health information literacy education will also be discussed. These research findings contribute to the emergence of information literacy investigations in everyday life and community. Although such settings have long been identified as a significant gap for exploration, research to date in this field has predominantly focused on educational and workplace environments. In this way the knowledge gained from this research has further revealed the contextual nature of information literacy, as well as its complexity as a phenomenon and focus of study.

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Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, which has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering is rarely known. Patterns are always thought to be more representative than single terms for representing documents. In this paper, a novel information filtering model, Pattern-based Topic Model(PBTM) , is proposed to represent the text documents not only using the topic distributions at general level but also using semantic pattern representations at detailed specific level, both of which contribute to the accurate document representation and document relevance ranking. Extensive experiments are conducted to evaluate the effectiveness of PBTM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model achieves outstanding performance.

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Many mature term-based or pattern-based approaches have been used in the field of information filtering to generate users’ information needs from a collection of documents. A fundamental assumption for these approaches is that the documents in the collection are all about one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, and this has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering has not been so well explored. Patterns are always thought to be more discriminative than single terms for describing documents. However, the enormous amount of discovered patterns hinder them from being effectively and efficiently used in real applications, therefore, selection of the most discriminative and representative patterns from the huge amount of discovered patterns becomes crucial. To deal with the above mentioned limitations and problems, in this paper, a novel information filtering model, Maximum matched Pattern-based Topic Model (MPBTM), is proposed. The main distinctive features of the proposed model include: (1) user information needs are generated in terms of multiple topics; (2) each topic is represented by patterns; (3) patterns are generated from topic models and are organized in terms of their statistical and taxonomic features, and; (4) the most discriminative and representative patterns, called Maximum Matched Patterns, are proposed to estimate the document relevance to the user’s information needs in order to filter out irrelevant documents. Extensive experiments are conducted to evaluate the effectiveness of the proposed model by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models

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The concept of cloud computing services is appealing to the small and medium enterprises (SMEs), with the opportunity to acquire modern information technology resources as a utility and avoid costly capital investments in technology resources. However, the adoption of the cloud computing services presents significant challenges to the SMEs. The SMEs need to determine a path to adopting the cloud computing services that would ensure their sustainable presence in the cloud computing environment. Information about approaches to adopting the cloud computing services by the SMEs is fragmented. Through an interpretive design, we suggest that the SMEs need to have a strategic and incremental intent, understand their organizational structure, understand the external factors, consider the human resource capacity, and understand the value expectations from the cloud computing services to forge a successful path to adopting the cloud computing services. These factors would contribute to a model of cloud services for SMEs.

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Although integrated marketing communication (IMC) has progressed towards midrange maturity level, its full-scale adoption has been impeded by a lack of consensus on its defining constructs. The purpose of this study is to move from abstraction to define the construct of strategic integration (SI) and develop this into a management tool, thus making an important contribution to both the theory and practice of IMC. Drawing from both IMC and strategic management literature, the construct of SI is operationalised into a number of key factors and a well-cited management model, Fuchs’ ‘integration valuator’ is explored as the starting point of a measurement tool for IMC. To do this, a Delphi study invites the scrutiny of an expert panel of world-leading IMC researchers and practitioners. The panel validated the model construction process,redefined overarching constructs and key factors with a high degree of consensus, supported a process measure, suggested a weighted evaluation measure and recognised the importance of developing such a measure. They delivered clear and consistent imperatives guiding model development. The result is a measure of SI that evaluates organisational proficiency and diagnoses the integration of IMC campaigns. It also advances theory by providing a better understanding of the construct of SI.

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The Central Queensland Mine Rehabilitation Group (CQMRG) has hosted mine site rehabilitation inspections combined with technical workshops for more than 20 years. It was recognised at CQMRG's anniversary meeting in April 2013 that the vast body of knowledge held by rehabilitation and closure planning practitioners was being lost as senior rehabilitation experts retire from the industry. It was noted that even more knowledge could be readily lost unless a knowledge management platform was developed to capture, store and enable retrieval of this information. This loss of knowledge results in a significant cost to industry. This project was therefore undertaken to review tools which have the capability to gather the less formal knowledge as well as to make links to existing resources and bibliographic material. This scoping study evaluated eight alternative knowledge management systems to provide guidance on the best method of providing the industry with an up-to-date, good practice, knowledge management system for rehabilitation and closure practices, with capability for information sharing via a portal and discussion forum. This project provides guidance for a larger project which will implement the knowledge management system to meet the requirements of the CQMRG and be transferrable to other regions if applicable. It will also provide the opportunity to identify missing links between existing tools and their application. That is, users may not be aware of how these existing tools can be used to assist with mine rehabilitation planning and implementation and the development of a new platform will help to create those linkages. The outcomes of this project are directed toward providing access to a live repository of rehabilitation practice information which is Central Queensland coal mine-specific, namely: highlighting best practice activities, results of trials and innovative practices; updated legislative requirements; links to practices elsewhere; and informal anecdotal information relevant to particular sites which may be of assistance in the development of rehabilitation of new areas. Solutions to the rehabilitation of challenging spoils/soils will also be provided. The project will also develop a process which can be applied more broadly within the mining sector to other regions and other commodities. Providing a platform for uploading information and holding discussion forums which can be managed by a regional practitioner network enables the new system to be kept alive, driven by users and information needs as they evolve over time. Similar internet-based platforms exist and are managed successfully. The preferred knowledge management system will capture the less formal and more difficult to access knowledge from rehabilitation and mine closure practitioners and stakeholders through the CQMRG and other contributors. It will also provide direct links, and greater accessibility, to more formal sources of knowledge with anticipated cost savings to the industry and improved rehabilitation practices with successful transitioning to closure and post-mining land use.

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Health Information Exchange (HIE) is an interesting phenomenon. It is a patient centric health and/or medical information management scenario enhanced by integration of Information and Communication Technologies (ICT). While health information systems are repositioning complex system directives, in the wake of the ‘big data’ paradigm, extracting quality information is challenging. It is anticipated that in this talk, ICT enabled healthcare scenarios with big data analytics will be shared. In addition, research and development regarding big data analytics, such as current trends of using these technologies for health care services and critical research challenges when extracting quality of information to improve quality of life will be discussed.

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Knowledge management (KM) strategy is the planned or actual coordination of a firm's major goals and learning in time; this coordination continually co-aligns the firm's knowledge-based resources with the environment. Based on the organic perspective of strategy, a KM performance evaluation approach should be able to 1) review the knowledge governance mechanisms and learning routines that underpin the KM strategy, as well as the performance outcomes driven by the strategy, and 2) predict the evolution of performance drivers and outcomes into the future to facilitate strategic planning. This study combined a survey study and a system dynamics (SD) simulation to demonstrate the transformation from a mechanistic to an organic perspective on KM strategy and performance evaluation. The survey study was conducted based on a sample of 143 construction contractors and used structural equation modeling (SEM) techniques to develop a KM performance index for reviewing the key elements that underpin KM strategy. The SD simulation predicted the development of KM strategy configurations and the evolution of KM performance over time. The organic KM performance evaluation approach demonstrated by this study has significant potential to improve the alignment of KM strategy within an increasingly dynamic business environment.

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While the economic and environmental benefits of fisheries management are well accepted, the costs of effective management in low value fisheries, including the research necessary to underpin such management, may be considerable relative to the total economic benefits they may generate. Co-management is often seen as a panacea in low value fisheries. Increasing fisher participation increases legitimacy of management decision in the absence of detailed scientific input. However, where only a small number of operators exist, the potential benefits of co-management are negated by the high transaction cost to the individual fishers engaging in the management process. From an economic perspective, sole ownership has been identified as the management structure which can best achieve biological and economic sustainability. Moving low value fisheries with a small number of participants to a corporate-cooperative management model may come close to achieving these sole ownership benefits, with lower transaction costs. In this paper we look at the applicability of different management models with industry involvement to low value fisheries with a small number of participants. We provide an illustration as to how a fishery could be transitioned to a corporate-cooperative management model that captures the key benefits of sole management at a low cost and is consistent with societal objectives.

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Australia is a leading user of collaborative procurement methods, which are used to deliver large and complex infrastructure projects. Project alliances, Early Contractor Involvement (ECI), and partnering are typical examples of collaborative procurement models. In order to increase procurement effectiveness and value for money (VfM), clients have adopted various learning strategies for new contract development. However client learning strategies and behaviours have not been systematically analysed before. Therefore, the current paper undertakes a literature review addressing the research question “How can client learning capabilities be effectively understood?”. From the resource-based and dynamic capability perspectives, this paper proposes that the collaborative learning capability (CLC) of clients drives procurement model evolution. Learning routines underpinning CLC carry out exploratory, transformative and exploitative learning phases associated with collaborative project delivery. This learning improves operating routines, and ultimately performance. The conceptualization of CLC and the three sequential learning phases is used to analyse the evidence in the construction management literature. The main contribution of this study is the presentation of a theoretical foundation for future empirical studies to unveil effective learning strategies, which help clients to improve the performance of collaborative projects in the dynamic infrastructure market.

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Theories of individual attitudes toward IT include task technology fit (TTF), technology acceptance model (TAM), unified theory of acceptance and use of technology (UTAUT), cognitive fit, expectation disconfirmation, and computer self-efficacy. Examination of these theories reveals three main concerns. First, the theories mostly ‘‘black box’’ (or omit) the IT artifact. Second, appropriate mid-range theory is not developed to contribute to disciplinary progress and to serve the needs of our practitioner community. Third, theories are overlapping but incommensurable. We propose a theoretical framework that harmonizes these attitudinal theories and shows how they can be specialized to include relevant IS phenomenon.

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Objective: To illustrate a new method for simplifying patient recruitment for advanced prostate cancer clinical trials using natural language processing techniques. Background: The identification of eligible participants for clinical trials is a critical factor to increase patient recruitment rates and an important issue for discovery of new treatment interventions. The current practice of identifying eligible participants is highly constrained due to manual processing of disparate sources of unstructured patient data. Informatics-based approaches can simplify the complex task of evaluating patient’s eligibility for clinical trials. We show that an ontology-based approach can address the challenge of matching patients to suitable clinical trials. Methods: The free-text descriptions of clinical trial criteria as well as patient data were analysed. A set of common inclusion and exclusion criteria was identified through consultations with expert clinical trial coordinators. A research prototype was developed using Unstructured Information Management Architecture (UIMA) that identified SNOMED CT concepts in the patient data and clinical trial description. The SNOMED CT concepts model the standard clinical terminology that can be used to represent and evaluate patient’s inclusion/exclusion criteria for the clinical trial. Results: Our experimental research prototype describes a semi-automated method for filtering patient records using common clinical trial criteria. Our method simplified the patient recruitment process. The discussion with clinical trial coordinators showed that the efficiency in patient recruitment process measured in terms of information processing time could be improved by 25%. Conclusion: An UIMA-based approach can resolve complexities in patient recruitment for advanced prostate cancer clinical trials.

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This study seeks to understand the prevailing status of Nepalese media portrayal of natural disasters and develop a disaster management framework to improve the effectiveness and efficiency of news production through the continuum of prevention, preparedness, response and recovery (PPRR) phases of disaster management. The study is currently under progress. It is being undertaken in three phases. In phase-1, a qualitative content analysis is conducted. The news contents are categorized in frames as proposed in the 'Framing theory' and pre-defined frames. However, researcher has looked at the theories of the Press, linking to social responsibility theory as it is regarded as the major obligation of the media towards the society. Thereafter, the contents are categorized as per PPRR cycle. In Phase-2, based on the findings of content analysis, 12 in-depth interviews with journalists, disaster managers and community leaders are conducted. In phase-3, based on the findings of content analysis and in-depth interviews, a framework for effective media management of disaster are developed using thematic analysis. As the study is currently under progress hence, findings from the pilot study are elucidated. The response phase of disasters is most commonly reported in Nepal. There is relatively low coverage of preparedness and prevention. Furthermore, the responsibility frame in the news is most prevalent following human interest. Economic consequences and conflict frames are also used while reporting and vulnerability assessment has been used as an additional frame. The outcomes of this study are multifaceted: At the micro-level people will be benefited as it will enable a reduction in the loss of human lives and property through effective dissemination of information in news and other mode of media. They will be ‘well prepared for', 'able to prevent', 'respond to' and 'recover from' any natural disasters. At the meso level the media industry will be benefited and have their own 'disaster management model of news production' as an effective disaster reporting tool which will improve in media's editorial judgment and priority. At the macro-level it will assist government and other agencies to develop appropriate policies and strategies for better management of natural disasters.