919 resultados para Person-centred information


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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

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Background: High levels of distress and need for self-care information by patients commencing chemotherapy suggest that current prechemotherapy education is suboptimal. We conducted a randomised, controlled trial of a prechemotherapy education intervention (ChemoEd) to assess impact on patient distress, treatment-related concerns, and the prevalence and severity of and bother caused by six chemotherapy side-effects. Patients and methods: One hundred and ninety-two breast, gastrointestinal, and haematologic cancer patients were recruited before the trial closing prematurely (original target 352). ChemoEd patients received a DVD, question-prompt list, self-care information, an education consultation ≥24 h before first treatment (intervention 1), telephone follow-up 48 h after first treatment (intervention 2), and a face-to-face review immediately before second treatment (intervention 3). Patient outcomes were measured at baseline (T1: pre-education) and immediately preceding treatment cycles 1 (T2) and 3 (T3). Results: ChemoEd did not significantly reduce patient distress. However, a significant decrease in sensory/psychological (P = 0.027) and procedural (P = 0.03) concerns, as well as prevalence and severity of and bother due to vomiting (all P = 0.001), were observed at T3. In addition, subgroup analysis of patients with elevated distress at T1 indicated a significant decrease (P = 0.035) at T2 but not at T3 (P = 0.055) in ChemoEd patients. Conclusions: ChemoEd holds promise to improve patient treatment-related concerns and some physical/psychological outcomes; however, further research is required on more diverse patient populations to ensure generalisability.

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Since the architectural design studio learning environment was first established in the early 19th century at the École des Beaux-Arts in Paris, there has been a complete transformation in how the discipline of architecture is practiced and how students of architecture acquire information. Digital technologies allow students to access information instantly and learning is no longer confined to the rigid boundaries of a physical campus environment. In many schools of architecture in Australia, the physical design studio learning environments however, remain largely unchanged. Many learning environments could be mistaken for those last refurbished 30 years ago, being devoid of any significant technological intervention. While some teaching staff are eagerly embracing new digital technologies and attempting to modify their pedagogical approaches, the physical design studio learning environment is resistant to such efforts. In a study aimed at better understanding how staff and students adapt to new blended learning environments, a group of 165 second year architecture students at a large school of architecture in Australia were separated into two different design studio learning environments. 70% of students were allocated to a traditional design studio setting and 30% to a new, high technology embedded, prototype digital learning laboratory. The digital learning laboratory was purpose designed for the case-study users, adapted Student-Centred Active Learning Environment for Undergraduate Programs [SCALE-UP] principles, and built as part of a larger university research project. The architecture students attended the same lectures, followed the same studio curriculum and completed the same pieces of assessment; the only major differences were the teaching staff and physical environment within which the studios were conducted. At the end of the semester, all staff and students were asked to complete a questionnaire about their experiences and preferences within the two respective learning environments. The questionnaire response rate represented the opinions of 100% of the 10 teaching staff and over 70% of the students. Using a qualitative grounded theory approach, data were coded, extrapolated and compared, to reveal emerging key themes. The key themes formed the basis for in-depth interviews and focus groups of teaching staff and students, allowing the researchers to understand the data in more detail. The results of the data verified what had become increasingly evident during the course of the semester: an underlying negative resistance to the new digital studio learning environment, by both staff and students. Many participants openly exhibited a yearning for a return to the traditional design studio learning environments, particularly when the new technology caused frustration, by being unreliable or failing altogether. This paper reports on the study, discusses the negative resistance and explores the major contributors to resistance. The researchers are not aware of any similar previous studies across these particular settings and believe that it offers a necessary and important contribution to emergent research about adaptation to new digital learning environments.

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This paper presents a graph-based method to weight medical concepts in documents for the purposes of information retrieval. Medical concepts are extracted from free-text documents using a state-of-the-art technique that maps n-grams to concepts from the SNOMED CT medical ontology. In our graph-based concept representation, concepts are vertices in a graph built from a document, edges represent associations between concepts. This representation naturally captures dependencies between concepts, an important requirement for interpreting medical text, and a feature lacking in bag-of-words representations. We apply existing graph-based term weighting methods to weight medical concepts. Using concepts rather than terms addresses vocabulary mismatch as well as encapsulates terms belonging to a single medical entity into a single concept. In addition, we further extend previous graph-based approaches by injecting domain knowledge that estimates the importance of a concept within the global medical domain. Retrieval experiments on the TREC Medical Records collection show our method outperforms both term and concept baselines. More generally, this work provides a means of integrating background knowledge contained in medical ontologies into data-driven information retrieval approaches.

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Retrieving information from Twitter is always challenging due to its large volume, inconsistent writing and noise. Most existing information retrieval (IR) and text mining methods focus on term-based approach, but suffers from the problems of terms variation such as polysemy and synonymy. This problem deteriorates when such methods are applied on Twitter due to the length limit. Over the years, people have held the hypothesis that pattern-based methods should perform better than term-based methods as it provides more context, but limited studies have been conducted to support such hypothesis especially in Twitter. This paper presents an innovative framework to address the issue of performing IR in microblog. The proposed framework discover patterns in tweets as higher level feature to assign weight for low-level features (i.e. terms) based on their distributions in higher level features. We present the experiment results based on TREC11 microblog dataset and shows that our proposed approach significantly outperforms term-based methods Okapi BM25, TF-IDF and pattern based methods, using precision, recall and F measures.

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New technologies and the pace of change in modern society mean changes for classroom teaching and learning. Information and communication technologies (ICTs) feature in everyday life and provide ample opportunities for enhancing classroom programs. This article outlines how ICTs complement curriculum implementation in one year two classroom. It suggests practical strategies demonstrating how teachers can make ICTs work for them and progressively teach children how to make ICTs work for them.

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The determination of performance standards and assessment practices in regard to student work placements is an essential and important task. Inappropriate, inadequate, or excessively complex assessment tasks can influence levels of student engagement and the quality of learning outcomes. Critical to determining appropriate standards and assessment tasks is an understanding and knowledge of key elements of the learning environment and the extent to which opportunities are provided for students to engage in critical reflection and judgement of their own performance in the contexts of the work environment. This paper focuses on the development of essential skills and knowledge (capabilities) that provide evidence of learning in work placements by describing an approach taken in the science and technology disciplines. Assessment matrices are presented to illustrate a method of assessment for use within the context of the learning environment centred on work placements in science and technology. This study contributes to the debate on the meaning of professional capability, performance standards and assessment practices in work placement programs by providing evidence of an approach that can be adapted by other programs to achieve similar benefits. The approach may also be valuable to other learning contexts where capability and performance are being judged in situations that are outside a controlled teaching and learning environment i.e. in other life-wide learning contexts.

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Entity-oriented search has become an essential component of modern search engines. It focuses on retrieving a list of entities or information about the specific entities instead of documents. In this paper, we study the problem of finding entity related information, referred to as attribute-value pairs, that play a significant role in searching target entities. We propose a novel decomposition framework combining reduced relations and the discriminative model, Conditional Random Field (CRF), for automatically finding entity-related attribute-value pairs from free text documents. This decomposition framework allows us to locate potential text fragments and identify the hidden semantics, in the form of attribute-value pairs for user queries. Empirical analysis shows that the decomposition framework outperforms pattern-based approaches due to its capability of effective integration of syntactic and semantic features.

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This article focuses on problem solving activities in a first grade classroom in a typical small community and school in Indiana. But, the teacher and the activities in this class were not at all typical of what goes on in most comparable classrooms; and, the issues that will be addressed are relevant and important for students from kindergarten through college. Can children really solve problems that involve concepts (or skills) that they have not yet been taught? Can children really create important mathematical concepts on their own – without a lot of guidance from teachers? What is the relationship between problem solving abilities and the mastery of skills that are widely regarded as being “prerequisites” to such tasks?Can primary school children (whose toolkits of skills are limited) engage productively in authentic simulations of “real life” problem solving situations? Can three-person teams of primary school children really work together collaboratively, and remain intensely engaged, on problem solving activities that require more than an hour to complete? Are the kinds of learning and problem solving experiences that are recommended (for example) in the USA’s Common Core State Curriculum Standards really representative of the kind that even young children encounter beyond school in the 21st century? … This article offers an existence proof showing why our answers to these questions are: Yes. Yes. Yes. Yes. Yes. Yes. And: No. … Even though the evidence we present is only intended to demonstrate what’s possible, not what’s likely to occur under any circumstances, there is no reason to expect that the things that our children accomplished could not be accomplished by average ability children in other schools and classrooms.

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Phenomenography is a research approach devised to allow the investigation of varying ways in which people experience aspects of their world. Whilst growing attention is being paid to interpretative research in LIS, it is not always clear how the outcomes of such research can be used in practice. This article explores the potential contribution of phenomenography in advancing the application of phenomenological and hermeneutic frameworks to LIS theory, research and practice. In phenomenography we find a research toll which in revealing variation, uncovers everyday understandings of phenomena and provides outcomes which are readily applicable to professional practice. THe outcomes may be used in human computer interface design, enhancement, implementation and training, in the design and evaluation of services, and in education and training for both end users and information professionals. A proposed research territory for phenomenography in LIS includes investigating qualitative variation in the experienced meaning of: 1) information and its role in society 2) LIS concepts and principles 3) LIS processes and; 4) LIS elements.

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This item provides supplementary materials for the paper mentioned in the title, specifically a range of organisms used in the study. The full abstract for the main paper is as follows: Next Generation Sequencing (NGS) technologies have revolutionised molecular biology, allowing clinical sequencing to become a matter of routine. NGS data sets consist of short sequence reads obtained from the machine, given context and meaning through downstream assembly and annotation. For these techniques to operate successfully, the collected reads must be consistent with the assumed species or species group, and not corrupted in some way. The common bacterium Staphylococcus aureus may cause severe and life-threatening infections in humans,with some strains exhibiting antibiotic resistance. In this paper, we apply an SVM classifier to the important problem of distinguishing S. aureus sequencing projects from alternative pathogens, including closely related Staphylococci. Using a sequence k-mer representation, we achieve precision and recall above 95%, implicating features with important functional associations.

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The Therapeutic Advice and Information Service was funded by the National Prescribing Service to provide a national drug information service for health professionals working in the community. For ten years the service achieved high levels of client satisfaction, and reached its contracted target of 6000 enquiries about medicines per year, however the service ceased on 30 June 2010.

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A building information model (BIM) provides a rich representation of a building's design. However, there are many challenges in getting construction-specific information from a BIM, limiting the usability of BIM for construction and other downstream processes. This paper describes a novel approach that utilizes ontology-based feature modeling, automatic feature extraction based on ifcXML, and query processing to extract information relevant to construction practitioners from a given BIM. The feature ontology generically represents construction-specific information that is useful for a broad range of construction management functions. The software prototype uses the ontology to transform the designer-focused BIM into a construction-specific feature-based model (FBM). The formal query methods operate on the FBM to further help construction users to quickly extract the necessary information from a BIM. Our tests demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

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The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

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Crowdsourcing has become a popular approach for capitalizing on the potential of large and open crowds of people external to the organization. While crowdsourcing as a phenomenon is studied in a variety of fields, research mostly focuses on isolated aspects and little is known about the integrated design of crowdsourcing efforts. We introduce a socio-technical systems perspective on crowdsourcing, which provides a deeper understanding of the components and relationships in crowdsourcing systems. By considering the function of crowdsourcing systems within their organizational context, we develop a typology of four distinct system archetypes. We analyze the characteristics of each type and derive a number of design requirements for the respective system components. The paper lays a foundation for IS-based crowdsourcing research, channels related academic work, and helps guiding the study and design of crowdsourcing information systems.