515 resultados para training school


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Homophobic hatred: these words summarise online commentary made by people in support of a school that banned gay students from taking their same sex partners to a school formal. With the growing popularity of online news sites, it seems appropriate to critically examine how these sites are becoming a new arena in which people can express personal opinions about controversial topics. While commentators equally expressed two dominant viewpoints about the school ban (homophobic hatred and human rights), this paper focuses on homophobic hatred as a discursive position and how the comments work to confirm the legitimacy of the schools’ decision. Drawing on the work of Foucault and others, the paper examines how the comments constitute certain types of subjectivity drawing on dominant ideas about what it means to be homophobic. The analysis demonstrates the complex and competing skein of strategies that constitute queering school social spaces as a social problem.

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To explore potential barriers to and facilitators for implementing occupational road safety initiatives, in-depth interviews were conducted with personnel from four major Australian organizations. Twenty-four participants were involved in the interviews comprising 16 front line employees and eight managers. The interviews identified that employees perceived six organizational characteristics as potential barriers to implementing occupational road safety initiatives. These included: prioritisation of production over safety; complacency towards occupational road risks; insufficient resources; diversity; limited employee input in safety decisions; and a perception that road safety initiatives were an unnecessary burden. Of these organizational characteristics, prioritisation of production over safety and complacency were the most frequently cited barriers. In regards to facilitators, participants perceived three organizational characteristics as potential facilitators to implementing occupational road safety initiatives. These included: management commitment; the presence of existing systems that could support the implementation of initiatives; and supportive relationships. Of these organizational characteristics, management commitment was the most frequently cited facilitator.

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The aim of this work was to investigate ultrafine particles (< 0.1 μm) in primary school classrooms, in relation to the classrooms activities. The investigations were conducted in three classrooms during two measuring campaigns, which together encompassed a period of 60 days. Initial investigations showed that under the normal operating conditions of the school there were many occasions in all three classrooms where indoor particle concentrations increased significantly compared to outdoor levels. By far the highest increases in the classroom resulted from art activities (painting, gluing and drawing), at times reaching over 1.4 x 105 particle cm-3. The indoor particle concentrations exceeded outdoor concentrations by approximately one order of magnitude, with a count median diameter ranging from 20-50 nm. Significant increases also occurred during cleaning activities, when detergents were used. GC-MS analysis conducted on 4 samples randomly selected from about 30 different paints and glues, as well as the detergent used in the school, showed that d-limonene was one of the main organic compounds of the detergent, however, it was not detected in the samples of the paints and the glue. Controlled experiments showed that this monoterpene, emitted from the detergent, reacted with O3 (at outdoor ambient concentrations ranging from 0.06-0.08ppm) and formed secondary organic aerosols. Further investigations to identify other liquids which may be potential sources of the precursors of secondary organic aerosols, were outside the scope of this project, however, it is expected that the problem identified by this study could be more widely spread, since most primary schools use liquid materials for art classes, and all schools use detergents for cleaning. Further studies are therefore recommended to better understand this phenomenon and also to minimize school children exposure to ultrafine particles from these indoor sources.

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Annual reports are an important component of New Zealand schools’ public accountability. Through the annual report the governance body informs stakeholders about school aims, objectives, achievements, use of resources, and financial performance. We examine the perceived usefulness of the annual report in the discharge of public accountability. We find that 15% of the recipients (mainly parents/caregivers) do not read the annual report because they trust in the school to do the right thing or rely on others to monitor school activities. We find that the annual report is used for a variety of purposes including to determine if the school has conducted its activities effectively and achieved stated objectives and goals; to examine student achievements; to assess financial accountability and performance; and to make decisions about the school as a suitable environment for their child/children. We find that other forms of communication such as school newsletters, parent-teacher interviews, children and other parents are more important sources of information about the school than the annual report.

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Describes a cognitive-behavioral intervention for alcohol and cannabis abuse with schizophrenic patients. The intervention integrates substance abuse treatment with other aspects of psychosis management, including assessment, use of anti-psychotic medication, and training in coping skills.

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Surveyed 45 therapists who had participated in a family intervention for schizophrenia training program to examine the difficulties they had encountered, their recall of the intervention strategies, and the extent that they thought the approach had become integrated in their everyday work. Between 6 mo and 3 yrs after the family training, Ss reported the number of families they had systematically treated, and the difficulties they had encountered. Allowance of time to undertake the intervention, afterhours scheduling, and illness or holidays presented particular difficulties. Only 4% reported that their knowledge of behavioral techniques was a problem, but in a written test most therapists did not display minimum recall of the material of cognitive therapy, social skills training, or behavioral strategies. The study demonstrated significant problems in disseminating cognitive-behavioral approaches to multidisciplinary settings.

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In this paper, we propose an unsupervised segmentation approach, named "n-gram mutual information", or NGMI, which is used to segment Chinese documents into n-character words or phrases, using language statistics drawn from the Chinese Wikipedia corpus. The approach alleviates the tremendous effort that is required in preparing and maintaining the manually segmented Chinese text for training purposes, and manually maintaining ever expanding lexicons. Previously, mutual information was used to achieve automated segmentation into 2-character words. The NGMI approach extends the approach to handle longer n-character words. Experiments with heterogeneous documents from the Chinese Wikipedia collection show good results.

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The CDIO (Conceive-Design-Implement-Operate) Initiative has been globally recognised as an enabler for engineering education reform. With the CDIO process, the CDIO Standards and the CDIO Syllabus, many scholarly contributions have been made around cultural change, curriculum reform and learning environments. In the Australasian region, reform is gaining significant momentum within the engineering education community, the profession, and higher education institutions. This paper presents the CDIO Syllabus cast into the Australian context by mapping it to the Engineers Australia Graduate Attributes, the Washington Accord Graduate Attributes and the Queensland University of Technology Graduate Capabilities. Furthermore, in recognition that many secondary schools and technical training institutions offer introductory engineering technology subjects, this paper presents an extended self-rating framework suited for recognising developing levels of proficiency at a preparatory level. A demonstrator mapping tool has been created to demonstrate the application of this extended graduate attribute mapping framework as a precursor to an integrated curriculum information model.

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The CDIO Initiative has been globally recognised as an enabler for engineering education reform. With the CDIO process, the CDIO Standards and the CDIO Syllabus, many scholarly contributions have been made around cultural change, curriculum reform and learning environments. In the Australasian region, reform is gaining significant momentum within the engineering education community, the profession, and higher education institutions. This paper presents the CDIO Syllabus cast into the Australian context by mapping it to the Engineers Australia Graduate Attributes, the Washington Accord Graduate Attributes and the Queensland University of Technology Graduate Capabilities. Furthermore, in recognition that many secondary schools and technical training institutions offer introductory engineering technology subjects, this paper presents an extended self-rating framework suited for recognising developing levels of proficiency at a preparatory level. The framework is consistent with conventional application to undergraduate programs and professional practice, but adapted for the preparatory context. As with the original CDIO framework with proficiency levels, this extended framework is informed by Bloom’s Educational Objectives. A proficiency evaluation of Queensland Study Authority’s Engineering Technology senior syllabus is demonstrated indicating proficiency levels embedded within this secondary school subject within a preparatory scope. Through this extended CDIO framework, students and faculty have greater awareness and access to tools to promote (i) student engagement in their own graduate capability development, (ii) faculty engagement in course and program design, through greater transparency and utility of the continuum of graduate capability development with associate levels of proficiency, and the context in which they exist in terms of pre-tertiary engineering studies; and (iii) course maintenance and quality audit methodology for the purpose of continuous improvement processes and program accreditation.

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The problem of impostor dataset selection for GMM-based speaker verification is addressed through the recently proposed data-driven background dataset refinement technique. The SVM-based refinement technique selects from a candidate impostor dataset those examples that are most frequently selected as support vectors when training a set of SVMs on a development corpus. This study demonstrates the versatility of dataset refinement in the task of selecting suitable impostor datasets for use in GMM-based speaker verification. The use of refined Z- and T-norm datasets provided performance gains of 15% in EER in the NIST 2006 SRE over the use of heuristically selected datasets. The refined datasets were shown to generalise well to the unseen data of the NIST 2008 SRE.

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This paper explores models for enabling increased participation in experience based learning in legal professional practice. Legal placements as part of “for-credit” units offer students the opportunity to develop their professional skills in practice, reflect on their learning and job performance and take responsibility for their career development and planning. In short, work integrated learning (WIL) in law supports students in making the transition from university to practice. Despite its importance, WIL has traditionally taken place in practical legal training courses (after graduation) rather than during undergraduate law courses. Undergraduate WIL in Australian law schools has generally been limited to legal clinics which require intensive academic supervision, partnerships with community legal organisations and government funding. This paper will propose two models of WIL for undergraduate law which may overcome many of the challenges to engaging in WIL in law (which are consistent with those identified generally by the WIL Report). The first is a virtual law placement in which students use technology to complete a real world project in a virtual workplace under the guidance of a workplace supervisor. The second enables students to complete placements in private legal firms, government legal offices, or community legal centres under the supervision of a legal practitioner. The units complement each other by a) creating and enabling placement opportunities for students who may not otherwise have been able to participate in work placement by reason of family responsibilities, financial constraints, visa restrictions, distance etc; and b) enabling students to capitalise on existing work experience. This paper will report on the pilot offering of the units in 2008, the evaluation of the models and changes implemented in 2009. It will conclude that this multi-pronged approach can be successful in creating opportunities for, and overcoming barriers to participation in experiential learning in legal professional practice.

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Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.

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The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

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Interactive educational courseware has been adopted in diverse education sectors such as primary, secondary, tertiary education, vocational and professional training. In Malaysian educational context, the ministry of education has implemented Smart School Project that aims to increase high level of academic achievement in primary and secondary schools by using interactive educational courseware. However, many researchers have reported that many coursewares fail to accommodate the learner and teacher needs. In particular, the interface design is not appropriately designed in terms of quality of learning. This paper reviews educational courseware development process in terms of defining quality of interface design and suggests a conceptual model of interface design through the integration of design components and interactive learning experience into the development process. As a result, it defines the concept of interactive learning experience in a more practical approach in order to implement each stage of the development process in a seamless and integrated way.