3 resultados para free-choice learning

em Nottingham eTheses


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This commentary will use recent events in Cornwall to highlight the ongoing abuse of adults with learning disabilities in England. It will critically explore how two parallel policy agendas – namely, the promotion of choice and independence for adults with learning disabilities and the development of adult protection policies – have failed to connect, thus allowing abuse to continue to flourish. It will be argued that the abuse of people with learning disabilities can only be minimised by policies which reflect an understanding that choice and independence must necessarily be mediated by effective adult protection measures. Such protection needs to include not only an appropriate regulatory framework, access to justice and well-qualified staff, but also a more critical and reflective approach to the current orthodoxy which promotes choice and independence as the only acceptable goals for any person with a learning disability.

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For the discipline of occupational health psychology (OHP) to continue to evolve and to serve workers effectively it is imperative that education and training provision is available that enables students to acquire knowledge and skills, free of geographical and temporal constraints. This chapter begins with a brief introduction to the historical development of education and training in OHP in Europe. The review culminates with the assertion that higher education institutions are now required to act innovatively in regard to the expansion of provision. One such initiative involves the introduction of e-learning. A case study concerning the implementation of a Masters degree in OHP by e-learning is presented. On the outcomes of the case study, recommendations are offered for the design and implementation of such courses. The chapter concludes by raising some further questions that need to be addressed for education and training provision in OHP to continue to expand.

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Background: Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results: We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.