18 resultados para free-choice learning


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This paper proposes a semantic analysis of the French free-choice indefinite 'n’importe qui'. The semantics of the indefinite is organised as a ternary structure. The (1) abstract meaning underlies all uses of the item and acts as a principle of creative interpretation generation and comprehension. This principle is actualised via (2) discrete contextual features through to (3) contextual interpretations. Thus, the “existential” reading of 'n’importe qui' is derived by a veridical reading of the arbitrary selection of a qualitatively-marked occurrence from the set of human animates. The derivation of contextual readings from the enrichment by contextual cues of an underspecified meaning has a claim to an explanatory model of the semantics of grammatical polysemous items, and is certainly relevant to model-theoretic approaches in as much as formal semantic notions are intricately linked to the contextual interpretation of items. It is not 'n’importe qui' itself, but its contextual interpretations which may be weak or strong, and an homonymous treatment is not possible given the continuity of the quality and free-choice dimensions from one observed reading of n’importe qui to the next.

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This paper looks at the notion of scale through the negative polarity and free-choice interpretations of arbitrary-selection expressions such as any. These interpretations rest on a scalar model, which explains why they often get associated with the same item cross-linguistically. A scalar model does not seem to emerge readily in the problematic imperatives of the type Pick any card, where the arbitrary selection item differs from its other uses by its existential value and absence of qualitative dimensions. These differences come from a choice over non-distinguishable entities left to the interlocutor. Yet, since this choice is exerted against the whole set of contextual entities, a scalar model seems to stand, for this and other problematic imperative uses.

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While commitment is an important antecedent to customer retention, a broad consensus has yet to emerge on the impacts of constituent dimensions of commitment on loyalty in service relationships. This study explores the impacts of affective and continuance commitment on attitudinal and behavioral loyalty in a service context. Since affective commitment is more positive and governed by free choice, whereas continuance commitment is more the result of perceived economic and psychological benefits of being in a relationship, the results of this study suggest that emotional bonds with customers provide a more enduring source of loyalty as compared to economic incentives and switching costs.

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In the 1990s, competition among public health insurance funds (‘sickness funds’) was introduced in Germany. As one means of competition, free choice of initial health funds and subsequent switching between them was made available to all insured. Since then, the number of funds has decreased substantially, and funds have had to engage in competitive strategies to remain in the market. In this paper, we want to analyse the funds' advertising activities in the face of the changed competitive environment. This has not been possible to date due to a lack of data. We use two new datasets to get a first insight into the potential effects of competition on funds' advertising strategies; one of the volume and cost of advertisements and one of their contents. Our results suggest that competition has been associated with an increase in the amount of advertising. As to the adverts themselves, we find that there was a decrease in the share of advertisements of a ‘general’ content in favour of advertisements of a more ‘fund-specific’ content. The data therefore indicate that once the market was open to switching of funds by the insured, funds' advertising efforts changed to differentiating their own perceived strengths from those of competitor funds. These observations allow us to draw some tentative conclusions about the relevance of (attempts of) risk selection by health funds via advertisements and about the general success of the pro-competitive legislation.

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It is known theoretically that an algorithm cannot be good for an arbitrary prior. We show that in practical terms this also applies to the technique of ``cross validation'', which has been widely regarded as defying this general rule. Numerical examples are analysed in detail. Their implications to researches on learning algorithms are discussed.

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A formalism for describing the dynamics of Genetic Algorithms (GAs) using method s from statistical mechanics is applied to the problem of generalization in a perceptron with binary weights. The dynamics are solved for the case where a new batch of training patterns is presented to each population member each generation, which considerably simplifies the calculation. The theory is shown to agree closely to simulations of a real GA averaged over many runs, accurately predicting the mean best solution found. For weak selection and large problem size the difference equations describing the dynamics can be expressed analytically and we find that the effects of noise due to the finite size of each training batch can be removed by increasing the population size appropriately. If this population resizing is used, one can deduce the most computationally efficient size of training batch each generation. For independent patterns this choice also gives the minimum total number of training patterns used. Although using independent patterns is a very inefficient use of training patterns in general, this work may also prove useful for determining the optimum batch size in the case where patterns are recycled.

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We analyse the dynamics of a number of second order on-line learning algorithms training multi-layer neural networks, using the methods of statistical mechanics. We first consider on-line Newton's method, which is known to provide optimal asymptotic performance. We determine the asymptotic generalization error decay for a soft committee machine, which is shown to compare favourably with the result for standard gradient descent. Matrix momentum provides a practical approximation to this method by allowing an efficient inversion of the Hessian. We consider an idealized matrix momentum algorithm which requires access to the Hessian and find close correspondence with the dynamics of on-line Newton's method. In practice, the Hessian will not be known on-line and we therefore consider matrix momentum using a single example approximation to the Hessian. In this case good asymptotic performance may still be achieved, but the algorithm is now sensitive to parameter choice because of noise in the Hessian estimate. On-line Newton's method is not appropriate during the transient learning phase, since a suboptimal unstable fixed point of the gradient descent dynamics becomes stable for this algorithm. A principled alternative is to use Amari's natural gradient learning algorithm and we show how this method provides a significant reduction in learning time when compared to gradient descent, while retaining the asymptotic performance of on-line Newton's method.

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An interactive hierarchical Generative Topographic Mapping (HGTM) ¸iteHGTM has been developed to visualise complex data sets. In this paper, we build a more general visualisation system by extending the HGTM visualisation system in 3 directions: bf (1) We generalize HGTM to noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM) developed in ¸iteKabanpami. bf (2) We give the user a choice of initializing the child plots of the current plot in either em interactive, or em automatic mode. In the interactive mode the user interactively selects ``regions of interest'' as in ¸iteHGTM, whereas in the automatic mode an unsupervised minimum message length (MML)-driven construction of a mixture of LTMs is employed. bf (3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualisation plots, since they can highlight the boundaries between data clusters. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. We illustrate our approach on a toy example and apply our system to three more complex real data sets.

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Aim To undertake a national study of teaching, learning and assessment in UK schools of pharmacy. Design Triangulation of course documentation, 24 semi-structured interviews undertaken with 29 representatives from the schools and a survey of all final year students (n=1,847) in the 15 schools within the UK during 2003–04. Subjects and setting All established UK pharmacy schools and final year MPharm students. Outcome measures Data were combined and analysed under the topics of curriculum, teaching and learning, assessment, multi-professional teaching and learning, placement education and research projects. Results Professional accreditation was the main driver for curriculum design but links to preregistration training were poor. Curricula were consistent but offered little student choice. On average half the curriculum was science-based. Staff supported the science content but students less so. Courses were didactic but schools were experimenting with new methods of learning. Examinations were the principal form of assessment but the contribution of practice to the final degree ranged considerably (21–63%). Most students considered the assessment load to be about right but with too much emphasis upon knowledge. Assessment of professional competence was focused upon dispensing and pharmacy law. All schools undertook placement teaching in hospitals but there was little in community/primary care. There was little inter-professional education. Resources and logistics were the major limiters. Conclusions There is a need for an integrated review of the accreditation process for the MPharm and preregistration training and redefinition of professional competence at an undergraduate level.

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The thesis is concerned with cross-cultural distance learning in two countries: Great Britain and France. Taking the example of in-house sales training, it argues that it is possible to develop courses for use in two or more countries of differing culture and language. Two courses were developed by the researcher. Both were essentially print-based distance-learning courses designed to help salespeople achieve a better understanding of their customers. One used a quantitative, the other qualitative approach. One considered the concept of the return on investment and the other, for which a video support was also developed, considered the analysis of a customer's needs. Part 1 of the thesis considers differences in the training context between France and Britain followed by a review of the learning process with reference to distance learning. Part 2 looks at the choice of training medium course design and evaluation and sets out the methodology adopted, including problems encountered in this type of fieldwork. Part 3 analyses the data and draws conclusions from the findings, before offering a series of guidelines for those concerned with the development of cross-cultural in-house training courses. The results of the field tests on the two courses were analysed in relation to the socio-cultural, educational and experiential background of the learners as well as their preferred learning styles. The thesis argues that it is possible to develop effective in-house sales training courses to be used in two cultures and identifies key considerations which need to be taken into account when carrying out this type of work.

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Background: Stereotypically perceived to be an ‘all male’ occupation, engineering has for many years failed to attract high numbers of young women [1,2]. The reasons for this are varied, but tend to focus on misconceptions of the profession as being more suitable for men. In seeking to investigate this issue a participatory research approach was adopted [3] in which two 17 year-old female high school students interviewed twenty high school girls. Questions focused on the girls’ perceptions of engineering as a study and career choice. The findings were recorded and analysed using qualitative techniques. The study identified three distinctive ‘influences’ as being pivotal to girls’ perceptions of engineering; pedagogical; social; and, familial. Pedagogical Influences: Pedagogical influences tended to focus on science and maths. In discussing science, the majority of the girls identified biology and chemistry as more ‘realistic’ whilst physics was perceived to more suitable for boys. The personality of the teacher, and how a particular subject is taught, proved to be important influences shaping opinions. Social Influences: Societal influences were reflected in the girls’ career choice with the majority considering medical or social science related careers. Although all of the girls believed engineering to be ‘male dominated’, none believed that a woman should not be engineer. Familial Influences: Parental influence was identified as key to career and study choice; only two of the girls had discussed engineering with their parents of which only one was being actively encouraged to pursue a career in engineering. Discussion: The study found that one of the most significant barriers to engineering is a lack of awareness. Engineering did not register in the girls’ lives, it was not taught in school, and only one had met a female engineer. Building on the study findings, the discussion considers how engineering could be made more attractive to young women. Whilst misconceptions about what an engineer is need to be addressed, other more fundamental pedagogical barriers, such as the need to make physics more attractive to girls and the need to develop the curriculum so as to meet the learning needs of 21st Century students are discussed. By drawing attention to the issues around gender and the barriers to engineering, this paper contributes to current debates in this area – in doing so it provides food for thought about policy and practice in engineering and engineering education.

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Higher education institutions are increasingly using social software tools to support teaching and learning. Despite the fact that social software is often used in a social context, these applications can significantly contribute to the educational experience of a student. However, as the social software domain comprises a considerable diversity of tools, the respective tools can be expected to differ in the way they can contribute to teaching and learning. In this review on the educational use of social software, we systematically analyze and compare the diverse social software tools and identify their contributions to teaching and learning. By integrating established learning theory and the extant literature on the individual social software applications we seek to contribute to a theoretical foundation for social software use and the choice of tools. Case vignettes from several UK higher education institutions are used to illustrate the different applications of social software tools in teaching and learning.

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There is an increasing trend by publishers to provide supplementary learning materials with text books in order to improve the learning experience and thus ultimately improve text book sales. This study will aim to establish the use of these materials and their relevance to students in terms of supporting student learning. The materials include multiple choice test banks, animated demonstrations, simulations, quizzes and electronic versions of the text. The study will focus on the extensive library of web-based learning materials available on the ‘WileyPlus’ web platform which accompanies the textbook ‘Operations Management’, 2nd edition authored by A. Greasley and published by John Wiley and Sons Ltd.

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Recently, we have developed the hierarchical Generative Topographic Mapping (HGTM), an interactive method for visualization of large high-dimensional real-valued data sets. In this paper, we propose a more general visualization system by extending HGTM in three ways, which allows the user to visualize a wider range of data sets and better support the model development process. 1) We integrate HGTM with noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM). This enables us to visualize data of inherently discrete nature, e.g., collections of documents, in a hierarchical manner. 2) We give the user a choice of initializing the child plots of the current plot in either interactive, or automatic mode. In the interactive mode, the user selects "regions of interest," whereas in the automatic mode, an unsupervised minimum message length (MML)-inspired construction of a mixture of LTMs is employed. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. 3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualization plots, since they can highlight the boundaries between data clusters. We illustrate our approach on a toy example and evaluate it on three more complex real data sets. © 2005 IEEE.

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Networked Learning, e-Learning and Technology Enhanced Learning have each been defined in different ways, as people's understanding about technology in education has developed. Yet each could also be considered as a terminology competing for a contested conceptual space. Theoretically this can be a ‘fertile trans-disciplinary ground for represented disciplines to affect and potentially be re-orientated by others’ (Parchoma and Keefer, 2012), as differing perspectives on terminology and subject disciplines yield new understandings. Yet when used in government policy texts to describe connections between humans, learning and technology, terms tend to become fixed in less fertile positions linguistically. A deceptively spacious policy discourse that suggests people are free to make choices conceals an economically-based assumption that implementing new technologies, in themselves, determines learning. Yet it actually narrows choices open to people as one route is repeatedly in the foreground and humans are not visibly involved in it. An impression that the effective use of technology for endless improvement is inevitable cuts off critical social interactions and new knowledge for multiple understandings of technology in people's lives. This paper explores some findings from a corpus-based Critical Discourse Analysis of UK policy for educational technology during the last 15 years, to help to illuminate the choices made. This is important when through political economy, hierarchical or dominant neoliberal logic promotes a single ‘universal model’ of technology in education, without reference to a wider social context (Rustin, 2013). Discourse matters, because it can ‘mould identities’ (Massey, 2013) in narrow, objective economically-based terms which 'colonise discourses of democracy and student-centredness' (Greener and Perriton, 2005:67). This undermines subjective social, political, material and relational (Jones, 2012: 3) contexts for those learning when humans are omitted. Critically confronting these structures is not considered a negative activity. Whilst deterministic discourse for educational technology may leave people unconsciously restricted, I argue that, through a close analysis, it offers a deceptively spacious theoretical tool for debate about the wider social and economic context of educational technology. Methodologically it provides insights about ways technology, language and learning intersect across disciplinary borders (Giroux, 1992), as powerful, mutually constitutive elements, ever-present in networked learning situations. In sharing a replicable approach for linguistic analysis of policy discourse I hope to contribute to visions others have for a broader theoretical underpinning for educational technology, as a developing field of networked knowledge and research (Conole and Oliver, 2002; Andrews, 2011).