195 resultados para Learning Networks
Resumo:
Background. Conceptions of learning have been investigated for students in higher. education in different countries. Some studies found that students' conceptions change and develop over time while others have found no changes. Investigating conceptions of learning for Australian Aboriginal and Torres Strait Islander university students is a relatively new area of research. Aims. This study set out to investigate conceptions of learning for Aboriginal and Torres Strait Islander university students during the first two years of their undergraduate degree courses in three Australian universities. Conceptions for each year were compared. Knowing, more about learning as conceived by this cultural group may facilitate more productive higher educational experiences. Sample. The sample comprised 17 students studying various degrees; Il were male and 6 were female. Ages ranged from 18 to 48 years; mean age was 26 years. Method. This was a phenomenographic, longitudinal study. Individual semistructured interviews were conducted each year to ascertain students' conceptions of learning. Conceptions for second year were derived independently of those From first year. A comparative analysis then took place to determine ally changes. Results. These students held conceptions of learning that were similar to those of other university students; however there were some intrinsic differences. On a group level, conceptions changed somewhat over the two years as did core conceptions reported by some individual students. Some students also exhibited a greater awareness of learning during their second year that resulted in three dimensions of changed awareness. Conclusions. We believe the changed conceptions and awareness resulted from learning at university where there is some need to understand and explain phenomena in relation to theory. This brought about new understandings which allowed students to see their own learning in a relational sense.
Resumo:
Following the application of the remember/know paradigm to student learning by Conway et al. (1997), this study examined changes in learning and memory awareness of university students in a lecture course and a research methods course. The proposed shift from a dominance of 'remember' awareness in early learning to a dominance of 'know' awareness as learning progresses and schematization occurs was evident for the methods course but not for the lecture course. The patterns of remember and know awareness and proposed associated levels of schematization were supported by a separate measure of the quality of student learning using the SOLO (Structure of Observed Learning Outcomes) Taxonomy. As found by previous research, the remember-to-know shift and schematization of knowledge is dependent upon type of course and level of achievement. Findings are discussed in terms of the utility of the methodology used, the theoretical implications and the applications to educational practice. Copyright (C) 2001 John Wiley & Sons, Ltd.
Resumo:
Learning organizations are a special form of organization where enhancing learning is a strategy to increase intellectual capital. Developing learning organizations has become an imperative for many managers, since an organization's learning methods and rate may be the only source of sustainable competitive advantage. However, learning organization theory tends to be prescriptive and rhetorical, with empirical research still relatively new. This paper contributes to the literature by reporting case-study research in progress based on four Australian organizations. In the organizations studied, use of the learning organization metaphor was coupled with an emergent metaphor: organization as `family". By employing structure mapping of metaphor within analytical induction, both established methods but not combined before, this paper shows how theory might be developed from metaphor.
Resumo:
This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.