43 resultados para Learn-to-learn


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Routine computer tasks are often difficult for older adult computer users to learn and remember. People tend to learn new tasks by relating new concepts to existing knowledge. However, even for 'basic' computer tasks there is little, if any, existing knowledge on which older adults can base their learning. This paper investigates a custom file management interface that was designed to aid discovery and learnability by providing interface objects that are familiar to the user. A study was conducted which examined the differences between older and younger computer users when undertaking routine file management tasks using the standard Windows desktop as compared with the custom interface. Results showed that older adult computer users requested help more than ten times as often as younger users when using a standard windows/mouse configuration, made more mistakes and also required significantly more confirmations than younger users. The custom interface showed improvements over standard Windows/mouse, with fewer confirmations and less help being required. Hence, there is potential for an interface that closely mimics the real world to improve computer accessibility for older adults, aiding self-discovery and learnability.

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This paper examines the factors that influence pupil take up of a subject, in this case history, at GCSE. The research indicates that pupils enjoy history but significant factors prevent many from choosing it for further study; these include factors that are beyond the control of teachers, such as government policy and the way this is interpreted by senior managers in school, and factors that are within the control of teachers. The paper suggests that there are lessons that departments can learn from more successful departments but there are also important side effects of government policy that are having unintended consequences.

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Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a mobile robot.

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Climate change is putting Colombian agriculture under significant stress and, if no adaptation is made, the latter will be severely impacted during the next decades. Ramirez-Villegas et al. (2012) set out a government-led, top-down, techno-scientific proposal for a way forward by which Colombian agriculture could adapt to climate change. However, this proposal largely overlooks the root causes of vulnerability of Colombian agriculture, and of smallholders in particular. I discuss some of the hidden assumptions underpinning this proposal and of the arguments employed by Ramirez-Villegas et al., based on existing literature on Colombian agriculture and the wider scientific debate on adaptation to climate change. While technical measures may play an important role in the adaptation of Colombian agriculture to climate change, I question whether the actions listed in the proposal alone and specifically for smallholders, truly represent priority issues. I suggest that by i) looking at vulnerability before adaptation, ii) contextualising climate change as one of multiple exposures, and iii) truly putting smallholders at the centre of adaptation, i.e. to learn about and with them, different and perhaps more urgent priorities for action can be identified. Ultimately, I argue that what is at stake is not only a list of adaptation measures but, more importantly, the scientific approach from which priorities for action are identified. In this respect, I propose that transformative rather than technical fix adaptation represents a better approach for Colombian agriculture and smallholders in particular, in the face of climate change.

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Two central issues in magnetospheric research are understanding the mapping of the low-altitude ionosphere to the distant regions of the magnetsphere, and understanding the relationship between the small-scale features detected in the various regions of the ionosphere and the global properties of the magnetosphere. The high-latitude ionosphere, through its magnetic connection to the outer magnetosphere, provides an important view of magnetospheric boundaries and the physical processes occurring there. All physical manifestations of this magnetic connectivity (waves, particle precipitation, etc.), however, have non-zero propagation times during which they are convected by the large-scale magnetospheric electric field, with phenomena undergoing different convection distances depending on their propagation times. Identification of the ionospheric signatures of magnetospheric regions and phenomena, therefore, can be difficult. Considerable progress has recently been made in identifying these convection signatures in data from low- and high-altitude satellites. This work has allowed us to learn much about issues such as: the rates of magnetic reconnection, both at the dayside magnetopause and in the magnetotail; particle transport across the open magnetopause; and particle acceleration at the magnetopause and the magnetotail current sheets.

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In response to herbivory by insects, several plant species have been shown to produce volatiles that attract the natural enemies of those herbivores. Using a Y-tube olfactometer, we investigated responses of the aphid parasitoid Diaeretiella rapae MacIntosh (Hymenoptera: Aphidiidae) to volatiles from Arabidopsis thaliana Columbia (Brassicaceae) plants that were either undamaged, infested by the peach-potato aphid, Myzus persicae Sulzer (Homoptera: Aphididae), or mechanically damaged, as well as to volatiles from just the aphid or its honeydew. In dual-choice experiments, female D. rapae given oviposition experience on A. thaliana infested with M. persicae were significantly attracted to volatiles from A. thaliana infested with M. persicae over volatiles from undamaged A. thaliana and similarly were significantly attracted to plants that had been previously infested by M. persicae, but from which the aphids were removed, over undamaged plants. Diaeretiella rapae did not respond to volatiles from M. persicae alone, their honeydew, or plants mechanically damaged with either a pin or scissors. We conclude that an interaction between the plant and the aphid induces A. thaliana to produce volatiles, which D. rapae can learn and respond to. Poor responses of D. rapae to volatiles from an A. thaliana plant that had two leaves infested with M. persicae, with the two infested leaves being removed before testing, suggested the possibility that, at this stage of infestation, the majority of volatile production induced by M. persicae may be localized to the infested tissues of the plant. We conclude that this tritrophic interaction is a suitable model system for future investigations of the biochemical pathways involved in the production of aphid-induced volatiles attractive to natural enemies.

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Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter-annual Arctic sea-ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictability of Arctic climate. We also examine key issues for ensemble system design, such as: measuring skill, the role of ensemble size and generation of ensemble members. When assessing the potential skill of a set of prediction experiments, using more than one metric is essential as different choices can significantly alter conclusions about the presence or lack of skill. We find that increasing both the number of hindcasts and ensemble size is important for reliably assessing the correlation and expected error in forecasts. For other metrics, such as dispersion, increasing ensemble size is most important. Probabilistic measures of skill can also provide useful information about the reliability of forecasts. In addition, various methods for generating the different ensemble members are tested. The range of techniques can produce surprisingly different ensemble spread characteristics. The lessons learnt should help inform the design of future operational prediction systems.

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While eye movements have been used widely to investigate how skilled adult readers process written language, relatively little research has used this methodology with children. This is unfortunate as, as we discuss here, eye-movement studies have significant potential to inform our understanding of children’s reading development. We consider some of the empirical and theoretical issues that arise when using this methodology with children, illustrating our points with data from an experiment examining word frequency effects in 8-year-old children’s sentence reading. Children showed significantly longer gaze durations to low than high-frequency words, demonstrating that linguistic characteristics of text drive children’s eye movements as they read. We discuss these findings within the broader context of how eye-movement studies can inform our understanding of children’s reading, and can assist with the development of appropriately targeted interventions to support children as they learn to read.

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The paper presents research with small and medium enterprise (SME) owners who have participated in a leadership development programme. The primary focus of the paper is on learning transfer and factors affecting it, arguing that entrepreneurs must engage in ‘action’ in order to ‘learn’ and that under certain conditions they may transfer learning to their firm. The paper draws on data from 19 focus groups undertaken from 2010 to 2012, involving 51 participants in the LEAD Wales programme. It considers the literatures exploring learning transfer and develops a conceptual framework, outlining four areas of focus for entrepreneurial learning. Utilising thematic analysis, it describes and evaluates what (actual facts and information) and how (techniques, styles of learning) participants transfer and what actions they take to improve the business and develop their people. The paper illustrates the complex mechanisms involved in this process and concludes that action learning is a method of facilitating entrepreneurial learning which is able to help address some of the problems of engagement, relevance and value that have been highlighted previously. The paper concludes that the efficacy of an entrepreneurial learning intervention in SMEs may depend on the effectiveness of learning transfer.