959 resultados para Learning objects repository


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What is the relationship between the type of training combatants receive upon recruitment into an armed group and their propensity to abuse civilians in civil war? Does military training or political training prevent or exacerbate the victimization of civilians by armed non-state actors? While the literature on civilian victimization has expanded rapidly, few studies have examined the correlation between abuse of civilians and the modes of training that illegal armed actors receive. Using a simple formal model, we develop hypotheses regarding this connection and argue that while military training should not decrease the probability that a combatant engages in civilian abuse, political training should. We test these hypotheses using a new survey consisting of a representative sample of approximately 1,500 demobilized combatants from the Colombian conflict, which we match with department-level data on civilian casualties. The empirical analysis confirms our hypotheses about the connection between training and civilian abuse and the results are robust to adding a full set of controls both at the department and at the individual level

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In this paper, we employ techniques from artificial intelligence such as reinforcement learning and agent based modeling as building blocks of a computational model for an economy based on conventions. First we model the interaction among firms in the private sector. These firms behave in an information environment based on conventions, meaning that a firm is likely to behave as its neighbors if it observes that their actions lead to a good pay off. On the other hand, we propose the use of reinforcement learning as a computational model for the role of the government in the economy, as the agent that determines the fiscal policy, and whose objective is to maximize the growth of the economy. We present the implementation of a simulator of the proposed model based on SWARM, that employs the SARSA(λ) algorithm combined with a multilayer perceptron as the function approximation for the action value function.

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Previous research has shown that often there is clear inertia in individual decision making---that is, a tendency for decision makers to choose a status quo option. I conduct a laboratory experiment to investigate two potential determinants of inertia in uncertain environments: (i) regret aversion and (ii) ambiguity-driven indecisiveness. I use a between-subjects design with varying conditions to identify the effects of these two mechanisms on choice behavior. In each condition, participants choose between two simple real gambles, one of which is the status quo option. I find that inertia is quite large and that both mechanisms are equally important.

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Infants (12 to 17 months) were taught 2 novel words for 2 images of novel objects, by pairing isolated auditory labels with to-be-associated images. Comprehension was tested using a preferential looking task in which the infant was presented with both images together with an isolated auditory label. The auditory label usually, but not always, matched one of the images. Infants looked preferentially at images that matched the auditory stimulus. The experiment controlled within-subjects for both side bias and preference for previously named items. Infants showed learning after 12 presentations of the new words. Evidence is presented that, in certain circumstances, the duration of longest look at a target may be a more robust measure of target preference than overall looking time. The experiment provides support for previous demonstrations of rapid word learning by pre-vocabulary spurt children, and offers some methodological improvements to the preferential looking task.

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Recent interest in material objects - the things of everyday interaction - has led to articulations of their role in the literature on organizational knowledge and learning. What is missing is a sense of how the use of these 'things' is patterned across both industrial settings and time. This research addresses this gap with a particular emphasis on visual materials. Practices are analysed in two contrasting design settings: a capital goods manufacturer and an architectural firm. Materials are observed to be treated both as frozen, and hence unavailable for change; and as fluid, open and dynamic. In each setting temporal patterns of unfreezing and refreezing are associated with the different types of materials used. The research suggests that these differing patterns or rhythms of visual practice are important in the evolution of knowledge and in structuring social relations for delivery. Hence, to improve their performance practitioners should not only consider the types of media they use, but also reflect on the pace and style of their interactions.

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This study was an attempt to identify the epistemological roots of knowledge when students carry out hands-on experiments in physics. We found that, within the context of designing a solution to a stated problem, subjects constructed and ran thought experiments intertwined within the processes of conducting physical experiments. We show that the process of alternating between these two modes- empirically experimenting and experimenting in thought- leads towards a convergence on scientifically acceptable concepts. We call this process mutual projection. In the process of mutual projection, external representations were generated. Objects in the physical environment were represented in an imaginary world and these representations were associated with processes in the physical world. It is through this coupling that constituents of both the imaginary world and the physical world gain meaning. We further show that the external representations are rooted in sensory interaction and constitute a semi-symbolic pictorial communication system, a sort of primitive 'language', which is developed as the practical work continues. The constituents of this pictorial communication system are used in the thought experiments taking place in association with the empirical experimentation. The results of this study provide a model of physics learning during hands-on experimentation.

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Older adults often demonstrate higher levels of false recognition than do younger adults. However, in experiments using novel shapes without preexisting semantic representations, this age-related elevation in false recognition was found to be greatly attenuated. Two experiments tested a semantic categorization account of these findings, examining whether older adults show especially heightened false recognition if the stimuli have preexisting semantic representations, such that semantic category information attenuates or truncates the encoding or retrieval of item-specific perceptual information. In Experiment 1, ambiguous shapes were presented with or without disambiguating semantic labels. Older adults showed higher false recognition when labels were present but not when labels were never presented. In Experiment 2, older adults showed higher false recognition for concrete but not abstract objects. The semantic categorization account was supported.

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Perirhinal cortex in monkeys has been thought to be involved in visual associative learning. The authors examined rats' ability to make associations between visual stimuli in a visual secondary reinforcement task. Rats learned 2-choice visual discriminations for secondary visual reinforcement. They showed significant learning of discriminations before any primary reinforcement. Following bilateral perirhinal cortex lesions, rats continued to learn visual discriminations for visual secondary reinforcement at the same rate as before surgery. Thus, this study does not support a critical role of perirhinal cortex in learning for visual secondary reinforcement. Contrasting this result with other positive results, the authors suggest that the role of perirhinal cortex is in "within-object" associations and that it plays a much lesser role in stimulus-stimulus associations between objects.

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Investigation of the anatomical substructure of the medial temporal lobe has revealed a number of highly interconnected areas, which has led some to propose that the region operates as a unitary memory system. However, here we outline the results of a number of studies from our laboratories, which investigate the contributions of the rat's perirhinal cortex and postrhinal cortex to memory, concentrating particularly on their respective roles in memory for objects. By contrasting patterns of impairment and spared abilities on a number of related tasks, we suggest that perirhinal cortex and postrhinal cortex make distinctive contributions to learning and memory: for example, that postrhinal cortex is important in learning about within-scene position and context. We also provide evidence that despite the strong connectivity between these cortical regions and the hippocampus, the hippocampus, as evidenced by lesions of the fornix, has a distinct function of its own-combining information about objects, positions, and contexts.

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This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic object-centred and appearance-based representations in computer vision giving improved hypothesis verification under iconic matching. The "appearance" of a 3D object is learnt using an eigenspace representation obtained as it is tracked through a scene. The feature representation implicitly models the background and the objects observed enabling the segmentation of the objects from the background. The method is shown to enhance model-based tracking, particularly in the presence of clutter and occlusion, and to provide a basis for identification. The unified approach is discussed in the context of the traffic surveillance domain. The approach is demonstrated on real-world image sequences and compared to previous (edge-based) iconic evaluation techniques.

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In this project we explore how to enhance the experience and understanding of cultural heritage in museums and heritage sites by creating interactive multisensory objects collaboratively with artists, technologists and people with learning disabilities. We focus here on workshops conducted during the first year of a three year project in which people with learning disabilities each constructed a 'sensory box' to represent their experiences of Speke Hall, a heritage site in the UK. The box is developed further in later workshops which explore aspects of physicality and how to appeal to the entire range of senses, making use of Arduino technology and basic sensors to enable an interactive user experience.

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Purpose – The purpose of this paper is to demonstrate analytically how entrepreneurial action as learning relating to diversifying into technical clothing – i.e. a high-value manufacturing sector – can take place. This is particularly relevant to recent discussion and debate in academic and policy-making circles concerning the survival of the clothing manufacture industry in developed industrialised countries. Design/methodology/approach – Using situated learning theory (SLT) as the major analytical lens, this case study examines an episode of entrepreneurial action relating to diversification into a high-value manufacturing sector. It is considered on instrumentality grounds, revealing wider tendencies in the management of knowledge and capabilities requisite for effective entrepreneurial action of this kind. Findings – Boundary events, brokers, boundary objects, membership structures and inclusive participation that addresses power asymmetries are found to be crucial organisational design elements, enabling the development of inter- and intracommunal capacities. These together constitute a dynamic learning capability, which underpins entrepreneurial action, such as diversification into high-value manufacturing sectors. Originality/value – Through a refinement of SLT in the context of entrepreneurial action, the paper contributes to an advancement of a substantive theory of managing technological knowledge and capabilities for effective diversification into high-value manufacturing sectors.

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Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the meaning of a word by looking for something in common across all observed uses of that word, and supervised operant conditioning learning, in which there is strong feedback between individuals about the intended meaning of the words. Despite the stark differences between these learning schemes, we show that they yield the same communication accuracy in the limits of large N and H, which coincides with the result of the classical occupancy problem of randomly assigning N objects to H words.

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Pós-graduação em Educação - FCT

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Pós-graduação em Educação - FCT