624 resultados para Learning Approach


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This study addresses the effectivity of the Anti-Bias approach and training methodology as a pedagogical political strategy to challenge oppression among student groups in the cities of Bombay and Berlin. The Anti-Bias trainings conducted within the framework of this study also become the medium through which the perpetuation of oppressive structures by students within and outside the school is investigated. Empirical data from predominantly qualitative investigations in four secondary schools, two each in Bombay and Berlin, is studied and analysed on the basis of theoretical understandings of prejudice, discrimination and identity. This study builds on insights offered by previous research on prejudices and evaluations of anti-bias and diversity interventions, where the lack of sufficient research and thorough evaluations testing impact has been identified (Levy Paluck, 2006). The theoretical framework suggests that prejudices and discriminatory practices are learnt and performed by individuals over the years by way of pre-existing discourses, and that behaviour and practices can be unlearnt through a multi-step process. It proposes that the discursive practices of students contribute to the constitution of their viable selves and in the constitution of ‘others’. Drawing on this framework, the study demonstrates how student-subjects in Bombay and Berlin perpetuate oppressive discourses by performing their identities and performing identities onto ‘others’. Such performative constitution opens up the agency of the individual, disclosing the shifting and dynamic nature of identities. The Anti-Bias approach is posited as an alternative to oppressive discourses and a vehicle that encourages and assists the agency of individuals. The theoretical framework, which brings together a psychological approach to prejudice, a structural approach to discrimination and a poststructural approach to identity, facilitates the analysis of the perpetuation of dominant discourses by the students, as well as how they negotiate their way through familiar norms and discourses. Group discussions and interviews a year after the respective trainings serve to evaluate the agency of the students and the extent to which the training impacted on their perceptions, attitudes and behavioural practices. The study reveals the recurrence of the themes race, religion, gender and sexuality in the representational practices of the students groups in Berlin and Bombay. It demonstrates how students in this study not only perform, but also negotiate and resist oppressive structures. Of particular importance is the role of the school: When schools offer no spaces for discussion, debate and action on contemporary social issues, learning can neither be put into practice nor take on a positive, transformative form. In such cases, agency and resistance is limited and interventionist actions yield little. This study reports the potential of the Anti-Bias approach and training as a tool of political education and action in education. It demonstrates that a single training can initiate change but sustaining change requires long-term strategies and on-going actions. Taking a poststructural perspective, it makes concrete suggestions to adapt and alter the Anti-Bias approach and the implementation of Anti-Bias trainings.

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As AI has begun to reach out beyond its symbolic, objectivist roots into the embodied, experientialist realm, many projects are exploring different aspects of creating machines which interact with and respond to the world as humans do. Techniques for visual processing, object recognition, emotional response, gesture production and recognition, etc., are necessary components of a complete humanoid robot. However, most projects invariably concentrate on developing a few of these individual components, neglecting the issue of how all of these pieces would eventually fit together. The focus of the work in this dissertation is on creating a framework into which such specific competencies can be embedded, in a way that they can interact with each other and build layers of new functionality. To be of any practical value, such a framework must satisfy the real-world constraints of functioning in real-time with noisy sensors and actuators. The humanoid robot Cog provides an unapologetically adequate platform from which to take on such a challenge. This work makes three contributions to embodied AI. First, it offers a general-purpose architecture for developing behavior-based systems distributed over networks of PC's. Second, it provides a motor-control system that simulates several biological features which impact the development of motor behavior. Third, it develops a framework for a system which enables a robot to learn new behaviors via interacting with itself and the outside world. A few basic functional modules are built into this framework, enough to demonstrate the robot learning some very simple behaviors taught by a human trainer. A primary motivation for this project is the notion that it is practically impossible to build an "intelligent" machine unless it is designed partly to build itself. This work is a proof-of-concept of such an approach to integrating multiple perceptual and motor systems into a complete learning agent.

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The Bologna Process defends the adoption of a higher education in teaching-learning methodologies that – in contraposition to the previous model based on the transmission of knowledge, which for being essentially theoretical, gives the student a passive role in the knowledge construction process – allows a (pro) active, autonomous and practical learning, where the student acquires and develops his competences. The personal tutorial guidance sessions are included in the teaching contact hours. This abstract presents a study about the University of Minho (first cycle) Courses Students’ perceptions of the personal tutorial guidance sessions’ relevance in the scope of the learning-teaching process, so as to confirm if the implementation/implantation of the commonly called tutorial (type) education, as an approach to an active, autonomous and practical learning, is sensed by the learners themselves

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In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

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Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

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This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

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This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task

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The UK Professional Standards Framework (UK PSF) for teaching and supporting learning, launched in February 2006, is a flexible framework which uses a descriptor-based approach to professional standards. There are three standard descriptors each of which is applicable to a number of staff roles and to different career stages of those engaged in teaching and supporting learning. The standard descriptors are underpinned by areas of professional activity, core knowledge and professional values. The framework provides a reference point for institutions and individuals as well as supporting ongoing development within any one standard descriptor.

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This paper presents the findings of a podcasting trial held in 2007-2008 within the Faculty of Economics and Business at the University of Sydney, Australia. The trial investigates the value of using short-format podcasts to support assessment for postgraduate and undergraduate students. A multi-method approach is taken in investigating perceptions of the benefits of podcasting, incorporating surveys, focus groups and interviews. The results show that a majority of students believe they gained learning benefits from the podcasts and appreciated the flexibility of the medium to support their learning, and the lecturers felt the innovation helped diversify their pedagogical approach and support a diverse student population. Three primary conclusions are presented: (1) most students reject the mobile potential of podcasting in favour of their traditional study space at home; (2) what students and lecturers value about this podcasting design overlap; (3) the assessment-focussed, short-format podcast design may be considered a successful podcasting model. The paper finishes by identifying areas for future research on the effective use of podcasting in learning and teaching.

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This guide provides a brief overview on different learning styles, along with the best way to approach study for each type.

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The use of electronic documents is constantly growing and the necessity to implement an ad-hoc eCertificate which manages access to private information is not only required but also necessary. This paper presents a protocol for the management of electronic identities (eIDs), meant as a substitute for the paper-based IDs, in a mobile environment with a user-centric approach. Mobile devices have been chosen because they provide mobility, personal use and high computational complexity. The inherent user-centricity also allows the user to personally manage the ID information and to display only what is required. The chosen path to develop the protocol is to migrate the existing eCert technologies implemented by the Learning Societies Laboratory in Southampton. By comparing this protocol with the analysis of the eID problem domain, a new solution has been derived which is compatible with both systems without loss of features.

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The educational software and computer assisted learning has been used in schools to promote the interest of students in new ways of thinking and learning so it can be useful in the reading learning process. Experimental studies performed in preschool and school age population have shown a better yield and a positive effect in reading, mathematics and cognitive skills in children who use educative software for fi fteen to twenty minutes a day periods. The goal of this study was to evaluate the progression in verbal, visual-motor integration and reading skills in children who were using educational software to compare them with a group in traditional pedagogic methodology. Results: All children were evaluated before using any kind of pedagogic approach. Initial evaluation revealed a lower–age score in all applied test. 11% of them were at high risk for learning disorders. There was a second evaluation that showed a significant positive change compared with the fi rst one. Nevertheless, despite some items, there were no general differences comparing the groups according if they were using or not a computer. In conclusion, policies on using educational software and computers must be revaluated due to the fact that children in our public schools come from a deprived environment with a lack of opportunities to use technologies.

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Traditionally, school efficiency has been measured as a function of educational production. In the last two decades, however, studies in the economics of education have indicated that more is required to improve school efficiency: researchers must explore how significant changes in school organization affect the performance of at-risk students. In this paper we introduce Henry Levin’s adoption of the X-efficiency approach to education and we describe the efficient and cost-effective characteristics of one Learning Communities Project School that significantly improved its student outcomes and enrollment numbers and reduced its absenteeism rate to zero. The organizational change that facilitated these improvements defined specific issues to address. Students’ school success became the focus of the school project, which also offered specific incentives, selected teachers, involved parents and community members in decisions, and used the most efficient technologies and methods. This case analysis reveals new two elements—family training and community involvement—that were not explicit parts of Levin’s adaptation. The case of the Antonio Machado Public School should attract the attention of both social scientists and policy makers

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The main premise of Vygotsky’s cultural-historical theory is that to promote learning, and thus development, educators must intervene in, and change, the students’ socio-cultural context. Vygotsky’s theory, however, has been misinterpreted and the opposite approach has been accepted: the teaching is adapted, according to the context. The result is widespread failure in schools. This article reclaims the true transformative meaning of Vygotskian theory and shows how successful schools in several countries implement various actions to transform their social and cultural environment. Data is presented from six case studies of successful schools conducted in five European countries. The analysis shows that these actions improve instrumental learning and, consequently, cognitive development. All these efforts focus on teaching methods that aim to increase the amount that students learn