998 resultados para geometry learning
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Peer-reviewed
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El proyecto "Propuesta de un ambiente e-learning para el fortalecimiento de las habilidades de alfabetización visual e informacional: caso Licenciatura en Electrónica - UPN" fortalece la investigación alrededor de ambientes e-learning de la Universitat Oberta de Catalunya (UOC). Con la investigación se buscó determinar las estrategias organizativas, pedagógicas y tecnológicas a implementar en el diseño y desarrollo de un entorno e-learning que promueva las habilidades de alfabetización visual e informacional en estudiantes de primer semestre de la Licenciatura en Electrónica de la Universidad Pedagógica Nacional de Colombia. La investigación realizada fue de tipo cualitativo a través de un estudio de caso.
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Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.
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This article examines the participation of Spanish older people in formal, non-formal and informal learning activities and presents a profile of participants in each kind of learning activity. We used data from a nationally representative sample of Spanish people between 60 and 75 years old (n = 4,703). The data were extracted from the 2007 Encuesta sobre la Participación de la Población Adulta en Actividades de Aprendizaje (EADA, Survey on Adult Population Involvement in Learning Activities). Overall, only 22.8 % of the sample participated in a learning activity. However, there was wide variation in the participation rates for the different types of activity. Informal activities were far more common than formal ones. Multivariate logistic regression indicated that education level and involvement in social and cultural activities were associated with likelihood of participating, regardless of the type of learning activity. When these variables were taken into account, age did not predict decreasing participation, at least in non-formal and informal activities. Implications for further research, future trends and policies to promote older adult education are discussed.
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Tämä julkaisu ilmestyy Turussa 18.–19.5.2009 järjestettävien valtakunnallisten kielikeskuspäivien yhteydessä. Turun yliopiston kielikeskus viettää samaan aikaan 30-vuotisjuhlaansa. Erään luokittelun mukaan 30–45-vuotias elää varsinaista keski-ikäänsä, kun taas joissakin katsotaan, että 28–35 vuoden ikä on vasta ns.
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The thesis deals with the phenomenon of learning between organizations in innovation networks that develop new products, services or processes. Inter organizational learning is studied especially at the level of the network. The role of the network can be seen as twofold: either the network is a context for inter organizational learning, if the learner is something else than the network (organization, group, individual), or the network itself is the learner. Innovations are regarded as a primary source of competitiveness and renewal in organizations. Networking has become increasingly common particularly because of the possibility to extend the resource base of the organization through partnerships and to concentrate on core competencies. Especially in innovation activities, networks provide the possibility to answer the complex needs of the customers faster and to share the costs and risks of the development work. Networked innovation activities are often organized in practice as distributed virtual teams, either within one organization or as cross organizational co operation. The role of technology is considered in the research mainly as an enabling tool for collaboration and learning. Learning has been recognized as one important collaborative process in networks or as a motivation for networking. It is even more important in the innovation context as an enabler of renewal, since the essence of the innovation process is creating new knowledge, processes, products and services. The thesis aims at providing enhanced understanding about the inter organizational learning phenomenon in and by innovation networks, especially concentrating on the network level. The perspectives used in the research are the theoretical viewpoints and concepts, challenges, and solutions for learning. The methods used in the study are literature reviews and empirical research carried out with semi structured interviews analyzed with qualitative content analysis. The empirical research concentrates on two different areas, firstly on the theoretical approaches to learning that are relevant to innovation networks, secondly on learning in virtual innovation teams. As a result, the research identifies insights and implications for learning in innovation networks from several viewpoints on organizational learning. Using multiple perspectives allows drawing a many sided picture of the learning phenomenon that is valuable because of the versatility and complexity of situations and challenges of learning in the context of innovation and networks. The research results also show some of the challenges of learning and possible solutions for supporting especially network level learning.
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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 numbersand reduced its absenteeism rate to zero. The organizational change that facilitatedthese 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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In this paper I defend a teleological explanation of normativity, i. e., I argue that what an organism (or device) is supposed to do is determined by its etiological function. In particular, I present a teleological account of the normativity that arises in learning processes, and I defend it from some objections