926 resultados para learning by discovering


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Virtual learning environments are online spaces where learners interact with other learners, teachers, resources and the environment in itself. Although technology is meant to enhance the learning process, there are important issues regarding pedagogical and organizational aspects that must be addressed. In this paper we review the barriers detected in a virtual university which exclusively uses Internet as the main channel of communication, with no face-to-face requirements exceptthose related to final evaluation.

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Peer-reviewed

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LORs, addressing content management and preservation, have the positive collaterals of institutional positioning and dissemination, but their main benefit is the empowerment of interest-centred learning communities, as we recognise that learning is much more than content, which becomes infrastructure: the LOR provides the learner interaction with the LOs, but also with other learners and teachers.

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Since its inception in 1994 as a purely online university, the Universitat Oberta de Catalunya(UOC) has been able to position itself among the main universities of the Catalan and Spanish university systems. Most of the students at the UOC (currently more than 60,000) are adults who have a profile that could hardly fit into the traditional university system, thus finding in the UOC an opportunity to start or continue their higher education grades, in a very innovative environment. The intensive use of ICT for both theteaching/learning processes and management allowsresearchers and practitioners to obtain data aboutwhat takes place in the UOC Virtual Campus, which is continuously being improved according to suchfindings.

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User retention is a major goal for higher education institutions running their teaching and learning programmes online. This is the first investigation into how the senses of presence and flow, together with perceptions about two central elements of the virtual education environment (didactic resource quality and instructor attitude), facilitate the user¿s intention to continue e-learning. We use data collected from a large sample survey of current users in a pure e-learning environment along with objective data about their performance. The results provide support to the theoretical model. The paper further offers practical suggestions for institutions and instructors who aim to provide effective e-learning experiences.

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Las autoras y autores de este libro ofrecen una descripción de la evolución general del e-learning apuntando los elementos clave hacia los que debe ir evolucionando. Parten de la experiencia y la práctica contrastada con las investigaciones sobre el tema. A lo largo de los distintos capítulos nos muestran cómo vive un estudiante virtual, su papel y la manera en que plantea y organiza sus actividades; nos acercan al profesorado analizando su rol en el diseño de la formación y la comunicación con los estudiantes; hablan de la colaboración, analizando cómo diseñar actividades colaborativas y señalando sus ventajas y límites; describen los diferentes recursos de aprendizaje que podemos disponer en el diseño de los cursos y, por último, acompañan nuestra mirada hacia el futuro próximo analizando las tendencias y los retos a los que debemos hacer frente para construir el e-learning del siglo XXI.

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Open Innovation is a relatively new concept which involves a change of paradigm in the R+D+i processes of companies whose aim is to create new technologies or new processes. If to this change, we add the need for innovation in the new green and sustainability economy, and we set out to create a collaborative platform with a learning space where this can happen, we will be facing an overwhelming challenge which requires the application of intelligent programming technologies and languages at the service of education.The aim of the Green IDI (Green Open Innovation) ¿ Economic development and job creation vector in SMEs, based on the environment and sustainability project is to create a platform where companies and individual researchers can perform open innovation processes in the field of sustainability and the environment.The Green IDI (Green Open Innovation) project is funded under the program INNPACTO by the Ministry of Science and Innovation of Spain and is being developed through a consortium formed by the following institutions: GRUPO ICA; COMPARTIA; GRUPO INTERCOM; CETAQUA and the Instituto de Investigación en Inteligencia Artificial (IIIA) from Consejo Superior de Investigaciones Científicas (CSIC). Also the consortium include FUNDACIÓ PRIVADA BARCELONA DIGITAL; PIMEC and UNIVERSITAT OBERTA DE CATALUNYA (UOC).Sustainability and positive action for the environment are considered the principle vector of economic development for companies. As Nicolás Scoli says (2007) ¿in short, preventing unnecessary consumption and the efficient consumption of resources means producing greater wealth with less. Both effects lead to reduced pollution linked to production and consumption¿.The Spanish Sustainable Development Strategy (EEDS) plan defends consumption and sustainable production linked to social and economic development by adhering to the commitment not to endanger ecosystems and abolishing the idea that economic growth is directly proportional to the deterioration of the environment.Uniting the Open Innovation and New Green Economy concepts leads to the "Green Open Innovation¿ Platform creation project.This article analyses the concept of open innovation and defines the importance of the new green and sustainable economy. Lastly, it proposes the creation of eLab. The eLab is defined as an Open Green Innovation Platform personal and collaborative education space which is fed by the interactions of users and which enables innovation processes based on new green economy concepts to be carried out.The creation of a personal learning environment such as eLab on the Green Open Innovation Platform meets the need to offer a collaborative space where platform users can improve their skills regarding the environment and sustainability based on collaborative synergies through Information and Communication Technologies.

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A descriptive, exploratory study is presented based on a questionnaire regarding the following aspects of reflective learning: a) self-knowledge, b) relating experience to knowledge, c) self-reflection, and d) self-regulation of the learning processes. The questionnaire was completed by students studying four different degree courses (social education, environmental sciences, nursing, and psychology). Specifically, the objectives of a self-reported reflective learning questionnaire are: i) to determine students’ appraisal of reflective learning methodology with regard to their reflective learning processes, ii) to obtain evidence of the main difficulties encountered by students in integrating reflective learning methodologies into their reflective learning processes, and iii) to collect students’ perceptions regarding the main contributions of the reflective learning processes they have experienced

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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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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

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This study investigates the transformation of practical teaching in a Catalan school, connected to the design, implementation and development of project-based learning, and focusing on dialogic learning to investigate its limits and possibilities. Qualitative and design-based research (DBR) methods are applied. These methods are based on empirical educational research with the theory-driven of learning environments. DBR is proposed and applied using practical guidance for the teachers of the school. It can be associated with the current proposals for Embedding Social Sciences and Humanities in the Horizon 2020 Societal Challenges. This position statement defends the social sciences and the humanities as the most fundamental and important ideas to face all societal challenges. The results of this study show that before the training process, teachers apply dialogic learning in specific moments (for example, when they speak about the weekend); however, during the process and after the process, they work systematically with dialogic learning through the PEPT: they start and finish every activity with a individual and group reflection about their own processes, favouring motivation, reasoning and the implication of all the participants. These results prove that progressive transformations of teaching practice benefit cooperative work in class

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Feedback-related negativity (FRN) is an ERP component that distinguishes positive from negative feedback. FRN has been hypothesized to be the product of an error signal that may be used to adjust future behavior. In addition, associative learning models assume that the trial-to-trial learning of cueoutcome mappings involves the minimization of an error term. This study evaluated whether FRN is a possible electrophysiological correlate of this error term in a predictive learning task where human subjects were asked to learn different cueoutcome relationships. Specifically, we evaluated the sensitivity of the FRN to the course of learning when different stimuli interact or compete to become a predictor of certain outcomes. Importantly, some of these cues were blocked by more informative or predictive cues (i.e., the blocking effect). Interestingly, the present results show that both learning and blocking affect the amplitude of the FRN component. Furthermore, independent analyses of positive and negative feedback event-related signals showed that the learning effect was restricted to the ERP component elicited by positive feedback. The blocking test showed differences in the FRN magnitude between a predictive and a blocked cue. Overall, the present results show that ERPs that are related to feedback processing correspond to the main predictions of associative learning models. ■

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An assortment of human behaviors is thought to be driven by rewards including reinforcement learning, novelty processing, learning, decision making, economic choice, incentive motivation, and addiction. In each case the ventral tegmental area/ventral striatum (nucleus accumbens) (VTAVS) system has been implicated as a key structure by functional imaging studies, mostly on the basis of standard, univariate analyses. Here we propose that standard functional magnetic resonance imaging analysis needs to be complemented by methods that take into account the differential connectivity of the VTAVS system in the different behavioral contexts in order to describe reward based processes more appropriately. We fi rst consider the wider network for reward processing as it emerged from animal experimentation. Subsequently, an example for a method to assess functional connectivity is given. Finally, we illustrate the usefulness of such analyses by examples regarding reward valuation, reward expectation and the role of reward in addiction.