783 resultados para Conceptions Of Learning


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Ocean acidification has the potential to cause dramatic changes in marine ecosystems. Larval damselfish exposed to concentrations of CO2 predicted to occur in the mid- to late-century show maladaptive responses to predator cues. However, there is considerable variation both within and between species in CO2 effects, whereby some individuals are unaffected at particular CO2 concentrations while others show maladaptive responses to predator odour. Our goal was to test whether learning via chemical or visual information would be impaired by ocean acidification and ultimately, whether learning can mitigate the effects of ocean acidification by restoring the appropriate responses of prey to predators. Using two highly efficient and widespread mechanisms for predator learning, we compared the behaviour of pre-settlement damselfish Pomacentrus amboinensis that were exposed to 440 µatm CO2 (current day levels) or 850 µatm CO2, a concentration predicted to occur in the ocean before the end of this century. We found that, regardless of the method of learning, damselfish exposed to elevated CO2 failed to learn to respond appropriately to a common predator, the dottyback, Pseudochromis fuscus. To determine whether the lack of response was due to a failure in learning or rather a short-term shift in trade-offs preventing the fish from displaying overt antipredator responses, we conditioned 440 or 700 µatm-CO2 fish to learn to recognize a dottyback as a predator using injured conspecific cues, as in Experiment 1. When tested one day post-conditioning, CO2 exposed fish failed to respond to predator odour. When tested 5 days post-conditioning, CO2 exposed fish still failed to show an antipredator response to the dottyback odour, despite the fact that both control and CO2-treated fish responded to a general risk cue (injured conspecific cues). These results indicate that exposure to CO2 may alter the cognitive ability of juvenile fish and render learning ineffective.

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The objective of this paper is to address the methodological process of a teaching strategy for training project management complexity in postgraduate programs. The proposal is made up of different methods —intuitive, comparative, deductive, case study, problem-solving Project-Based Learning— and different activities inside and outside the classroom. This integration of methods motivated the current use of the concept oflearning strategy”. The strategy has two phases: firstly, the integration of the competences —technical, behavioral and contextual—in real projects; and secondly, the learning activity was oriented in upper level of knowledge, the evaluating the complexity for projects management in real situations. Both the competences in the learning strategy and the Project Complexity Evaluation are based on the ICB of IPMA. The learning strategy is applied in an international Postgraduate Program —Erasmus Mundus Master of Science— with the participation of five Universities of the European Union. This master program is fruit of a cooperative experience from one Educative Innovation Group of the UPM -GIE-Project-, two Research Groups of the UPM and the collaboration with other external agents to the university. Some reflections on the experience and the main success factors in the learning strategy were presented in the paper

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The objective of this paper is to address the methodological process of a teaching strategy for training project management complexity in postgraduate programs. The proposal is made up of different methods —intuitive, comparative, deductive, case study, problem-solving Project-Based Learning— and different activities inside and outside the classroom. This integration of methods motivated the current use of the concept oflearning strategy‖. The strategy has two phases: firstly, the integration of the competences —technical, behavioral and contextual—in real projects; and secondly, the learning activity was oriented in upper level of knowledge, the evaluating the complexity for projects management in real situations. Both the competences in the learning strategy and the Project Complexity Evaluation are based on the ICB of IPMA. The learning strategy is applied in an international Postgraduate Program —Erasmus Mundus Master of Science— with the participation of five Universities of the European Union. This master program is fruit of a cooperative experience from one Educative Innovation Group of the UPM -GIE-Project-, two Research Groups of the UPM and the collaboration with other external agents to the university. Some reflections on the experience and the main success factors in the learning strategy were presented in the paper.

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Web-based education or „e-learning‟ has become a critical component in higher education for the last decade, replacing other distance learning methods, such as traditional computer training or correspondence learning. The number of university students who take on-line courses is continuously increasing all over the world. In Spain, nearly a 90% of the universities have an institutional e-learning platform and over 60% of the traditional on-site courses use this technology as a supplement to the traditional face-to-face classes. This new form of learning allows the disappearance of geographical barriers and enables students to schedule their own learning process, among some other advantages. On-line education is developed through specific software called „e-learning platform‟ or „virtual learning environment‟ (VLE). A considerable number of web-based tools to deliver distance courses are currently available. Open source software packages such as Moodle, Sakai, dotLRN or Dokeos are the most commonly used in the virtual campuses of Spanish universities. This paper analyzes the possibilities that virtual learning environments provide university teachers and learners and offers a technical comparison among some of the most popular e-learning learning platforms.

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Analysis of learning data (learning analytics) is a new research field with high growth potential. The main objective of Learning analytics is the analysis of data (interactions being the basic data unit) generated in virtual learning environments, in order to maximize the outcomes of the learning process; however, a consensus has not been reached yet on which interactions must be measured and what is their influence on learning outcomes. This research is grounded on the study of e-learning interaction typologies and their relationship with students? academic performance, by means of a comparative study between different interaction typologies (based on the agents involved, frequency of use and participation mode). The main conclusions are a) that classifications based on agents offer a better explanation of academic performance; and b) that each of the three typologies are able to explain academic performance in terms of some of their components (student-teacher and student-student interactions, evaluating students interactions and active interactions, respectively), with the other components being nonrelevant.

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Probabilistic graphical models are a huge research field in artificial intelligence nowadays. The scope of this work is the study of directed graphical models for the representation of discrete distributions. Two of the main research topics related to this area focus on performing inference over graphical models and on learning graphical models from data. Traditionally, the inference process and the learning process have been treated separately, but given that the learned models structure marks the inference complexity, this kind of strategies will sometimes produce very inefficient models. With the purpose of learning thinner models, in this master thesis we propose a new model for the representation of network polynomials, which we call polynomial trees. Polynomial trees are a complementary representation for Bayesian networks that allows an efficient evaluation of the inference complexity and provides a framework for exact inference. We also propose a set of methods for the incremental compilation of polynomial trees and an algorithm for learning polynomial trees from data using a greedy score+search method that includes the inference complexity as a penalization in the scoring function.

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La adquisición de la competencia grupal es algo básico en la docencia universitaria. Esta tarea va a suponer evaluar diferentes factores en un número elevado de alumnos, lo que puede supone gran complejidad y un esfuerzo elevado. De cara a evitar este esfuerzo se puede pensar en emplear los registros de la interacción de los usuarios almacenados en las plataformas de aprendizaje. Para ello el presente trabajo se basa en el desarrollo de un sistema de Learning Analytics que es utilizado como herramienta para analizar las evidencias individuales de los distintos miembros de un equipo de trabajo. El trabajo desarrolla un modelo teórico apoyado en la herramienta, que permite relacionar las evidencias observadas de forma empírica para cada alumno, con indicadores obtenidos tanto de la acción individual como cooperativo de los miembros de un equipo realizadas a través de los foros de trabajo. Abstract — The development of the group work competence is something basic in university teaching. It should be evaluated, but this means to analyze different issues about the participation of a high number of students which is very complex and implies a lot of effort. In order to facilitate this evaluation it is possible to analyze the logs of students’ interaction in Learning Management Systems. The present work describes the development of a Learning Analytics system that analyzes the interaction of each of the members of working group. This tool is supported by a theoretical model, which allows establishing links between the empirical evidences of each student and the indicators of their action in working forums.

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There are significant levels of concern about the relevance and the difficulty of learning some issues on Strength of Materials and Structural Analysis. Most students of Continuum Mechanics and Structural Analysis in Civil Engineering usually point out some key learning aspects as especially difficult for acquiring specific skills. These key concepts entail comprehension difficulties but ease access and applicability to structural analysis in more advanced subjects. Likewise, some elusive but basic structural concepts, such as flexibility, stiffness or influence lines, are paramount for developing further skills required for advanced structural design: tall buildings, arch-type structures as well as bridges. As new curricular itineraries are currently being implemented, it appears appropriate to devise a repository of interactive web-based applications for training in those basic concepts. That will hopefully train the student to understand the complexity of such concepts, to develop intuitive knowledge on actual structural response and to improve their preparation for exams. In this work, a web-based learning assistant system for influence lines on continuous beams is presented. It consists of a collection of interactive user-friendly applications accessible via Web. It is performed in both Spanish and English languages. Rather than a “black box” system, the procedure involves open interaction with the student, who can simulate and virtually envisage the structural response. Thus, the student is enabled to set the geometric, topologic and mechanic layout of a continuous beam and to change or shift the loading and the support conditions. Simultaneously, the changes in the beam response prompt on the screen, so that the effects of the several issues involved in structural analysis become apparent. The system is performed through a set of web pages which encompasses interactive exercises and problems, written in JavaScript under JQuery and DyGraphs frameworks, given that their efficiency and graphic capabilities are renowned. Students can freely boost their self-study on this subject in order to face their exams more confidently. Besides, this collection is expected to be added to the "Virtual Lab of Continuum Mechanics" of the UPM, launched in 2013 (http://serviciosgate.upm.es/laboratoriosvirtuales/laboratorios/medios-continuos-en-construcci%C3%B3n)

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Early experiences such as prenatal stress significantly influence the development of the brain and the organization of behavior. In particular, prenatal stress impairs memory processes but the mechanism for this effect is not known. Hippocampal granule neurons are generated throughout life and are involved in hippocampal-dependent learning. Here, we report that prenatal stress in rats induced lifespan reduction of neurogenesis in the dentate gyrus and produced impairment in hippocampal-related spatial tasks. Prenatal stress blocked the increase of learning-induced neurogenesis. These data strengthen pathophysiological hypotheses that propose an early neurodevelopmental origin for psychopathological vulnerabilities in aging.

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The biological bases of learning and memory are being revealed today with a wide array of molecular approaches, most of which entail the analysis of dysfunction produced by gene disruptions. This perspective derives both from early “genetic dissections” of learning in mutant Drosophila by Seymour Benzer and colleagues and from earlier behavior-genetic analyses of learning and in Diptera by Jerry Hirsch and coworkers. Three quantitative-genetic insights derived from these latter studies serve as guiding principles for the former. First, interacting polygenes underlie complex traits. Consequently, learning/memory defects associated with single-gene mutants can be quantified accurately only in equilibrated, heterogeneous genetic backgrounds. Second, complex behavioral responses will be composed of genetically distinct functional components. Thus, genetic dissection of complex traits into specific biobehavioral properties is likely. Finally, disruptions of genes involved with learning/memory are likely to have pleiotropic effects. As a result, task-relevant sensorimotor responses required for normal learning must be assessed carefully to interpret performance in learning/memory experiments. In addition, more specific conclusions will be obtained from reverse-genetic experiments, in which gene disruptions are restricted in time and/or space.

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In the last few years, one of the lines of research of great interest in the field of emotional intelligence (EI) has been the analysis of the role of emotions in the educational context and, in particular, their influence on learning strategies. The aims of this study are to identify the existence of different EI profiles and to determine possible statistically significant differences in learning strategies between the obtained profiles. The study involved 1253 Chilean school students from 14 to 18 years (M = 15.10, SD = 1.30), who completed the Trait Meta-Mood Scale-24 (TMMS-24) and the Inventory of Learning and Study Strategies—High School version (LASSI-HS). Cluster analysis identified four EI profiles: a group of adolescents with a high EI profile, a group with predominance of low emotional attention and high repair skills, a group with high scores on attention and low scores on clarity and repair, and a final group of adolescents with low EI. Also, students in groups with high overall scores in EI and low attention and high repair emotional obtained higher scores on the different learning strategies; however, the effect size analysis showed that these differences had no empirical relevance.

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Some would argue that there is a need for the traditional lecture format to be rethought in favour of a more active approach. However, this must form part of a bipartite strategy, considered in conjunction with the layout of any new space to facilitate alternative learning and teaching methods. With this in mind, this paper begins to examine the impact of the learning environment on the student learning experience, specifically focusing on students studying on the Architectural Technology and Management programme at Ulster University. The aim of this study is two-fold: to increase understanding of the impact of learning space layout, by taking a student centered approach; and to gain an appreciation of how technology can impact upon the learning space. The study forms part of a wider project being undertaken at Ulster University known as the Learning Landscape Transition Project, exploring the relationship between learning, teaching and space layout. Data collection was both qualitative and quantitative, with use of a case study supported by a questionnaire based on attitudinal scaling. A focus group was also used to further analyse the key trends resulting from the questionnaire. The initial results suggest that the learning environment, and the technology within it, can not only play an important part in the overall learning experience of the student, but also assist with preparation for the working environment to be experienced in professional life.

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This report offers a comparative policy study on adult learning within the scope of complementary research conducted by Beblavý et al. (2013) on how people upgrade their skills during their adult lifetimes. To achieve our objectives, we identified regulatory policies and financial support in 11 countries for two main categories of learning: formal higher education and employer-based training. Drawing upon the results of the country reports carried out by our partners in the MoPAct project, we found that in none of the countries examined is there an ‘older student’ policy. In most cases grants and financial support are awarded only up until a certain age. In all of the countries studied, standard undergraduate and post-graduate studies are available for part-time students. The distribution of full-time students and part-time students in tertiary education varies from one country to another as well as from one age group to another. The participation in full-time tertiary education programmes decreases with the age of students. In Lithuania, Latvia, Poland and the UK, there are no mandatory policies to ensure employer-based training. However, in Belgium, Czech Republic, Denmark, Estonia, Germany, Italy, the Netherlands and Spain, employer-based training is more clearly regulated and the employers might have obligations to provide training for their staff. Taking into consideration Beblavý et al. (2013), we observe that comparative differences across countries can be related to policy differences only in some cases. The policy framework seems to impact more the employer-based training than the educational attainment (upgrade of ISCED level). In Denmark, the Netherlands, Latvia, Lithuania, Czech Republic and Poland, we find a perfect match between policy outcomes and the results of Beblavý et al. (2013) related to employer-based training. This is not the case in the United Kingdom, where the two aspects observed are not correlated.

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Thesis (Ph.D.)--University of Washington, 2016-06

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Thesis (Ph.D.)--University of Washington, 2016-05