781 resultados para Open and Distance Learning


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The present study aims to investigate the constructs of Technological Readiness Index (TRI) and the Expectancy Disconfirmation Theory (EDT) as determinants of satisfaction and continuance intention use in e-learning services. Is proposed a theoretical model that seeks to measure the phenomenon suited to the needs of public organizations that offer distance learning course with the use of virtual platforms for employees. The research was conducted from a quantitative analytical approach, via online survey in a sample of 343 employees of 2 public organizations in RN who have had e-learning experience. The strategy of data analysis used multivariate analysis techniques, including structural equation modeling (SEM), operationalized by AMOS© software. The results showed that quality, quality disconfirmation, value and value disconfirmation positively impact on satisfaction, as well as disconfirmation usability, innovativeness and optimism. Likewise, satisfaction proved to be decisive for the purpose of continuance intention use. In addition, technological readiness and performance are strongly related. Based on the structural model found by the study, public organizations can implement e-learning services for employees focusing on improving learning and improving skills practiced in the organizational environment

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The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).

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A educação a distância apoiada pelos meios de comunicação digital ampliou as possibilidades de interação, flexibilizando o processo de mediação pedagógica no tempo e no espaço. Nessa perspectiva, a educação profissional democratizou seu acesso, na qual os conhecimentos de nível técnico são customizados em um Ambiente Virtual de Aprendizagem (AVA) para serem mediados a distância. Esta tese, apresentada na forma de artigos, problematiza o processo de mediação pedagógica realizado pelo professor tutor virtual na Rede e-Tec Brasil do Instituto Federal de Educação, Ciência e Tecnologia Sul-rio-grandense (IFSul) Campus Visconde da Graça (CAVG). Nesse modelo de ensino, o professor tutor virtual é contratado para atuar, pelo período de dois anos, em todas as disciplinas curriculares de um curso técnico. Se, por um lado, isso permite-lhe conhecer a realidade de seus alunos; por outro, exige-lhe um esforço pedagógico de apropriação e mediação dos conteúdos específicos nas diversas disciplinas que integram os currículos de cada curso. A pesquisa buscou conhecer como o professor tutor virtual apropria-se dos conhecimentos específicos nos cursos técnicos para mediá-los pedagogicamente com os alunos. Apresentamos, como hipótese explicativa neste estudo, que é na convivência com o professor pesquisador que o professor tutor virtual encontra a possibilidade de se apropriar dos conhecimentos curriculares para poder mediá-los pedagogicamente com os alunos. Para sustentar teoricamente nossas proposições na experiência vivida, estabelecemos uma rede de conversação com os autores Humberto Maturana, Pierre Lévy, Lee Shulman e Maurice Tardif, por meio dos conceitos: cultura em redes de conversação; inteligência coletiva; conhecimento pedagógico do conteúdo; e formação profissional docente. Como procedimento metodológico, encontramos na técnica do Discurso do Sujeito Coletivo (DSC), de Lefèvre e Lefèvre, uma estratégia de abordagem qualitativa para analisar as recorrências encontradas nos discursos dos professores tutores virtuais. O estudo aponta que uma rede de conversação recursiva entre o professor pesquisador e o professor tutor virtual possibilita a apropriação de conhecimentos técnicos e específicos necessários ao processo de mediação pedagógica com os estudantes. Essa convivência, no caminho da constituição de um coletivo inteligente, favorece o trabalho colaborativo no ambiente da tutoria, contribuindo para profissionalizar o processo de mediação pedagógica na educação profissional a distância do IFSul CAVG. Supported by digital media, distance learning has increased the possibilities of interaction, easing the process of pedagogical mediation in time and space. From this perspective, the access to professional education has been democratized: technical knowledge is customized in a Learning Managing System and later delivered by means of mediated distance education courses. Structured in a sequence of articles, this dissertation addresses the problem of the pedagogical mediation process performed by on-line tutor teachers at Rede e-Tec Brasil of the Instituto Federal Sul- rio-grandense (IF-Sul), Campus Visconde da Graça (CAVG). This model of education establishes that on-line tutor teachers are hired to work with all the curriculum courses of a technical program for two years. If, on the hand, it allows these teachers to know the reality of their students well, on the other hand it demands them a pedagogical effort of appropriation and mediation of the specific contents guiding the various courses that comprise the curriculum of each program. This research aimed to find out how on-line tutor teachers appropriate expertise from technical programs to mediate it with their students in a pedagogical way. The explanatory hypothesis given is that by working together and sharing experience with the teacher/researcher, on-line tutor teachers will be able to appropriate of curricular knowledge and pedagogically mediate it with their students afterwards. To support our theoretical propositions, a network of conversation was established with authors like Humberto Maturana, Pierre Lévy, Lee Shulman, and Maurice Tardif through the concepts of culture in networks of conversation, collective intelligence, pedagogical content knowledge, and teacher training. As a methodological procedure, the technique of the Collective Subject Discourse (CSD), by Lefèvre and Lefèvre, was found to offer a strategy of qualitative approach to analyze the recurrences seen in the speech of on-line tutor teachers. The study shows that a recursive network of conversation between the teacher/researcher and the on-line tutor teacher enables the appropriation of specific and technical knowledge required for the process of pedagogical mediation with students. The experience of sharing a consensual professional relationship, in which one respects and accepts the other as a way of establishing a collective intelligence, encourages collaborative work in the tutoring environment, helping professionalize the process of pedagogical mediation in distance professional education at IFSul CAVG.

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The use of Massive Open Online Courses (MOOCs) is being increasingly equated as a viable option by several educational shareholders in the scope of many scientific areas; nevertheless, research as to its potentialities in terms of digital (and consequently social) inclusion is still sparse and somehow atomised. Thus, this paper aims at putting forward the results of a thorough literature review focussed on the studies that bring together the concepts of MOOC and digital inclusion, published between January 2014 and January 2015. Thus, the main goal was to find out if there is evidence that MOOCS can be an important means for embracing digital inclusion, in particular, by promoting the development of soft skills (e.g., digital skills, communication skills, interaction skills). First and because the concept is becoming more and more polysemic (due to its manifold uses, theoretical frameworks, and application contexts), the MOOC’s main facets are depicted, considering its derivatives (e.g., cMOOC and xMOOC). Moreover, some critical aspects that stand out from the content analysis of the results of the literature review are also highlighted, namely as to: accessibility, employability and lifelong learning promoted through MOOC use. In general, results suggest that there is still a long way to go for MOOCs to fully address the digital inclusion challenge.

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Certain environments can inhibit learning and stifle enthusiasm, while others enhance learning or stimulate curiosity. Furthermore, in a world where technological change is accelerating we could ask how might architecture connect resource abundant and resource scarce innovation environments? Innovation environments developed out of necessity within urban villages and those developed with high intention and expectation within more institutionalized settings share a framework of opportunity for addressing change through learning and education. This thesis investigates formal and informal learning environments and how architecture can stimulate curiosity, enrich learning, create common ground, and expand access to education. The reason for this thesis exploration is to better understand how architects might design inclusive environments that bring people together to build sustainable infrastructure encouraging innovation and adaptation to change for years to come. The context of this thesis is largely based on Colin McFarlane’s theory that the “city is an assemblage for learning” The socio-spatial perspective in urbanism, considers how built infrastructure and society interact. Through the urban realm, inhabitants learn to negotiate people, space, politics, and resources affecting their daily lives. The city is therefore a dynamic field of emergent possibility. This thesis uses the city as a lens through which the boundaries between informal and formal logics as well as the public and private might be blurred. Through analytical processes I have examined the environmental devices and assemblage of factors that consistently provide conditions through which learning may thrive. These parameters that make a creative space significant can help suggest the design of common ground environments through which innovation is catalyzed.

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This quantitative study examines the impact of teacher practices on student achievement in classrooms where the English is Fun Interactive Radio Instruction (IRI) programs were being used. A contemporary IRI design using a dual-audience approach, the English is Fun IRI programs delivered daily English language instruction to students in grades 1 and 2 in Delhi and Rajasthan through 120 30-minute programs via broadcast radio (the first audience) while modeling pedagogical techniques and behaviors for their teachers (the second audience). Few studies have examined how the dual-audience approach influences student learning. Using existing data from 32 teachers and 696 students, this study utilizes a multivariate multilevel model to examine the role of the primary expectations for teachers (e.g., setting up the IRI classroom, following instructions from the radio characters and ensuring students are participating) and the role of secondary expectations for teachers (e.g., modeling pedagogies and facilitating learning beyond the instructions) in promoting students’ learning in English listening skills, knowledge of vocabulary and use of sentences. The study finds that teacher practice on both sets of expectations mattered, but that practice in the secondary expectations mattered more. As expected, students made the smallest gains in the most difficult linguistic task (sentence use). The extent to which teachers satisfied the primary and secondary expectations was associated with gains in all three skills – confirming the relationship between students’ English proficiency and teacher practice in a dual-audience program. When it came to gains in students’ scores in sentence use, a teacher whose focus was greater on primary expectations had a negative effect on student performance in both states. In all, teacher practice clearly mattered but not in the same way for all three skills. An optimal scenario for teacher practice is presented in which gains in all three skills are maximized. These findings have important implications for the way the classroom teacher is cast in IRI programs that utilize a dual-audience approach and in the way IRI programs are contracted insofar as the role of the teacher in instruction is minimized and access is limited to instructional support from the IRI lessons alone.

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To date, adult educational research has had a limited focus on lesbian, gay, bisexual and transgendered (LGBT) adults and the learning processes in which they engage across the life course. Adopting a biographical and life history methodology, this study aimed to critically explore the potentially distinctive nature and impact of how, when and where LGBT adults learn to construct their identities over their lives. In-depth, semi-structured interviews, dialogue and discussion with LGBT individuals and groups provided rich narratives that reflect shifting, diverse and multiple ways of identifying and living as LGBT. Participants engage in learning in unique ways that play a significant role in the construction and expression of such identities, that in turn influence how, when and where learning happens. Framed largely by complex heteronormative forces, learning can have a negative, distortive impact that deeply troubles any balanced, positive sense of being LGBT, leading to self- censoring, alienation and in some cases, hopelessness. However, learning is also more positively experiential, critically reflective, inventive and queer in nature. This can transform how participants understand their sexual identities and the lifewide spaces in which they learn, engendering agency and resilience. Intersectional perspectives reveal learning that participants struggle with, but can reconcile the disjuncture between evolving LGBT and other myriad identities as parents, Christians, teachers, nurses, academics, activists and retirees. The study’s main contributions lie in three areas. A focus on LGBT experience can contribute to the creation of new opportunities to develop intergenerational learning processes. The study also extends the possibilities for greater criticality in older adult education theory, research and practice, based on the continued, rich learning in which participants engage post-work and in later life. Combined with this, there is scope to further explore the nature of ‘life-deep learning’ for other societal groups, brought by combined religious, moral, ideological and social learning that guides action, beliefs, values, and expression of identity. The LGBT adults in this study demonstrate engagement in distinct forms of life-deep learning to navigate social and moral opprobrium. From this they gain hope, self-respect, empathy with others, and deeper self-knowledge.

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The author carries out a pedagogical reflection on how the technology driven distance learning repeatedly neglects the scientific achievements of Second Language Acquisition and Language Pedagogy. Seeing communicative competence as a major goal of a language classroom, she presents the main challenges that the communicative approach poses to distance learning. To this end, a general distance learning theory by Moore is adapted to the needs of language education, through a distinction between three aspects of learner interaction – with the teacher, with other learners and with content. In this three-dimensional paradigm the learner is seen as the main actor of the process, the teacher as a facilitator, the text as a main source of communicative data and the learner autonomy as the fundament of the process.

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Natural language processing has achieved great success in a wide range of ap- plications, producing both commercial language services and open-source language tools. However, most methods take a static or batch approach, assuming that the model has all information it needs and makes a one-time prediction. In this disser- tation, we study dynamic problems where the input comes in a sequence instead of all at once, and the output must be produced while the input is arriving. In these problems, predictions are often made based only on partial information. We see this dynamic setting in many real-time, interactive applications. These problems usually involve a trade-off between the amount of input received (cost) and the quality of the output prediction (accuracy). Therefore, the evaluation considers both objectives (e.g., plotting a Pareto curve). Our goal is to develop a formal understanding of sequential prediction and decision-making problems in natural language processing and to propose efficient solutions. Toward this end, we present meta-algorithms that take an existent batch model and produce a dynamic model to handle sequential inputs and outputs. Webuild our framework upon theories of Markov Decision Process (MDP), which allows learning to trade off competing objectives in a principled way. The main machine learning techniques we use are from imitation learning and reinforcement learning, and we advance current techniques to tackle problems arising in our settings. We evaluate our algorithm on a variety of applications, including dependency parsing, machine translation, and question answering. We show that our approach achieves a better cost-accuracy trade-off than the batch approach and heuristic-based decision- making approaches. We first propose a general framework for cost-sensitive prediction, where dif- ferent parts of the input come at different costs. We formulate a decision-making process that selects pieces of the input sequentially, and the selection is adaptive to each instance. Our approach is evaluated on both standard classification tasks and a structured prediction task (dependency parsing). We show that it achieves similar prediction quality to methods that use all input, while inducing a much smaller cost. Next, we extend the framework to problems where the input is revealed incremen- tally in a fixed order. We study two applications: simultaneous machine translation and quiz bowl (incremental text classification). We discuss challenges in this set- ting and show that adding domain knowledge eases the decision-making problem. A central theme throughout the chapters is an MDP formulation of a challenging problem with sequential input/output and trade-off decisions, accompanied by a learning algorithm that solves the MDP.

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The present study aims to investigate the constructs of Technological Readiness Index (TRI) and the Expectancy Disconfirmation Theory (EDT) as determinants of satisfaction and continuance intention use in e-learning services. Is proposed a theoretical model that seeks to measure the phenomenon suited to the needs of public organizations that offer distance learning course with the use of virtual platforms for employees. The research was conducted from a quantitative analytical approach, via online survey in a sample of 343 employees of 2 public organizations in RN who have had e-learning experience. The strategy of data analysis used multivariate analysis techniques, including structural equation modeling (SEM), operationalized by AMOS© software. The results showed that quality, quality disconfirmation, value and value disconfirmation positively impact on satisfaction, as well as disconfirmation usability, innovativeness and optimism. Likewise, satisfaction proved to be decisive for the purpose of continuance intention use. In addition, technological readiness and performance are strongly related. Based on the structural model found by the study, public organizations can implement e-learning services for employees focusing on improving learning and improving skills practiced in the organizational environment

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Educação, Programa de Pós-Graduação em Educação, 2016.

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Dissertação (mestrado)—Universidade de Brasília, Instituto de Letras, Departamento de Línguas Estrangeiras e Tradução, Programa de Pós-Graduação em Linguística Aplicada, 2016.

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Early human development offers a unique perspective in investigating the potential cognitive and social implications of action and perception. Specifically, during infancy, action production and action perception undergo foundational developments. One essential component to examine developments in action processing is the analysis of others’ actions as meaningful and goal-directed. Little research, however, has examined the underlying neural systems that may be associated with emerging action and perception abilities, and infants’ learning of goal-directed actions. The current study examines the mu rhythm—a brain oscillation found in the electroencephalogram (EEG)—that has been associated with action and perception. Specifically, the present work investigates whether the mu signal is related to 9-month-olds’ learning of a novel goal-directed means-end task. The findings of this study demonstrate a relation between variations in mu rhythm activity and infants’ ability to learn a novel goal-directed means-end action task (compared to a visual pattern learning task used as a comparison task). Additionally, we examined the relations between standardized assessments of early motor competence, infants’ ability to learn a novel goal-directed task, and mu rhythm activity. We found that: 1a) mu rhythm activity during observation of a grasp uniquely predicted infants’ learning on the cane training task, 1b) mu rhythm activity during observation and execution of a grasp did not uniquely predict infants’ learning on the visual pattern learning task (comparison learning task), 2) infants’ motor competence did not predict infants’ learning on the cane training task, 3) mu rhythm activity during observation and execution was not related to infants’ measure of motor competence, and 4) mu rhythm activity did not predict infants’ learning on the cane task above and beyond infants’ motor competence. The results from this study demonstrate that mu rhythm activity is a sensitive measure to detect individual differences in infants’ action and perception abilities, specifically their learning of a novel goal-directed action.

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Tese (doutorado)—Universidade de Brasília, Faculdade de Educação, Programa de Pós-graduação em Educação, 2015.

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The higher education system has a critical role to play in educating environmentally aware and participant citizens about global climate change. Yet, few studies have focused on higher education students’ knowledge and attitudes about this issue. This study aims to contribute to a comprehensive understanding of views and attitudes about climate change issues, across the postgraduate student population in three universities—the on Campus University of Porto and University of Coimbra, and the distance learning Universidade Aberta, Portugal. We surveyed university students and graduates from three master programs in environmental sciences targeting their knowledge, attitudes and behaviour on climate change issues, and their views of the role that their master degree had on it. A majority of the respondents believed that climate change is factual, and is largely human-induced; and a majority expressed concerns about climate change. Still, the surveyed students hold some misconceptions about basic causes and consequences of climate change. Further research is necessary to comprehend the university postgraduate students’ population, so that curricula programs can be adapted to grant consensus on scientific knowledge about climate change, and an active engagement of the graduate citizens, as part of the solution for climate change problems.