838 resultados para Active learning methods
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Bayesian methods offer a flexible and convenient probabilistic learning framework to extract interpretable knowledge from complex and structured data. Such methods can characterize dependencies among multiple levels of hidden variables and share statistical strength across heterogeneous sources. In the first part of this dissertation, we develop two dependent variational inference methods for full posterior approximation in non-conjugate Bayesian models through hierarchical mixture- and copula-based variational proposals, respectively. The proposed methods move beyond the widely used factorized approximation to the posterior and provide generic applicability to a broad class of probabilistic models with minimal model-specific derivations. In the second part of this dissertation, we design probabilistic graphical models to accommodate multimodal data, describe dynamical behaviors and account for task heterogeneity. In particular, the sparse latent factor model is able to reveal common low-dimensional structures from high-dimensional data. We demonstrate the effectiveness of the proposed statistical learning methods on both synthetic and real-world data.
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The hypothesis that the same educational objective, raised as cooperative or collaborative learning in university teaching does not affect students’ perceptions of the learning model, leads this study. It analyses the reflections of two students groups of engineering that shared the same educational goals implemented through two different methodological active learning strategies: Simulation as cooperative learning strategy and Problem-based Learning as a collaborative one. The different number of participants per group (eighty-five and sixty-five, respectively) as well as the use of two active learning strategies, either collaborative or cooperative, did not show differences in the results from a qualitative perspective.
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Compulsory education laws oblige primary and secondary schools to give each pupil positive encouragement in, for example, social, emotional, cognitive, creative, and ethical respects. This is a fairly smooth process for most pupils, but it is not as easy to achieve with others. A pattern of pupil, home or family, and school variables turns out to be responsible for a long-term process that may lead to a pupil’s dropping out of education. A systemic approach will do much to introduce more clarity into the diagnosis, potential reduction and possible prevention of some persistent educational problems that express themselves in related phenomena, for example low school motivation and achievement; forced underachievement of high ability pupils; concentration of bullying and violent behaviour in and around some types of classes and schools; and drop-out percentages that are relatively constant across time. Such problems have a negative effect on pupils, teachers, parents, schools, and society alike. In this address, I would therefore like to clarify some of the systemic causes and processes that we have identified between specific educational and pupil characteristics. Both theory and practice can assist in developing, implementing, and checking better learning methods and coaching procedures, particularly for pupils at risk. This development approach will take time and require co-ordination, but it will result in much better processes and outcomes than we are used to. First, I will diagnose some systemic aspects of education that do not seem to optimise the learning processes and school careers of some types of pupils in particular. Second, I will specify cognitive, social, motivational, and self-regulative aspects of learning tasks and relate corresponding learning processes to relevant instructional and wider educational contexts. I will elaborate these theoretical notions into an educational design with systemic instructional guidelines and multilevel procedures that may improve learning processes for different types of pupils. Internet-based Information and Communication Technology, or ICT, also plays a major role here. Third, I will report on concrete developments made in prototype research and trials. The development process concerns ICT-based differentiation of learning materials and procedures, and ICT-based strategies to improve pupil development and learning. Fourth, I will focus on the experience gained in primary and secondary educational practice with respect to implementation. We can learn much from such practical experience, in particular about the conditions for developing and implementing the necessary changes in and around schools. Finally, I will propose future research. As I hope to make clear, theory-based development and implementation research can join forces with systemic innovation and differentiated assessment in educational practice, to pave the way for optimal “learning for self-regulation” for pupils, teachers, parents, schools, and society at large.
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For a structural engineer, effective communication and interaction with architects cannot be underestimated as a key skill to success throughout their professional career. Structural engineers and architects have to share a common language and understanding of each other in order to achieve the most desirable architectural and structural designs. This interaction and engagement develops during their professional career but needs to be nurtured during their undergraduate studies. The objective of this paper is to present the strategies employed to engage higher order thinking in structural engineering students in order to help them solve complex problem-based learning (PBL) design scenarios presented by architecture students. The strategies employed were applied in the experimental setting of an undergraduate module in structural engineering at Queen’s University Belfast in the UK. The strategies employed were active learning to engage with content knowledge, the use of physical conceptual structural models to reinforce key concepts and finally, reinforcing the need for hand sketching of ideas to promote higher order problem-solving. The strategies employed were evaluated through student survey, student feedback and module facilitator (this author) reflection. The strategies were qualitatively perceived by the tutor and quantitatively evaluated by students in a cross-sectional study to help interaction with the architecture students, aid interdisciplinary learning and help students creatively solve problems (through higher order thinking). The students clearly enjoyed this module and in particular interacting with structural engineering tutors and students from another discipline
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Student response systems (SRS) are hand-held devices or mobile phone polling systems which collate real-time, individual responses to on-screen questions. Previous research examining their role in higher education has highlighted both advantages and disadvantages of their use. This paper explores how different SRS influence the learning experience of psychology students across different levels of their programme. Across two studies, first year students’ experience of using Turningpoint clickers and second year students’ experience of using Poll Everywhere was investigated. Evaluations of both studies revealed that SRS has a number of positive impacts on learning, including enhanced engagement, active learning, peer interaction, and formative feedback. Technical and practical issues emerged as consistent barriers to the use of SRS. Discussion of these findings and the authors’ collective experiences of these technologies are used to provide insight into the way in which SRS can be effectively integrated within undergraduate psychology programmes.
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Purpose The aim of the study is to explore the role of confluent learning in supporting the development of change management knowledge, skills and attitudes and to inform the creation of a conceptual model based upon a priori and a posteriori knowledge gained from literature and the research. Design/methodology/approach The research adopts qualitative approach based on reflective inquiry methodology. There are two primary data sources, interviews with learners and the researchers’ reflective journals on learners’ opinions. Findings The confluent learning approach helped to stimulate affective states (e.g. interest and appreciation) to further reinforce cognitive gains (e.g. retention of knowledge) as a number of higher order thinking skills were further developed. The instructional design premised upon confluent learning enabled learners to further appreciate the complexities of change management. Research implications/ limitations The confluent learning approach offers another explanation to how learning takes place, contingent upon the use of a problem solving framework, instructional design and active learning in developing inter- and trans-disciplinary competencies. Practical implications This study not only explains how effective learning takes place but is also instructive to learning and teaching, and human resource development (HRD) professionals in curriculum design and the potential benefits of confluent learning. Social implications The adoption of a confluent learning approach helps to re-naturalise learning that appeals to learners affect. Originality/value This research is one of the few studies that provide an in-depth exploration of the use of confluent learning and how this approach co-develops cognitive abilities and affective capacity in the creation of a conceptual model.
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This paper is reviewing objective assessments of Parkinson’s disease(PD) motor symptoms, cardinal, and dyskinesia, using sensor systems. It surveys the manifestation of PD symptoms, sensors that were used for their detection, types of signals (measures) as well as their signal processing (data analysis) methods. A summary of this review’s finding is represented in a table including devices (sensors), measures and methods that were used in each reviewed motor symptom assessment study. In the gathered studies among sensors, accelerometers and touch screen devices are the most widely used to detect PD symptoms and among symptoms, bradykinesia and tremor were found to be mostly evaluated. In general, machine learning methods are potentially promising for this. PD is a complex disease that requires continuous monitoring and multidimensional symptom analysis. Combining existing technologies to develop new sensor platforms may assist in assessing the overall symptom profile more accurately to develop useful tools towards supporting better treatment process.
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This paper addresses the estimation of object boundaries from a set of 3D points. An extension of the constrained clustering algorithm developed by Abrantes and Marques in the context of edge linking is presented. The object surface is approximated using rectangular meshes and simplex nets. Centroid-based forces are used for attracting the model nodes towards the data, using competitive learning methods. It is shown that competitive learning improves the model performance in the presence of concavities and allows to discriminate close surfaces. The proposed model is evaluated using synthetic data and medical images (MRI and ultrasound images).
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Abstract: Active or participatory learning by the student within a classroom environment has been fairly recently recognized as an effective, efficient, and superior instructional technique yet few teachers in higher education have adopted this pedagogical strategy. This is especially true in Science where teachers primarily lecture to passively seated students while using static visual aids or multimedia projections. Teachers generally teach as they were taught and lecture formats have been the norm. Although student-learning theories as well as student learning styles, abilities, and understanding strategies have changed, traditional teaching techniques have not evolved past the “chalk and talk” instructional strategy. This research looked into student’s perceptions of cooperative learning or team-based active learning in order to gain insight and some understanding as to how students felt about this learning technique. Student’s attitudes were then compared to student grades to detennine whether cooperative learning impeded or ameliorated academic performance. The results revealed significant differences measured in all the survey questions pertaining to perception or attitudes. As a result of the cooperative learning activities, respondents indicated more agreement to the survey questions pertaining to the benefits of cooperative learning. The experimental group exposed to cooperative learning thus experienced more positive attitudes and perceptions than the groups exposed only to a lecture-based teaching and learning format. Each of the hypotheses tested demonstrated that students had more positive attitudes towards cooperative learning strategies. Recommendations as to future work were presented in order to gain a greater understanding into both student and teacher attitudes towards the cooperative learning model.||Résumé: Lapprentissage actif ou préparatoire par létudiant au sein d’une classe a été reconnu assez récemment comme une technique d’enseignement plus efficace. Cependant, peu d’enseignants ont adopté cette stratégie pedagogique pour l'éducation post-secondaire. Ceci est particulièrement le cas dans le domaine des sciences où les enseignants font surtout usage de cours magistraux avec des étudiants passifs tout en utilisant des aides visuelles statiques ou des projections multimédias. Les professeurs enseignent generalement comme on leur a eux-même enseigné et les cours magistraux ont été la norme par le passé. Les techniques traditionnelles d'enseignernent n'ont pas évolué au-delà de la craie et du tableau noir et ce même si les théories sur l’apprentissage par les étudiants ont changé, tout comme les styles, les habiletés et les stratégies de compréhension d’apprentissage des étudiants. Cette recherche se penche sur les perceptions des étudiants au sujet de l'apprentissage coopératif ou de l'apprentissage actif par équipe de telle sorte qu'on puisse avoir un aperçu et une certaine compréhension de comment les étudiants se sentent par rapport à ces techniques d'apprentissage. Les attitudes des étudiants ont par la suite été comparées aux notes de ceux-ci pour déterminer si l'apprentissage coopératif avait nui ou au contraire amélioré leurs performances académiques. Les résultats obtenus dans l'étude d'ensemble révèlent des différences significatives dans toutes les questions ayant trait à la perception et aux attitudes.
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This thesis addresses the Batch Reinforcement Learning methods in Robotics. This sub-class of Reinforcement Learning has shown promising results and has been the focus of recent research. Three contributions are proposed that aim to extend the state-of-art methods allowing for a faster and more stable learning process, such as required for learning in Robotics. The Q-learning update-rule is widely applied, since it allows to learn without the presence of a model of the environment. However, this update-rule is transition-based and does not take advantage of the underlying episodic structure of collected batch of interactions. The Q-Batch update-rule is proposed in this thesis, to process experiencies along the trajectories collected in the interaction phase. This allows a faster propagation of obtained rewards and penalties, resulting in faster and more robust learning. Non-parametric function approximations are explored, such as Gaussian Processes. This type of approximators allows to encode prior knowledge about the latent function, in the form of kernels, providing a higher level of exibility and accuracy. The application of Gaussian Processes in Batch Reinforcement Learning presented a higher performance in learning tasks than other function approximations used in the literature. Lastly, in order to extract more information from the experiences collected by the agent, model-learning techniques are incorporated to learn the system dynamics. In this way, it is possible to augment the set of collected experiences with experiences generated through planning using the learned models. Experiments were carried out mainly in simulation, with some tests carried out in a physical robotic platform. The obtained results show that the proposed approaches are able to outperform the classical Fitted Q Iteration.
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Research on the impact of the Project Approach on young children with disabilities or children who are at-risk is limited. Mixed methods were used to study the impact of the Project Approach on the social interactions, challenging behaviors, and language development of eight focal children in two inclusive classrooms. Child participants were two children with IEPs and two children identified as at-risk from each class. Adult participants were six professionals who received high quality supports to implement the Project Approach. Adults were interviewed prior to the beginning of the study and again mid-, and post-implementation. Choice time observations were videotaped twice per week over 14 weeks to assess the impact of the Project Approach on play levels and MLUm. Results revealed that social interactions, challenging behaviors, vocabulary, MLUm, were positively impacted following implementation of the Project Approach. Limitations of the study and suggestions for research and practice are discussed.
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Relatório EPE - Relatório de estágio em Educação Pré-Escolar:O relatório de estágio para a qualificação profissional foi realizado no âmbito da unidade curricular de Prática Pedagógica Supervisionada na Educação Pré-Escolar, sendo esta parte integrante do Mestrado em Educação Pré-Escolar e Ensino do 1º ciclo do Ensino Básico. Todo o trabalho desenvolvido no presente relatório teve como objetivo dar a conhecer, de forma crítica, reflexiva e sustentada, as experiências vividas pela formanda com o grupo de crianças que acompanhou, num total de 210 horas de estágio, iniciado em fevereiro e terminado em junho do presente ano. A prática pedagógica de um educador de infância influencia diretamente o desenvolvimento das crianças, bem como o desenvolvimento do próprio docente, contituindo para o desenvolvimento de competências fundamentais para a sua prática futura. Com vista a uma planificação focada nas necessidades e interesses evidenciados pelo grupo de crianças, o educador deve observar, planear, agir, avaliar, comunicar e articular, levando a cabo, paralelamente, a investigaçãoação como forma de refletir sobre a sua prática e sobre os efeitos da mesma, em si e nas crianças. Tendo por base estes pressupostos, foram observadas necessidades de desenvolvimento, interesses e resultados de aprendizagem, que permitiram a planificação de atividades a realizar, por forma a atingir os objetivos traçados para o desenvolvimento de capacidades nas crianças. Para isso, recorreu-se a estratégias inovadoras e diversificadas, suportadas pelos modelos curriculares High/Scope e Reggio Emilia, e também pela Metodologia de Trabalho de Projeto. O trabalho desenvolvido em torno da unidade curricular visa competências como a mobilização de saberes, a adoção de estratégias diferenciadas, a tomada de decisões conscientes e adequadas, o desenvolvimento de projetos de investigação e o desenvolvimento e consolidação de competências socioprofissionais e pessoais. Neste sentido, contribuiu para o desenvolvimento pessoal e para o crescimento profissional da mestranda, através das intervenções realizadas com o grupo de crianças. As diferentes etapas do processo educativo acompanharam afincadamente esta etapa, na medida em que contribuiram para um maior conhecimento da formanda quanto à ação e à planificação. Importa salientar que as atividades desenvolvidas ao longo deste período visaram o desenvolvimento de todas as áreas e domínios de conteúdo, nas crianças, com mais ênfase na área da formação pessoal e social e na área do conhecimento do mundo.
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Relatório de Estágio apresentado à Escola Superior de Educação de Paula Frassinetti para obtenção do grau de Mestre em Educação Pré-Escolar e Ensino do 1º Ciclo do Ensino Básico
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Evolutionary algorithms alone cannot solve optimization problems very efficiently since there are many random (not very rational) decisions in these algorithms. Combination of evolutionary algorithms and other techniques have been proven to be an efficient optimization methodology. In this talk, I will explain the basic ideas of our three algorithms along this line (1): Orthogonal genetic algorithm which treats crossover/mutation as an experimental design problem, (2) Multiobjective evolutionary algorithm based on decomposition (MOEA/D) which uses decomposition techniques from traditional mathematical programming in multiobjective optimization evolutionary algorithm, and (3) Regular model based multiobjective estimation of distribution algorithms (RM-MEDA) which uses the regular property and machine learning methods for improving multiobjective evolutionary algorithms.
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Wydział Studiów Edukacyjnych: Zakład Pedeutologii