10 resultados para science learning

em Helda - Digital Repository of University of Helsinki


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Participation and social modes of thinking - An intervention study on the development of collaborative learning in two primary school small groups This study explores the thinking together -intervention programme in three primary school classes. The object of the intervention was to teach pupils to use exploratory talk in small group collaboratory learning. Exploratory talk is a type of talk in which joint reasoning is made explicit. Research has shown that exploratory talk can improve mathematics and science learning, argumentative skills and competence in reasoning tests. The object of this study was to investigate the theory of social modes of thinking which the intervention program is based on. I tried to find out how the thinking together -intervention programme suits the Finnish context. Therefore my study is part of an international research project of interventions that have been implemented for example in Great-Britain and in Mexico. One essential drawback in former research made on thinking together -approach is that the nature of participation has not been studied properly. In this study I also examine how the nature of participation develops in small groups. In addition to that I aim to develope a theoretical framework which includes both the perspectives of the social modes of thinking and the nature of participation. The perspective of this study is sociocultural. The research material consists of video recordings of collaborative learning tasks of two small groups. In groups there were pupils of age groups 9 - 11. I study the nature of participation using both qualitative and quantitative methods. Quantitative methods include for example IR-analysis method and counting of turns at talk and words. I also use qualitative content analysis to analyze both the nature of participation and social modes of thinking. As a result of my study I found out that the interaction of the other group was leadership based and in the other group the interaction was without leadership relations. In both groups the participation was quantitatively more symmetrical in the end of the intervention. In the group in which the interaction was leadership based the participation of the pupils was more symmetrical. Exploratory talk was found more in the group without leadership relations, but in both groups the amount of exploratory talk was increased during the intervention. Leadership based interaction was further divided into interaction of alienating and inclusive leadership according to how symmetrical the participation was in the dialogue. Exploratory talk was found only when the leadership was inclusive or the interaction was without leadership relations. The main result of the study was that the exploratory talk was further divided into four subcategories according to the nature of participation. In open and inclusive exploratory talk all group members participated initiatively and their initiatives were responded by others. In closed and uneven exploratory talk some group members couldn't participate properly. Therefore it cannot be said that exploratory talk guarantees symmetrical participation. The nature of participation must be investigated separately.

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The aim of the study was to analyze and facilitate collaborative design in a virtual learning environment (VLE). Discussions of virtual design in design education have typically focused on technological or communication issues, not on pedagogical issues. Yet in order to facilitate collaborative design, it is also necessary to address the pedagogical issues related to the virtual design process. In this study, the progressive inquiry model of collaborative designing was used to give a structural level of facilitation to students working in the VLE. According to this model, all aspects of inquiry, such as creating the design context, constructing a design idea, evaluating the idea, and searching for new information, can be shared in a design community. The study consists of three design projects: 1) designing clothes for premature babies, 2) designing conference bags for an international conference, and 3) designing tactile books for visually impaired children. These design projects constituted a continuum of design experiments, each of which highlighted certain perspectives on collaborative designing. The design experiments were organized so that the participants worked in design teams, both face-to-face and virtually. The first design experiment focused on peer collaboration among textile teacher students in the VLE. The second design experiment took into consideration end-users needs by using a participatory design approach. The third design experiment intensified computer-supported collaboration between students and domain experts. The virtual learning environments, in these design experiments, were designed to support knowledge-building pedagogy and progressive inquiry learning. These environments enabled a detailed recording of all computer-mediated interactions and data related to virtual designing. The data analysis was based on qualitative content analysis of design statements in the VLE. This study indicated four crucial issues concerning collaborative design in the VLE in craft and design education. Firstly, using the collaborative design process in craft and design education gives rise to special challenges of building learning communities, creating appropriate design tasks for them, and providing tools for collaborative activities. Secondly, the progressive inquiry model of collaborative designing can be used as a scaffold support for design thinking and for reflection on the design process. Thirdly, participation and distributed expertise can be facilitated by considering the key stakeholders who are related to the design task or design context, and getting them to participate in virtual designing. Fourthly, in the collaborative design process, it is important that team members create and improve visual and technical ideas together, not just agree or disagree about proposed ideas. Therefore, viewing the VLE as a medium for collaborative construction of the design objects appears crucial in order to understand and facilitate the complex processes in collaborative designing.

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The paradigm of computational vision hypothesizes that any visual function -- such as the recognition of your grandparent -- can be replicated by computational processing of the visual input. What are these computations that the brain performs? What should or could they be? Working on the latter question, this dissertation takes the statistical approach, where the suitable computations are attempted to be learned from the natural visual data itself. In particular, we empirically study the computational processing that emerges from the statistical properties of the visual world and the constraints and objectives specified for the learning process. This thesis consists of an introduction and 7 peer-reviewed publications, where the purpose of the introduction is to illustrate the area of study to a reader who is not familiar with computational vision research. In the scope of the introduction, we will briefly overview the primary challenges to visual processing, as well as recall some of the current opinions on visual processing in the early visual systems of animals. Next, we describe the methodology we have used in our research, and discuss the presented results. We have included some additional remarks, speculations and conclusions to this discussion that were not featured in the original publications. We present the following results in the publications of this thesis. First, we empirically demonstrate that luminance and contrast are strongly dependent in natural images, contradicting previous theories suggesting that luminance and contrast were processed separately in natural systems due to their independence in the visual data. Second, we show that simple cell -like receptive fields of the primary visual cortex can be learned in the nonlinear contrast domain by maximization of independence. Further, we provide first-time reports of the emergence of conjunctive (corner-detecting) and subtractive (opponent orientation) processing due to nonlinear projection pursuit with simple objective functions related to sparseness and response energy optimization. Then, we show that attempting to extract independent components of nonlinear histogram statistics of a biologically plausible representation leads to projection directions that appear to differentiate between visual contexts. Such processing might be applicable for priming, \ie the selection and tuning of later visual processing. We continue by showing that a different kind of thresholded low-frequency priming can be learned and used to make object detection faster with little loss in accuracy. Finally, we show that in a computational object detection setting, nonlinearly gain-controlled visual features of medium complexity can be acquired sequentially as images are encountered and discarded. We present two online algorithms to perform this feature selection, and propose the idea that for artificial systems, some processing mechanisms could be selectable from the environment without optimizing the mechanisms themselves. In summary, this thesis explores learning visual processing on several levels. The learning can be understood as interplay of input data, model structures, learning objectives, and estimation algorithms. The presented work adds to the growing body of evidence showing that statistical methods can be used to acquire intuitively meaningful visual processing mechanisms. The work also presents some predictions and ideas regarding biological visual processing.

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In this thesis a manifold learning method is applied to the problem of WLAN positioning and automatic radio map creation. Due to the nature of WLAN signal strength measurements, a signal map created from raw measurements results in non-linear distance relations between measurement points. These signal strength vectors reside in a high-dimensioned coordinate system. With the help of the so called Isomap-algorithm the dimensionality of this map can be reduced, and thus more easily processed. By embedding position-labeled strategic key points, we can automatically adjust the mapping to match the surveyed environment. The environment is thus learned in a semi-supervised way; gathering training points and embedding them in a two-dimensional manifold gives us a rough mapping of the measured environment. After a calibration phase, where the labeled key points in the training data are used to associate coordinates in the manifold representation with geographical locations, we can perform positioning using the adjusted map. This can be achieved through a traditional supervised learning process, which in our case is a simple nearest neighbors matching of a sampled signal strength vector. We deployed this system in two locations in the Kumpula campus in Helsinki, Finland. Results indicate that positioning based on the learned radio map can achieve good accuracy, especially in hallways or other areas in the environment where the WLAN signal is constrained by obstacles such as walls.

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This research is connected with an education development project for the four-year-long officer education program at the National Defence University. In this curriculum physics was studied in two alternative course plans namely scientific and general. Observations connected to the later one e.g. student feedback and learning outcome gave indications that action was needed to support the course. The reform work was focused on the production of aligned course related instructional material. The learning material project produced a customized textbook set for the students of the general basic physics course. The research adapts phases that are typical in Design Based Research (DBR). The research analyses the feature requirements for physics textbook aimed at a specific sector and frames supporting instructional material development, and summarizes the experiences gained in the learning material project when the selected frames have been applied. The quality of instructional material is an essential part of qualified teaching. The goal of instructional material customization is to increase the product's customer centric nature and to enhance its function as a support media for the learning process. Textbooks are still one of the core elements in physics teaching. The idea of a textbook will remain but the form and appearance may change according to the prevailing technology. The work deals with substance connected frames (demands of a physics textbook according to the PER-viewpoint, quality thinking in educational material development), frames of university pedagogy and instructional material production processes. A wide knowledge and understanding of different frames are useful in development work, if they are to be utilized to aid inspiration without limiting new reasoning and new kinds of models. Applying customization even in the frame utilization supports creative and situation aware design and diminishes the gap between theory and practice. Generally, physics teachers produce their own supplementary instructional material. Even though customization thinking is not unknown the threshold to produce an entire textbook might be high. Even though the observations here are from the general physics course at the NDU, the research gives tools also for development in other discipline related educational contexts. This research is an example of an instructional material development work together the questions it uncovers, and presents thoughts when textbook customization is rewarding. At the same time, the research aims to further creative customization thinking in instruction and development. Key words: Physics textbook, PER (Physics Education Research), Instructional quality, Customization, Creativity

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We propose an efficient and parameter-free scoring criterion, the factorized conditional log-likelihood (ˆfCLL), for learning Bayesian network classifiers. The proposed score is an approximation of the conditional log-likelihood criterion. The approximation is devised in order to guarantee decomposability over the network structure, as well as efficient estimation of the optimal parameters, achieving the same time and space complexity as the traditional log-likelihood scoring criterion. The resulting criterion has an information-theoretic interpretation based on interaction information, which exhibits its discriminative nature. To evaluate the performance of the proposed criterion, we present an empirical comparison with state-of-the-art classifiers. Results on a large suite of benchmark data sets from the UCI repository show that ˆfCLL-trained classifiers achieve at least as good accuracy as the best compared classifiers, using significantly less computational resources.