733 resultados para Design-Build-Test, Project-Based-Learning
Resumo:
Analog filters and direct digital filters are implemented using digital signal processing techniques. Specifically, Butterworth, Elliptic, and Chebyshev filters are implemented using the Motorola 56001 Digital Signal Processor by the integration of three software packages: MATLAB, C++, and Motorola's Application Development System. The integrated environment allows the novice user to design a filter automatically by specifying the filter order and critical frequencies, while permitting more experienced designers to take advantage of MATLAB's advanced design capabilities. This project bridges the gap between the theoretical results produced by MATLAB and the practicalities of implementing digital filters using the Motorola 56001 Digital Signal Processor. While these results are specific to the Motorola 56001 they may be extended to other digital signal processors. MATLAB handles the filter calculations, a C++ routine handles the conversion to assembly code, and the Motorola software compiles and transmits the code to the processor
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n learning from trial and error, animals need to relate behavioral decisions to environmental reinforcement even though it may be difficult to assign credit to a particular decision when outcomes are uncertain or subject to delays. When considering the biophysical basis of learning, the credit-assignment problem is compounded because the behavioral decisions themselves result from the spatio-temporal aggregation of many synaptic releases. We present a model of plasticity induction for reinforcement learning in a population of leaky integrate and fire neurons which is based on a cascade of synaptic memory traces. Each synaptic cascade correlates presynaptic input first with postsynaptic events, next with the behavioral decisions and finally with external reinforcement. For operant conditioning, learning succeeds even when reinforcement is delivered with a delay so large that temporal contiguity between decision and pertinent reward is lost due to intervening decisions which are themselves subject to delayed reinforcement. This shows that the model provides a viable mechanism for temporal credit assignment. Further, learning speeds up with increasing population size, so the plasticity cascade simultaneously addresses the spatial problem of assigning credit to synapses in different population neurons. Simulations on other tasks, such as sequential decision making, serve to contrast the performance of the proposed scheme to that of temporal difference-based learning. We argue that, due to their comparative robustness, synaptic plasticity cascades are attractive basic models of reinforcement learning in the brain.
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In this article, we refine a politics of thinking from the margins by exploring a pedagogical model that advances transformative notions of service learning as social justice teaching. Drawing on a recent course we taught involving both incarcerated women and traditional college students, we contend that when communication among differentiated and stratified parties occurs, one possible result is not just a view of the other but also a transformation of the self and other. More specifically, we suggest that an engaged feminist praxis of teaching incarcerated women together with college students helps illuminate the porous nature of fixed markers that purport to reveal our identities (e.g., race and gender), to emplace our bodies (e.g., within institutions, prison gates, and walls), and to specify our locations (e.g., cultural, geographic, socialeconomic). One crucial theoretical insight our work makes clear is that the model of social justice teaching to which we aspired necessitates re-conceptualizing ourselves as students and professors whose subjectivities are necessarily relational and emergent.
Resumo:
Misconceptions exist in all fields of learning and develop through a person’s preconception of how the world works. Students with misconceptions in chemical engineering are not capable of correctly transferring knowledge to a new situation and will likely arrive at an incorrect solution. The purpose of this thesis was to repair misconceptions in thermodynamics by using inquiry-based activities. Inquiry-based learning is a method of teaching that involves hands-on learning and self-discovery. Previous work has shown inquiry-based methods result in better conceptual understanding by students relative to traditional lectures. The thermodynamics activities were designed to guide students towards the correct conceptual understanding through observing a preconception fail to hold up through an experiment or simulation. The developed activities focus on the following topics in thermodynamics: “internal energy versus enthalpy”, “equilibrium versus steady state”, and “entropy”. For each topic, two activities were designed to clarify the concept and assure it was properly grasped. Each activity was coupled with an instructions packet containing experimental procedure as well as pre- and post-analysis questions, which were used to analyze the effect of the activities on the students’ responses. Concept inventories were used to monitor students’ conceptual understanding at the beginning and end of the semester. The results did not show a statistically significant increase in the overall concept inventory scores for students who performed the activities compared to traditional learning. There was a statistically significant increase in concept area scores for “internal energy versus enthalpy” and “equilibrium versus steady state”. Although there was not a significant increase in concept inventory scores for “entropy”, written analyses showed most students’ misconceptions were repaired. Students transferred knowledge effectively and retained most of the information in the concept areas of “internal energy versus enthalpy” and “equilibrium versus steady state”.
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We introduce a diagnostic test for the mixing distribution in a generalised linear mixed model. The test is based on the difference between the marginal maximum likelihood and conditional maximum likelihood estimates of a subset of the fixed effects in the model. We derive the asymptotic variance of this difference, and propose a test statistic that has a limiting chi-square distribution under the null hypothesis that the mixing distribution is correctly specified. For the important special case of the logistic regression model with random intercepts, we evaluate via simulation the power of the test in finite samples under several alternative distributional forms for the mixing distribution. We illustrate the method by applying it to data from a clinical trial investigating the effects of hormonal contraceptives in women.
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This report provides an analysis of the thermal performance and emissions characteristics of improved biomass stoves constructed using earthen materials. Commonly referred to as mud stoves, this type of improved stove incorporates high clay content soil with an organic binder in the construction of its combustion chamber and body. When large quantities of the mud material are used to construct the stove body, the stove does not offer significant improvements in fuel economy or air quality relative to traditional open fire cooking. This is partly because a significant amount of heat is absorbed by the mass of the stove reducing combustion efficiency and heat transfer to the cook pot. An analysis of the thermal and mechanical properties of stove materials was also performed. A material mixture containing a one‐to‐one ratio by volume of high content clay soil and straw was found to have thermal properties comparable to fired ceramics used in more advanced improved stove designs. Feedback from mud stove users in Mauritania and Mali, West Africa was also collected during implementation. Suggestions for stove design improvements were developed based on this information and the data collected in the performance, emissions, and material properties analysis. Design suggestions include reducing stove height to accommodate user cooking preferences and limiting overall stove mass to reduce heat loss to the stove body.
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Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.
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Learning is based on rules that can be elucidated by behavioural experiments. This article focuses on virtual experiments, in which non-associative learning (habituation, sensitization) and principles of associative learning (contiguity, inhibitory learning, generalization, overshadowing, positive and negative patterning) can be examined using 'virtual' honey bees in PER (Proboscis Reaction Extension) conditioning experiments. Users can develop experimental designs, simulate and document the experiments and find explanations and suggestions for the analysis of the learning experiments. The virtual experiments are based on video sequences and data from actual learning experiments. The bees' responses are determined by probability-based learning profiles.
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The article is concerned with design and use of e-learning technology to develop education qualitatively. The purpose is to develop a framework for a pedagogical evaluation of e-learning technology. The approach is that evaluation and design must be grounded in a learning theoretical approach, and it is argued that it is necessary to make a reflection of technology in relation to activities, learning principles, and a learning theory in order to qualitatively develop education. The article presents three frameworks developed on the basis of cognitivism, radical constructivism and activity theory. Finally, on the basis of the frameworks, the article discusses e-learning technology and, more specifically, design of virtual learning environments and learning objects. It is argued that e-learning technology is not pedagogically neutral, and that it is therefore necessary to focus on design of technology that explicitly supports a certain pedagogical approach. Further, it is argued that design should direct its focus away from organisation of content and towards design of activities.
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The goal of this article was to study teachers' professional development related to web-based learning in the context of the teacher community. The object was to learn in what kind of networks teachers share the knowledge of web-based learning and what are the factors in the community that support or challenge teachers professional development of web-based learning. The findings of the study revealed that there are teachers who are especially active, called the central actors in this study, in the teacher community who collaborate and share knowledge of web-based learning. These central actors share both technical and pedagogical knowledge of web-based learning in networks that include both internal and external relations in the community and involve people, artefacts and a variety of media. Furthermore, the central actors appear to bridge different fields of teaching expertise in their community. According to the central actors' experiences the important factors that support teachers' professional development of web-based learning in the community are; the possibility to learn from colleagues and from everyday working practices, an emotionally safe atmosphere, the leader's personal support and community-level commitment. Also, the flexibility in work planning, challenging pupils, shared lessons with colleagues, training events in an authentic work environment and colleagues' professionalism are considered meaningful for professional development. As challenges, the knowledge sharing of web-based learning in the community needs mutual interests, transactive memory, time and facilities, peer support, a safe atmosphere and meaningful pedagogical practices. On the basis of the findings of the study it is suggested that by intensive collaboration related to web-based learning it may be possible to break the boundaries of individual teachership and create such sociocultural activities which support collaborative professional development in the teacher community. Teachers' in-service training programs should be more sensitive to the culture of teacher communities and teachers' reciprocal relations. Further, teacher trainers should design teachers' in-service training of web-based learning in co-evolution with supporting networks which include the media and artefacts as well as people.
Resumo:
The goal of this article was to study teachers' professional development related to web-based learning in the context of the teacher community. The object was to learn in what kind of networks teachers share the knowledge of web-based learning and what are the factors in the community that support or challenge teachers professional development of web-based learning. The findings of the study revealed that there are teachers who are especially active, called the central actors in this study, in the teacher community who collaborate and share knowledge of web-based learning. These central actors share both technical and pedagogical knowledge of web-based learning in networks that include both internal and external relations in the community and involve people, artefacts and a variety of media. Furthermore, the central actors appear to bridge different fields of teaching expertise in their community. According to the central actors' experiences the important factors that support teachers' professional development of web-based learning in the community are; the possibility to learn from colleagues and from everyday working practices, an emotionally safe atmosphere, the leader's personal support and community-level commitment. Also, the flexibility in work planning, challenging pupils, shared lessons with colleagues, training events in an authentic work environment and colleagues' professionalism are considered meaningful for professional development. As challenges, the knowledge sharing of web-based learning in the community needs mutual interests, transactive memory, time and facilities, peer support, a safe atmosphere and meaningful pedagogical practices. On the basis of the findings of the study it is suggested that by intensive collaboration related to web-based learning it may be possible to break the boundaries of individual teachership and create such sociocultural activities which support collaborative professional development in the teacher community. Teachers' in-service training programs should be more sensitive to the culture of teacher communities and teachers' reciprocal relations. Further, teacher trainers should design teachers' in-service training of web-based learning in co-evolution with supporting networks which include the media and artefacts as well as people.
Resumo:
The goal of this article was to study teachers' professional development related to web-based learning in the context of the teacher community. The object was to learn in what kind of networks teachers share the knowledge of web-based learning and what are the factors in the community that support or challenge teachers professional development of web-based learning. The findings of the study revealed that there are teachers who are especially active, called the central actors in this study, in the teacher community who collaborate and share knowledge of web-based learning. These central actors share both technical and pedagogical knowledge of web-based learning in networks that include both internal and external relations in the community and involve people, artefacts and a variety of media. Furthermore, the central actors appear to bridge different fields of teaching expertise in their community. According to the central actors' experiences the important factors that support teachers' professional development of web-based learning in the community are; the possibility to learn from colleagues and from everyday working practices, an emotionally safe atmosphere, the leader's personal support and community-level commitment. Also, the flexibility in work planning, challenging pupils, shared lessons with colleagues, training events in an authentic work environment and colleagues' professionalism are considered meaningful for professional development. As challenges, the knowledge sharing of web-based learning in the community needs mutual interests, transactive memory, time and facilities, peer support, a safe atmosphere and meaningful pedagogical practices. On the basis of the findings of the study it is suggested that by intensive collaboration related to web-based learning it may be possible to break the boundaries of individual teachership and create such sociocultural activities which support collaborative professional development in the teacher community. Teachers' in-service training programs should be more sensitive to the culture of teacher communities and teachers' reciprocal relations. Further, teacher trainers should design teachers' in-service training of web-based learning in co-evolution with supporting networks which include the media and artefacts as well as people.
Resumo:
Today, Digital Systems and Services for Technology Supported Learning and Education are recognized as the key drivers to transform the way that individuals, groups and organizations “learn” and the way to “assess learning” in 21st Century. These transformations influence: Objectives - moving from acquiring new “knowledge” to developing new and relevant “competences”; Methods – moving from “classroom” based teaching to “context-aware” personalized learning; and Assessment – moving from “life-long” degrees and certifications to “on-demand” and “in-context” accreditation of qualifications. Within this context, promoting Open Access to Formal and Informal Learning, is currently a key issue in the public discourse and the global dialogue on Education, including Massive Open Online Courses (MOOCs) and Flipped School Classrooms. This volume on Digital Systems for Open Access to Formal and Informal Learning contributes to the international dialogue between researchers, technologists, practitioners and policy makers in Technology Supported Education and Learning. It addresses emerging issues related with both theory and practice, as well as, methods and technologies that can support Open Access to Formal and Informal Learning. In the twenty chapters contributed by international experts who are actively shaping the future of Educational Technology around the world, topics such as: - The evolution of University Open Courses in Transforming Learning - Supporting Open Access to Teaching and Learning of People with Disabilities - Assessing Student Learning in Online Courses - Digital Game-based Learning for School Education - Open Access to Virtual and Remote Labs for STEM Education - Teachers’ and Schools’ ICT Competence Profiling - Web-Based Education and Innovative Leadership in a K-12 International School Setting are presented. An in-depth blueprint of the promise, potential, and imminent future of the field, Digital Systems for Open Access to Formal and Informal Learning is necessary reading for researchers and practitioners, as well as, undergraduate and postgraduate students, in educational technology.
Resumo:
The increasing practice of offshore outsourcing software maintenance has posed the challenge of effectively transferring knowledge to individual software engineers of the vendor. In this theoretical paper, we discuss the implications of two learning theories, the model of work-based learning (MWBL) and cognitive load theory (CLT), for knowledge transfer during the transition phase. Taken together, the theories suggest that learning mechanisms need to be aligned with the type of knowledge (tacit versus explicit), task characteristics (complexity and recurrence), and the recipients’ expertise. The MWBL proposes that learning mechanisms need to include conceptual and practical activities based on the relative importance of explicit and tacit knowledge. CLT explains how effective portfolios of learning mechanisms change over time. While jobshadowing, completion tasks, and supportive information may prevail at the outset of transition, they may be replaced by the work on conventional tasks towards the end of transition.
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BACKGROUND Evidence exists that a farming environment in childhood may provide protection against atopic respiratory disease. In the GABRIEL project based in Poland and Alpine regions of Germany, Austria and Switzerland, we aimed to assess whether a farming environment in childhood is protective against allergic diseases in Poland and whether specific exposures explain any protective effect. METHODS In rural Poland, 23 331 families of schoolchildren completed a questionnaire enquiring into farming practices and allergic diseases (Phase I). A subsample (n = 2586) participated in Phase II involving a more detailed questionnaire on specific farm exposures with objective measures of atopy. RESULTS Farming differed between Poland and the Alpine centres; in the latter, cattle farming was prevalent, whereas in Poland 18% of village farms kept ≥1 cow and 34% kept ≥1 pig. Polish children in villages had lower prevalences of asthma and hay fever than children from towns, and in the Phase II population, farm children had a reduced risk of atopy measured by IgE (aOR = 0.72, 95% CI 0.57, 0.91) and skin prick test (aOR = 0.65, 95% CI 0.50, 0.86). Early-life contact with grain was inversely related to the risk of atopy measured by IgE (aOR = 0.66, 95% CI 0.47, 0.92) and appeared to explain part of the farming effect. CONCLUSION While farming in Poland differed from that in the Alpine areas as did the exposure-response associations, we found in communities engaged in small-scale, mixed farming, there was a protective farming effect against objective measures of atopy potentially related to contact with grain or associated farm activities.