976 resultados para Networked learning


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A Nonverbal Learning Disability is believed to be caused by damage, disorder or destruction of neuronal white matter in the brain’s right hemisphere and may be seen in persons experiencing a wide range of neurological diseases such as hydrocephalus and other types of brain injury (Harnadek & Rourke 1994). This article probes the relationship between shunted hydrocephalus and Nonverbal Learning Disability. Description of hydrocephalus and intelligence associated with hydrocephalus concludes with explication of the ‘final common pathway’ that links residual damage caused by the hydrocephalic condition to a Nonverbal Learning Disability (Rourke & Del Dotto 1994, p. 37). The paper seeks to assist teachers, teacher aides, psychologists, guidance officers, support workers, parents and disability service providers whose role is to understand and advocate for individuals with shunted hydrocephalus and spina bifida.

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Mobile sensor platforms such as Autonomous Underwater Vehicles (AUVs) and robotic surface vessels, combined with static moored sensors compose a diverse sensor network that is able to provide macroscopic environmental analysis tool for ocean researchers. Working as a cohesive networked unit, the static buoys are always online, and provide insight as to the time and locations where a federated, mobile robot team should be deployed to effectively perform large scale spatiotemporal sampling on demand. Such a system can provide pertinent in situ measurements to marine biologists whom can then advise policy makers on critical environmental issues. This poster presents recent field deployment activity of AUVs demonstrating the effectiveness of our embedded communication network infrastructure throughout southern California coastal waters. We also report on progress towards real-time, web-streaming data from the multiple sampling locations and mobile sensor platforms. Static monitoring sites included in this presentation detail the network nodes positioned at Redondo Beach and Marina Del Ray. One of the deployed mobile sensors highlighted here are autonomous Slocum gliders. These nodes operate in the open ocean for periods as long as one month. The gliders are connected to the network via a Freewave radio modem network composed of multiple coastal base-stations. This increases the efficiency of deployment missions by reducing operational expenses via reduced reliability on satellite phones for communication, as well as increasing the rate and amount of data that can be transferred. Another mobile sensor platform presented in this study are the autonomous robotic boats. These platforms are utilized for harbor and littoral zone studies, and are capable of performing multi-robot coordination while observing known communication constraints. All of these pieces fit together to present an overview of ongoing collaborative work to develop an autonomous, region-wide, coastal environmental observation and monitoring sensor network.

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Teacher quality is recognised as a lynchpin for education reforms internationally, and both Federal and State governments in Australia have turned their attention to teacher education institutions: the starting point for preparing quality teachers. Changes to policy and shifts in expectations impact on Faculties of Education, despite the fact that little is known about what makes a quality teacher preparation program effective. New accountability measures, mandated Professional Standards, and proposals to test all graduates before registration, mean that teacher preparation programs need capacity for flexibility and responsiveness. The risk is that undergraduate degree programs can become ‘patchwork quilts’ with traces of the old and new stitched together, sometimes at the expense of coherence and integrity. This paper provides a roadmap used by one large Faculty of Education in Queensland for reforming and reconceptualising the curriculum for a 4-year undergraduate program, in response to new demands from government and the professional bodies.

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An approach aimed at enhancing learning by matching individual students' preferred cognitive styles to computer-based instructional (CBI) material is presented. This approach was used in teaching some components of a third-year unit in an electrical engineering course at the Queensland University of Technology. Cognitive style characteristics of perceiving and processing information were considered. The bimodal nature of cognitive styles (analytic/imager, analytic/verbalizer, wholist/imager and wholist/verbalizer) was examined in order to assess the full ramification of cognitive styles on learning. In a quasi-experimental format, students' cognitive styles were analysed by cognitive style analysis (CSA) software. On the basis of the CSA results the system defaulted students to either matched or mismatched CBI material. The consistently better performance by the matched group suggests potential for further investigations where the limitations cited in this paper are eliminated. Analysing the differences between cognitive styles on individual test tasks also suggests that certain test tasks may better suit certain cognitive styles.

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This paper reports two studies designed to investigate the effect on learning outcomes of matching individuals' preferred cognitive styles to computer-based instructional (CBI) material. Study 1 considered the styles individually as Verbalizer, Imager, Wholist and Analytic. Study 2 considered the bi-dimensional nature of cognitive styles in order to assess the full ramification of cognitive styles on learning: Analytic/Imager, Analytic/ Verbalizer, Wholist/Imager and the Wholist/Verbalizer. The mix of images and text, the nature of the text material, use of advance organizers and proximity of information to facilitate meaningful connections between various pieces of information were some of the considerations in the design of the CBI material. In a quasi-experimental format, students' cognitive styles were analysed by Cognitive Style Analysis (CSA) software. On the basis of the CSA result, the system defaulted students to either matched or mismatched CBI material by alternating between the two formats. The instructional material had a learning and a test phase. Learning outcome was tested on recall, labelling, explanation and problem-solving tasks. Comparison of the matched and mismatched instruction did not indicate significant difference between the groups, but the consistently better performance by the matched group suggests potential for further investigations where the limitations cited in this paper are eliminated. The result did indicate a significant difference between the four cognitive styles with the Wholist/Verbalizer group performing better then all other cognitive styles. Analysing the difference between cognitive styles on individual test tasks indicated significant difference on recall, labelling and explanation, suggesting that certain test tasks may suit certain cognitive styles.

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The computation of compact and meaningful representations of high dimensional sensor data has recently been addressed through the development of Nonlinear Dimensional Reduction (NLDR) algorithms. The numerical implementation of spectral NLDR techniques typically leads to a symmetric eigenvalue problem that is solved by traditional batch eigensolution algorithms. The application of such algorithms in real-time systems necessitates the development of sequential algorithms that perform feature extraction online. This paper presents an efficient online NLDR scheme, Sequential-Isomap, based on incremental singular value decomposition (SVD) and the Isomap method. Example simulations demonstrate the validity and significant potential of this technique in real-time applications such as autonomous systems.

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This paper presents a general methodology for learning articulated motions that, despite having non-linear correlations, are cyclical and have a defined pattern of behavior Using conventional algorithms to extract features from images, a Bayesian classifier is applied to cluster and classify features of the moving object. Clusters are then associated in different frames and structure learning algorithms for Bayesian networks are used to recover the structure of the motion. This framework is applied to the human gait analysis and tracking but applications include any coordinated movement such as multi-robots behavior analysis.

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In this paper, we present the application of a non-linear dimensionality reduction technique for the learning and probabilistic classification of hyperspectral image. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. It gives much greater information content per pixel on the image than a normal colour image. This should greatly help with the autonomous identification of natural and manmade objects in unfamiliar terrains for robotic vehicles. However, the large information content of such data makes interpretation of hyperspectral images time-consuming and userintensive. We propose the use of Isomap, a non-linear manifold learning technique combined with Expectation Maximisation in graphical probabilistic models for learning and classification. Isomap is used to find the underlying manifold of the training data. This low dimensional representation of the hyperspectral data facilitates the learning of a Gaussian Mixture Model representation, whose joint probability distributions can be calculated offline. The learnt model is then applied to the hyperspectral image at runtime and data classification can be performed.

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In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

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The impact of digital technology within the creative industries has brought with it a range of new opportunities for collaborative, cross-disciplinary and multi-disciplinary practice. Along with these opportunities has come the need to re-evaluate how we as educators approach teaching within this new digital culture. Within the field of animation, there has been a radical shift in the expectations of students, industry and educators as animation has become central to a range of new moving image practices. This paper interrogates the effectiveness of adopting a studio-based collaborative production project as a method for educating students within this new moving-image culture. The project was undertaken, as part of the Creative Industries Transitions to New Professional Environments program at Queensland University of Technology (QUT) in Brisbane Australia. A number of students studying across the Creative Industries Faculty and the Faculty of Science and Technology were invited to participate in the development of a 3D animated short film. The project offered students the opportunity to become actively involved in all stages of the creative process, allowing them to experience informal learning through collaborative professional practice. It is proposed that theoretical principles often associated with andragogy and constructivism can be used to design and deliver programs that address the emerging issues surrounding the teaching of this new moving image culture.

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A number of instructors have recently adopted social network sites (SNSs) for learning. However, the learning design of SNSs often remains at a preliminary level similar to a personal log book because it does not properly include reflective learning elements such as individual reflection and collaboration. This article looks at the reflective learning process and the public writing process as a way of improving the quality of reflective learning on SNSs. It proposes a reflective learning model on SNSs based on two key pedagogical concepts for social networking: individual expression and collaborative connection. It is expected that the model would be helpful for instructors in designing a reflective learning process on SNSs in an effective and flexible way.

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Research has established a close relationship between learning environments and learning outcomes (Department of Education and Early Childhood Development, Victoria, 2008; Woolner, Hall, Higgins, McCaughey & Wall, 2007) yet little is known about how students in Australian schools imagine the ways that their learning environments could be improved to enhance their engagement with the processes and content of education and children are rarely consulted on the issue of school design (Rudduck & Flutter, 2004). Currently, school and classroom designers give attention to operational matters of efficiency and economy, so that architecture for children’s education is largely conceived in terms of adult and professional needs (Halpin, 2007). This results in the construction of educational spaces that impose traditional teaching and learning methods, reducing the possibilities of imaginative pedagogical relationships. Education authorities may encourage new, student-centred pedagogical styles, such as collaborative learning, team-teaching and peer tutoring, but the spaces where such innovations are occurring do not always provide the features necessary to implement these styles. Heeding the views of children could result in the creation of spaces where more imaginative pedagogical relationships and student-centred pedagogical styles can be implemented. In this article, a research project conducted with children in nine Queensland primary schools to investigate their ideas of the ideal ‘school’ is discussed. Overwhelmingly, the students’ work emphasised that learning should be fun and that learning environments should be eco-friendly places where their imaginations can be engaged and where they learn from and in touch with reality. The children’s imagined schools echo ideas that have been promoted over many decades by progressive educators such as John Dewey (1897, in Provenzo, 2006) (“experiential learning”), AS Neill (in Cassebaum, 2003) (Summerhill school) and Ivan Illich (1970) (“deschooling”), with a vast majority of students suggesting that, wherever possible, learning should take place away from classrooms and in environments that support direct, hands-on learning.

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This case study involved a detailed analysis of the changes in beliefs and teaching practices of teachers who adopted the Primary Connections program as a professional development initiative. When implementing an inquiry-based learning model, teachers observed that their students learnt more when they intervened less. By scaffolding open-ended nquiries they achieved more diverse, complex and thorough learning outcomes than previously achieved with teacher-led discussions or demonstrations. Initially, student autonomy presented erceived threats to teachers, including possible selection of topics outside the teachers’ science knowledge. In practice, when such issues arose, resolving them became a stimulating part of the earning for both teachers and students. The teachers’ observation of enhanced student learning became a powerful motivator for change in their beliefs and practices. Implications for developers of PD programs are (1) the importance of modeling student-devised inquiries, and (2) recognising the role of successful classroom implementation in facilitating change.

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It is widely held, through the Socratic tradition, that discussion is at the heart of learning. Moderated discussion forums have been shown to replicate the debate, argument and verbal defence of viewpoints that we have come to expect in face-to-face learning environments and that we generally accept to underpin learning. While much has been written about discussion forums in educational settings, particularly in how to moderate and promote effective interaction with students at a distance, this paper takes a different approach. It looks at how forums may be used to support face-to-face learning in the contemporary context of the massification of on-campus classes. Further to this, it will argue for discussion forums as an indicator of social presence in the learning environment. It will cautiously conclude that, through purposeful design, this form of asynchronous communication has a valuable role to play in creating a positive and supportive environment for students entering university. Discussion forums are tools with a versatility yet to be fully exploited.