c&d-learning implementation architecture: Adapting e-learning to developing countries

From the educational point of view, the most widespread method in developing countries is on-site education. Technical and economic resources cannot support conventional distance learning infrastructures and it is even worse for courses in universities. They usually suffer a lack of qualified faculty staff, especially in technical degrees. The literature suggest that e-learning is a suitable solution for this problem, but its methods are developed attending to educational necessities of the First World and cannot be applied directly to other contexts. The proposed methodology is a variant of traditional e-learning adapted to the needs of developing countries. E-learning for Cooperation and Development (c&d-learning) is oriented to be used for educational institutions without adequate technical or human resources. In this paper we describe the c&d-learning implementation architecture based on three main phases: hardware, communication and software; e.g. computer and technical equipping, internet accessing and e-learning platform adaptation. Proper adaptation of educational contents to c&d-learning is discussed and a real case of application in which the authors are involved is described: the Ngozi University at Burundi.

Bilingualism, literacy and NAPLAN : ongoing challenges for EAL/D education [Editorial]

Advocacy is integral to the work of many TESOL specialists. For several decades, ACTA and the state TESOL associations, along with other professional associations, and individual teachers, researchers and administrators have all engaged with conversations about EAL/D education in public forums. These advocates have drawn attention to implications of policy developments for EAL/D students; they have proffered alternative forms of curriculum, pedagogy and assessment to better account for the particularity of EAL/D learning pathways; they have argued the necessity of specialist EAL/D teaching. In response to the Australian Language and Literacy Policy of the early 1990s, for example, there was “a frenzy of writing responses… a conference… and attempts to publicise what was going on through the press and television” (Moore, 1995, p. 6). It is in this spirit that this double issue of TESOL in Context has been compiled...

Spatial/surveying programs repositioning within new STEM Faculty at QUT

Many of the undergraduate and postgraduate programs of the former Faculty of Built Environment and Engineering PLUS Faculty of Sciences and Technology are changing as a result of merging these two large organisations, with some disciplines relocating to faculties of Creative Industries and Health respectively. The new STEM precinct under construction has begun rising from the proverbial hole-in-the-ground. Existing Surveying and Spatial Sciences programs, assets and staff are being repositioned with the newly formed School of Earth, Environment and Biological Sciences.2011. Golden graduates morning tea organised by QUT Alumni. Technology upgrades to the Mapping Sciences lab benefits 3-D learning experiences. Second and third-year students are undertaking Work Integrated Learning (WIL) over the summer vacation period. Final year students recently presented capstone project presentations at mini-conference in the Gibson Rooms overlooking a vibrant Southbank and sparkling Brisbane River. Discussion on end of year graduation ceremony held at QPAC.

EaD e Ciberespaço: um estudo sobre a Didática nos ambientes virtuais de aprendizagem e as possibilidades de construção de saberes

O presente trabalho de pesquisa investiga a didática, relacionando-a com as atividades educativas desenvolvidas intencionalmente nos ambientes virtuais de aprendizagem. O trabalho se desenvolve a partir do conceito de didática, compreendida como meios e mecanismos pelos quais se desenvolvem os processos de ensino-aprendizagem relacionados ao contexto sociociocultural. Utiliza-se como base teórica predominantemente, os conceitos de didática de Libâneo (1994, 2009, 2010, 2011, 2012), Candau (2003, 2011) e Pimenta (2011, 2013). Com relação ao contexto sociocultural utiliza-se Castells (2003, 2013), Lévy (1998, 2012), Lemos (2010) e Moore (2013). Investiga-se a sequência didática utilizada por duas instituições, através da coleta e análise das páginas web e dos planejamentos de curso disponibilizados nos AVA. Esta pesquisa situa-se no âmbito das pesquisas qualitativas e desta forma não houve uma estruturação rígida. Foi delineado um design mínimo para início do trabalho focando os aspectos da estruturação da aula virtual e dos elementos estruturais elencados por Libâneo. No decorrer da investigação foram adotados procedimentos de acordo com a realidade investigada. Observa-se que ambas as instituições apresentam uma sequência didática singular, com diferenças de concepção na sua elaboração. Percebe-se que, no ambiente online, a didática está sempre presente, embora tal qual no ambiente presencial, retratando as diferentes concepções de ensino.

Kształcenie zdalne w szkole wyższej – stan i perspektywy

Wydział Studiów Edukacyjnych

Modeling endogenous technological change for climate policy analysis

The approach used to model technological change in a climate policy model is a critical determinant of its results in terms of the time path of CO2 prices and costs required to achieve various emission reduction goals. We provide an overview of the different approaches used in the literature, with an emphasis on recent developments regarding endogenous technological change, research and development, and learning. Detailed examination sheds light on the salient features of each approach, including strengths, limitations, and policy implications. Key issues include proper accounting for the opportunity costs of climate-related knowledge generation, treatment of knowledge spillovers and appropriability, and the empirical basis for parameterizing technological relationships. No single approach appears to dominate on all these dimensions, and different approaches may be preferred depending on the purpose of the analysis, be it positive or normative. © 2008 Elsevier B.V. All rights reserved.

O processo de construção da Unesp Corporativa

The article presents São Paulo State University Corporate Education Program – UNESPCorp – whose target is to evolve the staff of institution in order of their professional improvement, using distance education technologies (D-learning). The UNESPCorp pilot project started with the Improvement in Bidding and Public Employment curse. The curse was taught on the second semester of 2012 and received 130 employees representing all UNESP campuses. The text was divided in two parts, the first part recovers historical context which introduces the Corporate University. The second part presents challenges and advances represented for the first version of course, even as its pedagogical structure of operation.

R&D in clean technology: A project choice model with learning

In this study, we investigate the qualitative and quantitative effects of an R&D subsidy for a clean technology and a Pigouvian tax on a dirty technology on environmental R&D when it is uncertain how long the research takes to complete. The model is formulated as an optimal stopping problem, in which the number of successes required to complete the R&D project is finite and learning about the probability of success is incorporated. We show that the optimal R&D subsidy with the consideration of learning is higher than that without it. We also find that an R&D subsidy performs better than a Pigouvian tax unless suppliers have sufficient incentives to continue cost-reduction efforts after the new technology success-fully replaces the old one. Moreover, by using a two-project model, we show that a uniform subsidy is better than a selective subsidy.

Learning-Based Fast Iterative Convergence of 3-D MoM via Eigen-AGMRES Method

Three-dimensional (3-D) full-wave electromagnetic simulation using method of moments (MoM) under the framework of fast solver algorithms like fast multipole method (FMM) is often bottlenecked by the speed of convergence of the Krylov-subspace-based iterative process. This is primarily because the electric field integral equation (EFIE) matrix, even with cutting-edge preconditioning techniques, often exhibits bad spectral properties arising from frequency or geometry-based ill-conditioning, which render iterative solvers slow to converge or stagnate occasionally. In this communication, a novel technique to expedite the convergence of MoMmatrix solution at a specific frequency is proposed, by extracting and applying Eigen-vectors from a previously solved neighboring frequency in an augmented generalized minimum residual (AGMRES) iterative framework. This technique can be applied in unison with any preconditioner. Numerical results demonstrate up to 40% speed-up in convergence using the proposed Eigen-AGMRES method.

Robert Heinich, Michael Molenda, James D. Russell, Sharon E. Smaldino, Instructional Media and Technologies for Learning, Prentice-Hall, Inc., Englewood Cliffs, New Jersey 1996, ss. 446. Steven Hackbarth, The Educational Technology Handbook. A Comprehensive Guide, Educational Technology Publications Inc., Englewood Cliffs, New Jersey 1996, ss. 351

Recenzje i sprawozdania z książek

A Self-Organizing Neural Network for Learning a Body-Centered Invariant Representation of 3-D Target Position

This paper describes a self-organizing neural network that rapidly learns a body-centered representation of 3-D target positions. This representation remains invariant under head and eye movements, and is a key component of sensory-motor systems for producing motor equivalent reaches to targets (Bullock, Grossberg, and Guenther, 1993).

Neural Representations for Sensory-Motor Control, III: Learning a Body-Centered Representation of 3-D Target Position

A neural model is described of how the brain may autonomously learn a body-centered representation of 3-D target position by combining information about retinal target position, eye position, and head position in real time. Such a body-centered spatial representation enables accurate movement commands to the limbs to be generated despite changes in the spatial relationships between the eyes, head, body, and limbs through time. The model learns a vector representation--otherwise known as a parcellated distributed representation--of target vergence with respect to the two eyes, and of the horizontal and vertical spherical angles of the target with respect to a cyclopean egocenter. Such a vergence-spherical representation has been reported in the caudal midbrain and medulla of the frog, as well as in psychophysical movement studies in humans. A head-centered vergence-spherical representation of foveated target position can be generated by two stages of opponent processing that combine corollary discharges of outflow movement signals to the two eyes. Sums and differences of opponent signals define angular and vergence coordinates, respectively. The head-centered representation interacts with a binocular visual representation of non-foveated target position to learn a visuomotor representation of both foveated and non-foveated target position that is capable of commanding yoked eye movementes. This head-centered vector representation also interacts with representations of neck movement commands to learn a body-centered estimate of target position that is capable of commanding coordinated arm movements. Learning occurs during head movements made while gaze remains fixed on a foveated target. An initial estimate is stored and a VOR-mediated gating signal prevents the stored estimate from being reset during a gaze-maintaining head movement. As the head moves, new estimates arc compared with the stored estimate to compute difference vectors which act as error signals that drive the learning process, as well as control the on-line merging of multimodal information.

Fast Learning VIEWNET Architectures for Recognizing 3-D Objects from Multiple 2-D Views

The recognition of 3-D objects from sequences of their 2-D views is modeled by a family of self-organizing neural architectures, called VIEWNET, that use View Information Encoded With NETworks. VIEWNET incorporates a preprocessor that generates a compressed but 2-D invariant representation of an image, a supervised incremental learning system that classifies the preprocessed representations into 2-D view categories whose outputs arc combined into 3-D invariant object categories, and a working memory that makes a 3-D object prediction by accumulating evidence from 3-D object category nodes as multiple 2-D views are experienced. The simplest VIEWNET achieves high recognition scores without the need to explicitly code the temporal order of 2-D views in working memory. Working memories are also discussed that save memory resources by implicitly coding temporal order in terms of the relative activity of 2-D view category nodes, rather than as explicit 2-D view transitions. Variants of the VIEWNET architecture may also be used for scene understanding by using a preprocessor and classifier that can determine both What objects are in a scene and Where they are located. The present VIEWNET preprocessor includes the CORT-X 2 filter, which discounts the illuminant, regularizes and completes figural boundaries, and suppresses image noise. This boundary segmentation is rendered invariant under 2-D translation, rotation, and dilation by use of a log-polar transform. The invariant spectra undergo Gaussian coarse coding to further reduce noise and 3-D foreshortening effects, and to increase generalization. These compressed codes are input into the classifier, a supervised learning system based on the fuzzy ARTMAP algorithm. Fuzzy ARTMAP learns 2-D view categories that are invariant under 2-D image translation, rotation, and dilation as well as 3-D image transformations that do not cause a predictive error. Evidence from sequence of 2-D view categories converges at 3-D object nodes that generate a response invariant under changes of 2-D view. These 3-D object nodes input to a working memory that accumulates evidence over time to improve object recognition. ln the simplest working memory, each occurrence (nonoccurrence) of a 2-D view category increases (decreases) the corresponding node's activity in working memory. The maximally active node is used to predict the 3-D object. Recognition is studied with noisy and clean image using slow and fast learning. Slow learning at the fuzzy ARTMAP map field is adapted to learn the conditional probability of the 3-D object given the selected 2-D view category. VIEWNET is demonstrated on an MIT Lincoln Laboratory database of l28x128 2-D views of aircraft with and without additive noise. A recognition rate of up to 90% is achieved with one 2-D view and of up to 98.5% correct with three 2-D views. The properties of 2-D view and 3-D object category nodes are compared with those of cells in monkey inferotemporal cortex.