TutorGSI : aplicación de tecnologías de 'bots' a entornos LMS.

Número monográfico dedicado a las I Jorandas Telspain de Proyectos de I + D en Tecnologías para el Aprendizaje en España.Resumen basado en el de la publicación

An analysis of the moderating effects of age in the acceptance of Learning Management Systems. 'Análisis del efecto moderador de la edad en la aceptación de sistemas e-learning LMS'.

Resumen basado en el de la publicación

Uso de contenidos educativos digitales a trav??s de sistemas de gesti??n del aprendizaje (LMS) y su repercusi??n en el acto did??ctico comunicativo

Esta tesis doctoral estudia la naturaleza de los contenidos educativos digitales desde la perspectiva de su uso e integraci??n en el acto did??ctico-comunicativo mediante sistemas de gesti??n del aprendizaje (LMS). Se analizan las transformaciones que sufren los contenidos desde su concepci??n para operar a trav??s de un LMS; las funciones de los LMS que permiten y desarrollan la difusi??n de los contenidos; y la repercusi??n que estos fen??menos y factores tienen en el acto did??ctico-comunicativo. La aplicaci??n de una metodolog??a que combina las t??cnicas del an??lisis documental, el grupo de discusi??n de expertos en la materia, el an??lisis funcional se soluciones TIC para el aprendizaje y el cuestionario usuarios de contenidos digitales, arroja unos resultados que permiten la aproximaci??n a un modelo de optimizaci??n de la integraci??n de los elementos estudiados -contenidos educativos digitales, sistemas de gesti??n del aprendizaje y acto did??ctico comunicativo- en el contexto educativo espa??ol.

Modelo de dise??o instruccional semipresencial basado en proyectos a partir de un LMS y PLEs : integrando ambientes organizacionales y personales

Resumen basado en el de la publicaci??n

Ensino/Aprendizagem da estatística promovendo o pensamento crítico utilizando o fórum de uma LMS

A estatística nos dias de hoje está incorporada de uma forma generalizada no currículo da matemática no ensino básico e secundário e em diferentes cursos do ensino superior.Este interesse, não é exclusivo da comunidade de educação matemática, mas sim da sociedade em geral, pois a sua apropriação permite contribuir para um melhor espirito crítico sobre a informação e logo um exercicio de melhor cidadania. Esta experiência realizou-se no âmbito da Unidade Curricular de Introdução à Estatística da licenciatura em Educação Básica da Escola Superior de Educação Paula Frassinetti , a qual contou com a participação de 74 estudantes inscritos na unidade curricular.Tendo como referência as diretrizes para o ensino superior impulsionadas por o processo de Bolonha que apontam para a centralidade do estudante no processo autónomo de aprendizagem ao longo da vida implementamos uma metodologia de b-learning alicerçada na plataforma moodle usando o fórum de forma a potenciar o pensamento crítico.Do ponto de vista pedagógico, utilizamos o modelo Community of Inquiry desenvolvido por Garrison, Anderson e Archer.Os posts que lançamos para a discussão, eram notícias dos meios de comunicação fazendo um pequeno comentário de forma a fomentar o sentido crítico face ao modo como a informação é apresentada e a aptidão para ler e interpretar tabelas e gráficos à luz das situações a que dizem respeito, com o objetivo de desenvolver skills interpretativos e a literacia estatística, desenvolver a capacidade para comunicar estatisticamente e desenvolver disposições estatísticas úteis.Neste trabalho, apresentamos uma análise qualitativa e quantitativa dos vários indicadores que caracterizam a formação de futuros professores da educação básica em estatística,recolhendo os dados das interações do fórum, monitorizados com o software SNAPP e a análise dos mesmos com o Netdraw e SPSS.E ainda, a interpretabilidade de diversos fatores, de acordo com a estrutura e conceção do instrumento a respeito de como o estudante perceciona a presença cognitiva relativamente à construção do significado e compreensão da matéria da unidade curricular.Concluímos que a maioria dos estudantes apesar de saber calcular medidas de localização e dispersão, tem dificuldade em apresentar argumentos em que as explicite, pois ainda não conseguiu interpretar, interiorizar as medidas, para que possa inseri-los e articulá-los numa argumentação.

Variable step LMS algorithm using the accumulated instantaneous error concept

The convergence speed of the standard Least Mean Square adaptive array may be degraded in mobile communication environments. Different conventional variable step size LMS algorithms were proposed to enhance the convergence speed while maintaining low steady state error. In this paper, a new variable step LMS algorithm, using the accumulated instantaneous error concept is proposed. In the proposed algorithm, the accumulated instantaneous error is used to update the step size parameter of standard LMS is varied. Simulation results show that the proposed algorithm is simpler and yields better performance than conventional variable step LMS.

Use of the LMS adaptive signal processing technique to improve signal data rates from practical oil well logging equipment

The simulation and development work that has been undertaken to produce a signal equaliser used to improve the data rates from oil well logging instruments is presented. The instruments are lowered into the drill bore hole suspended by a cable which has poor electrical characteristics. The equaliser described in the paper corrects for the distortions that occur from the cable (dispersion and attenuation) with the result that the instrument can send data at 100 K.bits/second down its own suspension cable of 12 Km in length. The use of simulation techniques and tools were invaluable in generating a model for the distortions and proved to be a useful tool when site testing was not available.

An LMS style variable tap-length algorithm for structure adaptation

Searching for the optimum tap-length that best balances the complexity and steady-state performance of an adaptive filter has attracted attention recently. Among existing algorithms that can be found in the literature, two of which, namely the segmented filter (SF) and gradient descent (GD) algorithms, are of particular interest as they can search for the optimum tap-length quickly. In this paper, at first, we carefully compare the SF and GD algorithms and show that the two algorithms are equivalent in performance under some constraints, but each has advantages/disadvantages relative to the other. Then, we propose an improved variable tap-length algorithm using the concept of the pseudo fractional tap-length (FT). Updating the tap-length with instantaneous errors in a style similar to that used in the stochastic gradient [or least mean squares (LMS)] algorithm, the proposed FT algorithm not only retains the advantages from both the SF and the GD algorithms but also has significantly less complexity than existing algorithms. Both performance analysis and numerical simulations are given to verify the new proposed algorithm.

Convergence analysis of chip- and fractionally spaced LMS adaptive multiuser CDMA detectors

This paper analyzes the convergence behavior of the least mean square (LMS) filter when used in an adaptive code division multiple access (CDMA) detector consisting of a tapped delay line with adjustable tap weights. The sampling rate may be equal to or higher than the chip rate, and these correspond to chip-spaced (CS) and fractionally spaced (FS) detection, respectively. It is shown that CS and FS detectors with the same time-span exhibit identical convergence behavior if the baseband received signal is strictly bandlimited to half the chip rate. Even in the practical case when this condition is not met, deviations from this observation are imperceptible unless the initial tap-weight vector gives an extremely large mean squared error (MSE). This phenomenon is carefully explained with reference to the eigenvalues of the correlation matrix when the input signal is not perfectly bandlimited. The inadequacy of the eigenvalue spread of the tap-input correlation matrix as an indicator of the transient behavior and the influence of the initial tap weight vector on convergence speed are highlighted. Specifically, a initialization within the signal subspace or to the origin leads to very much faster convergence compared with initialization in the a noise subspace.

Performance analysis of the LMS blind minimum-output-energy CDMA detector

Adaptive filters used in code division multiple access (CDMA) receivers to counter interference have been formulated both with and without the assumption of training symbols being transmitted. They are known as training-based and blind detectors respectively. We show that the convergence behaviour of the blind minimum-output-energy (MOE) detector can be quite easily derived, unlike what was implied by the procedure outlined in a previous paper. The simplification results from the observation that the correlation matrix determining convergence performance can be made symmetric, after which many standard results from the literature on least mean square (LMS) filters apply immediately.

Variable step-size LMS blind CDMA multiuser detectors

Adaptive least mean square (LMS) filters with or without training sequences, which are known as training-based and blind detectors respectively, have been formulated to counter interference in CDMA systems. The convergence characteristics of these two LMS detectors are analyzed and compared in this paper. We show that the blind detector is superior to the training-based detector with respect to convergence rate. On the other hand, the training-based detector performs better in the steady state, giving a lower excess mean-square error (MSE) for a given adaptation step size. A novel decision-directed LMS detector which achieves the low excess MSE of the training-based detector and the superior convergence performance of the blind detector is proposed.

Seasonal cycles and variability of O3 and H2O in the UT/LMS during SPURT

Airborne high resolution in situ measurements of a large set of trace gases including ozone (O3) and total water (H2O) in the upper troposphere and the lowermost stratosphere (UT/LMS) have been performed above Europe within the SPURT project. SPURT provides an extensive data coverage of the UT/LMS in each season within the time period between November 2001 and July 2003. In the LMS a distinct spring maximum and autumn minimum is observed in O3, whereas its annual cycle in the UT is shifted by 2–3 months later towards the end of the year. The more variable H2O measurements reveal a maximum during summer and a minimum during autumn/winter with no phase shift between the two atmospheric compartments. For a comprehensive insight into trace gas composition and variability in the UT/LMS several statistical methods are applied using chemical, thermal and dynamical vertical coordinates. In particular, 2-dimensional probability distribution functions serve as a tool to transform localised aircraft data to a more comprehensive view of the probed atmospheric region. It appears that both trace gases, O3 and H2O, reveal the most compact arrangement and are best correlated in the view of potential vorticity (PV) and distance to the local tropopause, indicating an advanced mixing state on these surfaces. Thus, strong gradients of PV seem to act as a transport barrier both in the vertical and the horizontal direction. The alignment of trace gas isopleths reflects the existence of a year-round extra-tropical tropopause transition layer. The SPURT measurements reveal that this layer is mainly affected by stratospheric air during winter/spring and by tropospheric air during autumn/summer. Normalised mixing entropy values for O3 and H2O in the LMS appear to be maximal during spring and summer, respectively, indicating highest variability of these trace gases during the respective seasons.

Improving the performance of the LMS and RLS algorithms for adaptive equalizer

In this paper, we present the experiment results of three adaptive equalization algorithms: least-mean-square (LMS) algorithm, discrete cosine transform-least mean square (DCT-LMS) algorithm, and recursive least square (RLS) algorithm. Based on the experiments, we obtained that the convergence rate of LMS is slow; the convergence rate of RLS is great faster while the computational price is expensive; the performance of that two parameters of DCT-LMS are between the previous two algorithms, but still not good enough. Therefore we will propose an algorithm based on H2 in a coming paper to solve the problems.

Stability and convergence analysis of transform-domain LMS adaptive filters with second-order autoregressive process

In this paper, the stability and convergence properties of the class of transform-domain least mean square (LMS) adaptive filters with second-order autoregressive (AR) process are investigated. It is well known that this class of adaptive filters improve convergence property of the standard LMS adaptive filters by applying the fixed data-independent orthogonal transforms and power normalization. However, the convergence performance of this class of adaptive filters can be quite different for various input processes, and it has not been fully explored. In this paper, we first discuss the mean-square stability and steady-state performance of this class of adaptive filters. We then analyze the effects of the transforms and power normalization performed in the various adaptive filters for both first-order and second-order AR processes. We derive the input asymptotic eigenvalue distributions and make comparisons on their convergence performance. Finally, computer simulations on AR process as well as moving-average (MA) process and autoregressive-moving-average (ARMA) process are demonstrated for the support of the analytical results.