The role of lifelong learning (LLL) in the creation of a european knowledge- based society

This chapter appears in Encyclopaedia of Human Resources Information Systems: Challenges in e-HRM edited by Torres-Coronas, T. and Arias-Oliva, M. Copyright 2009, IGI Global, www.igi-global.com. Posted by permission of the publisher. URL:http://www.igi-pub.com/reference/details.asp?id=7737

The development of a knowledge-based society - Challenges for e-learning and adult students in higher education

This chapter appears in Encyclopaedia of Distance Learning 2nd Edition edit by Rogers, P.; Berg, Gary; Boettecher, Judith V.; Howard, Caroline; Justice, Lorraine; Schenk, Karen D.. Copyright 2009, IGI Global, www.igi-global.com. Posted by permission of the publisher. URL: http://www.igi-global.com/reference/ details.asp?ID=9703&v=tableOfContents

O desenvolvimento da compet��ncia intercultural atrav��s do Task-Based learning na aula de l��ngua estrangeira

Relat��rio de Est��gio apresentado para cumprimento dos requisitos necess��rios �� obten����o do grau de Mestre em Ensino de Ingl��s e de L��ngua Estrangeira (Franc��s) no 3.�� Ciclo do Ensino B��sico e no Ensino Secund��rio

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

A constru����o de um curr��culo de project-based learning: o curr��culo ideal e o curr��culo formal

O objetivo deste trabalho �� apresentar os resultados da an��lise das concep����es de dois protagonistas de uma reforma curricular que est�� sendo implementada numa escola de engenharia. A principal caracter��stica do novo curr��culo �� o uso de projetos e oficinas como atividades complementares a serem realizadas pelos estudantes. As atividades complementares acontecer��o em paralelo ao trabalho realizado nas disciplinas sem que haja uma rela����o de interdisciplinaridade. O novo curr��culo est�� sendo implantado desde fevereiro de 2015. Segundo Pacheco (2005) h�� dois momentos, dentre outros, no processo de mudan��a curricular, o curr��culo ���ideal���, determinado por dimens��es epistemol��gica, pol��tica, econ��mica, ideol��gica, t��cnica, est��tica, e hist��rica e, que recebe influ��ncia direta daquele que idealiza e cria o novo curr��culo e, o curr��culo ���formal��� que se traduz na pr��tica implementada na escola. S��o essas duas etapas estudadas nesta pesquisa. Para isso ser��o considerados como fontes de dados dois protagonistas, um mais ligado �� concep����o do curr��culo e outro da sua implementa����o, a partir dos quais se busca compreender as motiva����es, cren��as e percep����es que, por sua vez, determinam a reforma curricular. Entrevistas semiestruturadas foram utilizadas como t��cnica de pesquisa, com o prop��sito de se entender a g��nese da proposta e as mudan��as entre essas duas etapas. Os dados revelam que mudan��as aconteceram desde a idealiza����o at�� a formaliza����o do curr��culo, motivadas por demandas do processo de implementa����o, revela ainda diferen��as na vis��o de curr��culo e a motiva����o para romper com padr��es na forma����o de engenheiros no Brasil.

Gamification e game-based learning: uma abordagem l��dica �� aprendizagem

Relat��rio de est��gio de mestrado em Ensino de Inform��tica

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletr��nica e de Computadores

O desenvolvimento do pensamento abstrato atrav��s de game-based learning e do Scratch

Relat��rio de est��gio de mestrado em Ensino de Inform��tica

An��lisis comparativo entre actividades de aprendizaje dise��adas con Estudio de Casos y Aprendizaje Basado en Problemas, y actividades de tipo tradicional, como dispositivos did��cticos en Educaci��n a Distancia. Comparative analysis of learning activities designed with Problem Based Learning and Case Study approaches, and activities designed with traditional methods, in Distance Education.

Identificaci��n y caracterizaci��n del problema: El problema que gu��a este proyecto, pretende dar respuesta a interrogantes tales como: ��De qu�� modo el tipo de actividades que se dise��an, se constituyen en dispositivos posibilitadores de la comprensi��n de los temas propios de cada asignatura, por parte de los alumnos? A partir de esta pregunta, surge la siguiente: Al momento de resolver las actividades, ��qu�� estrategias cognitivas ponen en juego los estudiantes? y ��cu��les de ellas favorecen procesos de construcci��n del conocimiento? Hip��tesis: - Las asignaturas cuyas actividades est��n elaboradas bajo la metodolog��a de Aprendizaje Basado en Problemas y Estudio de Casos, propician aprendizajes significativos por parte de los estudiantes. - Las actividades elaboradas bajo la metodolog��a del Aprendizaje Basado en Problemas y el Estudio de Casos requieren de procesos cognitivos m��s complejos que los que se implementan en las de tipo tradicional. Objetivo: - Identificar el impacto que tienen las actividades de aprendizaje de tipo tradicional y las elaboradas bajo la metodolog��a de Aprendizaje Basado en Problemas y Estudio de Casos, en el aprendizaje de los alumnos. Materiales y M��todos: a) An��lisis de las actividades de aprendizaje del primero y segundo a��o de la carrera de Abogac��a, bajo lamodalidad a Distancia. b) Entrevistas tanto a docentes contenidistas como as�� tambi��n a los tutores. c) Encuestas y entrevistas a los alumnos. Resultados esperados: Se pretende confirmar que las actividades de aprendizaje, dise��adas bajo la metodolog��a del Aprendizaje Basado en Problemas y el Estudio de Casos, promueven aprendizajes significativos en los alumnos. Importancia del proyecto y pertinencia: La relevancia del presente proyecto se podr��a identificar a trav��s de dos grandes variables vinculadas entre s��: la relacionada con el dispositivo did��ctico (estrategias implementadas por los alumnos) y la referida a lo institucional (car��cter innovador de la propuesta de ense��anza y posibilidad de extenderla a otras c��tedras). El presente proyecto pretende implementar mejoras en el dise��o de las actividades de aprendizaje, a fin de promover en los alumnos la generaci��n de ideas y soluciones responsables y el desarrollo de su capacidad anal��tica y reflexiva.

Development of a data acquisition system to characterise sustainable energy technologies and to support Web-Based learning (DAQ-WBL)

Driven by concerns about rising energy costs, security of supply and climate change a new wave of Sustainable Energy Technologies (SET���s) have been embraced by the Irish consumer. Such systems as solar collectors, heat pumps and biomass boilers have become common due to government backed financial incentives and revisions of the building regulations. However, there is a deficit of knowledge and understanding of how these technologies operate and perform under Ireland���s maritime climate. This AQ-WBL project was designed to address both these needs by developing a Data Acquisition (DAQ) system to monitor the performance of such technologies and a web-based learning environment to disseminate performance characteristics and supplementary information about these systems. A DAQ system consisting of 108 sensors was developed as part of Galway-Mayo Institute of Technology���s (GMIT���s) Centre for the Integration of Sustainable EnergyTechnologies (CiSET) in an effort to benchmark the performance of solar thermal collectors and Ground Source Heat Pumps (GSHP���s) under Irish maritime climate, research new methods of integrating these systems within the built environment and raise awareness of SET���s. It has operated reliably for over 2 years and has acquired over 25 million data points. Raising awareness of these SET���s is carried out through the dissemination of the performance data through an online learning environment. A learning environment was created to provide different user groups with a basic understanding of a SET���s with the support of performance data, through a novel 5 step learning process and two examples were developed for the solar thermal collectors and the weather station which can be viewed at http://www.kdp 1 .aquaculture.ie/index.aspx. This online learning environment has been demonstrated to and well received by different groups of GMIT���s undergraduate students and plans have been made to develop it further to support education, awareness, research and regional development.

Towards effective research-paper recommender systems and user modeling based on mind maps

Magdeburg, Univ., Fak. f��r Informatik, Diss., 2015