Evolution of Various Library Instruction Strategies: Using Student Feedback to Create and Enhance Online Active Learning Assignments

This case study traces the evolution of library assignments for biological science students from paper-based workbooks in a blended (hands-on) workshop to blended learning workshops using online assignments to online active learning modules which are stand-alone without any face-to-face instruction. As the assignments evolved to adapt to online learning supporting materials in the form of PDFs (portable document format), screen captures and screencasting were embedded into the questions as teaching moments to replace face-to-face instruction. Many aspects of the evolution of the assignment were based on student feedback from evaluations, input from senior lab demonstrators and teaching assistants, and statistical analysis of the students’ performance on the assignment. Advantages and disadvantages of paper-based and online assignments are discussed. An important factor for successful online learning may be the ability to get assistance.

Avaluació de l'experiència pilot dels tallers d'estudi assistit de la UVic dins dels plans educatius d'entorn de Manlleu, Roda de Ter i Vic (curs 2006-2007)

Aquest treball de recerca ha consistit en realitzar el seguiment dels Tallers d'Estudi Assistit (TEA) de diferents poblacions de la comarca d'Osona, per tal de conèixer-los i avaluar-los. Els TEA consisteixen en una activitat extraescolar d'acompanyament en l'etapa educativa d'alumnes de cicle mitjà, cicle superior i secundària que no disposen d'un entorn favorabale per fer una correcte escolarització. La recerca estudia dues dimensions: per una banda analitzar com la Uvic assumeix la responsabilitat de la formació i seguiment dels estudiants que participen com a monitors en els TEA, i per l'altra, contextualitzar els Tallers d'Estudi Assistit com una eina dels Plans Educatius d'Entorn, per la igualtat d'oportunitats; així com valorar el treball en xarxa que els tallers representen. Amb l'objectiu d'avaluar el funcionament dels TEA, la formació dels monitors (estudiants de la UVic) i la implicació dels agents implicats en el projecte; així com també plantejar propostes de millora per a properes edicions dels TEA.

Estratégias midiáticas na aprendizagem do tema DST/AIDS: ações em rede para reduzir vulnerabilidades de adolescentes e jovens da comunidade de Mãe Luiza, Natal-RN

Youngsters and teenagers are still a very vulnerable group of DST/AIDS. In order to combat this vulnerability the community intervention project being developed in Mãe Luiza neighborhood in the city of Natal-RN, entitled Strengthening Community Action Network for Prevention in HIV/AIDS: knowledge and Intervene emerged, popularly known as Project Viva Mãe Luiza. The project develops workshops of educomunication whose approach involves the DST/AIDS subject with the following media: video, photography, and theater playbook. This research integrates the activities of the project and has as main objective to investigate how strategies and practices of media communication developed in Project Viva Mãe Luiza through workshops of educomunication, assisted learning for the prevention of DST/AIDS and contributed to the reduction of vulnerability to DST/AIDS among adolescents and young participants of the project residents of Mãe Luiza community. The methodological basis was based on intervention research, with the technique of gathering daily field data, literature and documentary, in-depth interviews and ethnographic observation. The qualitative analysis was based on the monitoring of video workshops, photography, theater and primer, respectively, crossed by transverse to the prevention of DST/AIDS, conducted between June 2012 and December 2013 issues. Interviews with eight multipliers, aiming to understand their perceptions of vulnerability, prevention, multiplication and use of media that were part of the project were conducted. The analyzes show that learning workshops educomunication community health repercussions both in the development of individual skills in communication as changing perceptions about the vulnerabilities to which they are exposed, the awareness about prevention at the individual and differentiated actions multiplication in the community

Um estudo da autonomia no contexto da metodologia das oficinas de aprendizagem

Pós-graduação em Educação para a Ciência - FC

Um estudo da autonomia no contexto da metodologia das oficinas de aprendizagem

Pós-graduação em Educação para a Ciência - FC

e-Math Workshops : a forum for exchanging experiences of mathematics e-learning at university level

We report here about a series of international workshops on e-learning of mathematics at university level, which have been jointly organized by the three publicly funded open universities in the Iberian Peninsula and which have taken place annually since 2009. The history, achievements and prospects for the future of this initiative will be addressed.

A shift from passive teaching at medical conferences to more interactive methods improves physician learning

Conferences that deliver interactive sessions designed to enhance physician participation, such as role play, small discussion groups, workshops, hands-on training, problem- or case-based learning and individualised training sessions, are effective for physician education.

Engaging with theories of dialogue and voice: Using Bakhtin as a framework to understand teaching and learning Indigenous Australian women's performance

In this paper I explore the Indigenous Australian women's performance classroom (hereafter ANTH2120) as a dialectic and discursive space where the location of possibility is opened for female Indigenous performers to enter into a dialogue from and between both non-Indigenous and Indigenous voices. The work of Bakhtin on dialogue serves as a useful standpoint for understanding the multiple speaking positions and texts in the ANTH2120 context. Bakhtin emphasizes performance, history, actuality and the openness of dialogue to provide an important framework for analysing multiple speaking positions and ways of making meaning through dialogue between shifting and differing subjectivities. I begin by briefly critiquing Bakhtin's "dialogic imagination" and consider the application and usefulness of concepts such as dialogism, heteroglossia and the utterance to understanding the ANTH2120 classroom as a polyphonic and discursive space. I then turn to an analysis of dialogue in the ANTH2120 classroom and primarily situate my gaze on an examination of the interactions that took place between the voices of myself as family/teacher/student and senior Yanyuwa women from the r e m o t e N o r t h e r n T e r r i t o r y A b o r i g i n a l c o m m u n i t y o f B o r r o l o o l a as family/performers/teachers. The 2000 and 2001 Yanyuwa women's performance workshops will be used as examples of the way power is constantly shifting in this dialogue to allow particular voices to speak with authority, and for others to remain silent as roles and relationships between myself and the Yanyuwa women change. Conclusions will be drawn regarding how my subject positions and white race privilege affect who speaks, who listens and on whose terms, and further, the efficacy of this pedagogical platform for opening up the location of possibility for Indigenous Australian women to play a powerful part in the construction of knowledges about women's performance traditions.

A utilização da plataforma Educast@fccn, como ferramenta de gravação de aulas no ambiente de e-learning português

Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.

Unlocking the technology-mediated learning process : insights and articulating actions for an institutional approach

This paper is part of the results from the project "Implementation Strategies and Development of an Open and Distance Education System for the University of the Azores" funded by the European Social Fund. http://hdl.handle.net/10400.3/2327

A construção de um currículo de project-based learning: o currículo ideal e o currículo formal

O objetivo deste trabalho é apresentar os resultados da análise das concepções de dois protagonistas de uma reforma curricular que está sendo implementada numa escola de engenharia. A principal característica do novo currículo é o uso de projetos e oficinas como atividades complementares a serem realizadas pelos estudantes. As atividades complementares acontecerão em paralelo ao trabalho realizado nas disciplinas sem que haja uma relação de interdisciplinaridade. O novo currículo está sendo implantado desde fevereiro de 2015. Segundo Pacheco (2005) há dois momentos, dentre outros, no processo de mudança curricular, o currículo “ideal”, determinado por dimensões epistemológica, política, econômica, ideológica, técnica, estética, e histórica e, que recebe influência direta daquele que idealiza e cria o novo currículo e, o currículo “formal” que se traduz na prática implementada na escola. São essas duas etapas estudadas nesta pesquisa. Para isso serão considerados como fontes de dados dois protagonistas, um mais ligado à concepção do currículo e outro da sua implementação, a partir dos quais se busca compreender as motivações, crenças e percepções que, por sua vez, determinam a reforma curricular. Entrevistas semiestruturadas foram utilizadas como técnica de pesquisa, com o propósito de se entender a gênese da proposta e as mudanças entre essas duas etapas. Os dados revelam que mudanças aconteceram desde a idealização até a formalização do currículo, motivadas por demandas do processo de implementação, revela ainda diferenças na visão de currículo e a motivação para romper com padrões na formação de engenheiros no Brasil.

Health equity audit - learning from practice briefing

This briefing provides a summary of learning from three workshops on HEA, and examples of completed or near-completed HEAs to illustrate these learning points. It is recognised that this experience is evolving.

A multicase study for the evaluation of a pattern-based visual design process for collaborative learning

Collage is a pattern-based visual design authoring tool for the creation of collaborative learning scripts computationally modelled with IMS Learning Design (LD). The pattern-based visual approach aims to provide teachers with design ideas that are based on broadly accepted practices. Besides, it seeks hiding the LD notation so that teachers can easily create their own designs. The use of visual representations supports both the understanding of the design ideas and the usability of the authoring tool. This paper presents a multicase study comprising three different cases that evaluate the approach from different perspectives. The first case includes workshops where teachers use Collage. A second case implies the design of a scenario proposed by a third-party using related approaches. The third case analyzes a situation where students follow a design created with Collage. The cross-case analysis provides a global understanding of the possibilities and limitations of the pattern-based visual design approach.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Open Educational Resources: an opportunity for virtual learning institutions

The Universitat Oberta de Catalunya (UOC, Open University of Catalonia) is involved inseveral research projects and educational activities related to the use of Open Educational Resources (OER). Some of the discussed issues in the concept of OER are research issues which are being tackled in two EC projects (OLCOS and SELF). Besides the research part, the UOC aims at developing a virtual centre for analysing and promoting the concept of OERin Europe in the sector of Higher and Further Education. The objectives are to makeinformation and learning services available to provide university management staff,eLearning support centres, faculty and learners with practical information required to create, share and re-use such interoperable digital content, tools and licensing schemes. In the realisation of these objectives, the main activities are the following: to provide organisationaland individual e-learning end-users with orientation; to develop perspectives and useful recommendations in the form of a medium-term Roadmap 2010 for OER in Higher and Further Education in Europe; to offer practical information and support services about how to create, share and re-use open educational content by means of tutorials, guidelines, best practices, and specimen of exemplary open e-learning content; to establish a larger group ofcommitted experts throughout Europe and other continents who not only share theirexpertise but also steer networking, workshops, and clustering efforts; and to foster and support a community of practice in open e-learning content know-how and experiences.