A cooperar é que se aprende?: a aprendizagem cooperativa e educação intercultural: um contributo na construção da autonomia do aluno

Relatório de estágio de mestrado em Ensino de Inglês e Espanhol no 3º Ciclo do Ensino Básico e Ensino Secundário

L' Aprenentatge basat en problemes a través de casos clínics simulats. Una proposta metodològica de disseny i avaluació docent

RESUM Les exigències actuals de la professió de d’infermeria requereixen que la docència vagi orientada a interrelacionar els diferents rols a desenvolupar enla pràctica diària, per adquirir experiència en l’aprenentatge i així augmentar la qualitat de les cures d’infermeria. Per assolir aquest objectiu és important l’aprenentatge basat enproblemes. Aquest pretén en primer lloc que els estudiants aprenguin allò que permet desenvolupar-se enla vida professional de la manera més natural possible a partir d’una idea clara i profunda de l’evidència sobre la que s’ha d’actuar. Amb aquesta finalitat es vandissenyar casos clínics amb uns objectius que requerien la integració de coneixements, actituds i valors, en diferents fases a desenvolupar en un període de temps predeterminat. També ens vam proposar una estratègia docent que permetés a l’estudiant incorporar el coneixement científic que dóna suport a la pràctica assistencial per aproximar teoria i pràctica. Es pretén que els estudiants busquin una resposta basada en la millor evidència científica disponible, per prendre una decisió respecte a les cures del pacient. Els objectius de l’estudi són: Avaluar globalment l’aprenentatge basat en la simulació de casos Avaluar com els estudiants valoren la integració del model d’infermeria i del procés d’atenció en l’aprenentatge basat en la simulació de casos. Valorar les sensacions percebudes per l’estudiant durant la simulació del cas. Valorar l’actitud d el’estudiant en relació a la incorporació de l’evidència científica per una millora en la pràctica clínica. Avaluar el grau de dificultat manifestat per l’estudiant en relació al procés de documentació. Avaluar la idonietat de l’argumentació i la decisió de l’estudiant a la pregunta formulada en el cas clínic. Metodologia: L’assignatura d’Infermeria Medicoquirúrgica. Adult I del Departament d’Infermeria de la Universitat de Vic, va iniciar una experiència d’aprenentatge basat en la resolució de problemes, amb estudiants de 2on curs. Les professores responsables dels seminaris van realitzar una avaluació de l’experiència a través d’una enquesta. Aquesta es responia al cap d’un mes de la simulació al laboratori, quan es contrastaven els resultats obtinguts en aquesta entre professores i estudiants després de visualitzar la gravació feta durant el mateix. En el context del seminari de simulació de casos, es va introduir una pregunta/problema, a partir de la que els estudiants, en grup, havien de documentar-se amb el suport d’una guia. Per valorar l’actitud davant aquesta pregunta/problema es va dissenyar un qustionari tipus Likert. L’avaluació del grau de dificultat s’ha registrat a través d’unes escales de puntuació. Per a l’avaluació de la decisió presa, es van valorar les síntesis resum entregades en els treballs escrits pels diferents grups. Resultats: La realització de la simulació en el laboratori va ser avaluada per un alt percentatge d’estudiants (68,8%) amb puntuacions entre 6 i 8 mentre que un 26,6% la van situar en tre 9 i 10, només un 4,7 % la van puntuar amb 5. La integració del model d’infermeria va ser valorada pel 86% amb una puntuació entre 7 i 10. La valoració global de la simulació va ser qualificada pels estudiants amb una puntuació de 8 (34,4%) seguida d’un 28,1% amb una consideració de 7. Un 7,2% van puntuar entre 9 i 10. El 93,3% van assegurar que conèixer les fonts documentals els serviria per millorar l’assistència, el 86,7% esperen obtenir arguments sòlids respecte les seves desicions si la documentació consultada és de qualitat. Un 77,8% dels estudiants consideren estar més satisfets al saber incorporar la presa de decisions basada en evidències. Respecte el grau de dificultat en el procés de documentació la dificultat més gran la presenten en com buscar en les bases de dades de referències bibliogràfiques. Conclusions: L’aprenentatge dels estudiants a través de la simulació de casos és una estratègia vàlida que l’estudiant valora positivament al mateix temps que permet desenvolupar habilitats per a la pràctica professional. L’estratègia docent dissenyada per integrar les evidències en la presa de decisions es considera positiva, no obstant, després d’analitzar els resultats, s’han de modificar alguns aspectes per a la seva millora; tutoritzar per a millorar el procés de documentació i incidir més en la crítica i reflexió, de manera que les troballes de la investigació siguin canalitzades cap a la pràctica.

L'aprenentatge basat en problemes (PBL) en la regulació del metabolisme. Desenvolupament del portal per a l'intercanvi d'experiències en PBL en ciències biomèdiques

L’aprenentatge basat en problemes està en fase experimental en tot el món i és objecte d’anàlisi i reflexió en moltes reunions internacionals. Tanmateix, no hi ha massa feina feta en aquesta direcció en el nostre camp més proper. Hem elaborat problemes per l’aprenentatge de la Regulació del Metabolisme i els hem incorporat a un porta virtual (http://www.ub.edu/GID-BBM). La finalitat d’aquesta estratègia és que mitjançant l’aprenentatge basat en problemes reals o simulacions de problemes reals s’aconsegueixi motivar l’alumnat a treballar de forma continuada durant tot el curs. La millora dels resultats acadèmics haurà de ser la conseqüència lògica d’aquest treball. La finalitat última del projecte que hem desenvolupat és preparar l’alumnat per la seva futura activitat professional a on serà molt important i valorat la seva capacitat de resposta davant de diferents problemes

Evolution of decision-making and learning under fluctuating social environments

The capacity to learn to associate sensory perceptions with appropriate motor actions underlies the success of many animal species, from insects to humans. The evolutionary significance of learning has long been a subject of interest for evolutionary biologists who emphasize the bene¬fit yielded by learning under changing environmental conditions, where it is required to flexibly switch from one behavior to another. However, two unsolved questions are particularly impor¬tant for improving our knowledge of the evolutionary advantages provided by learning, and are addressed in the present work. First, because it is possible to learn the wrong behavior when a task is too complex, the learning rules and their underlying psychological characteristics that generate truly adaptive behavior must be identified with greater precision, and must be linked to the specific ecological problems faced by each species. A framework for predicting behavior from the definition of a learning rule is developed here. Learning rules capture cognitive features such as the tendency to explore, or the ability to infer rewards associated to unchosen actions. It is shown that these features interact in a non-intuitive way to generate adaptive behavior in social interactions where individuals affect each other's fitness. Such behavioral predictions are used in an evolutionary model to demonstrate that, surprisingly, simple trial-and-error learn¬ing is not always outcompeted by more computationally demanding inference-based learning, when population members interact in pairwise social interactions. A second question in the evolution of learning is its link with and relative advantage compared to other simpler forms of phenotypic plasticity. After providing a conceptual clarification on the distinction between genetically determined vs. learned responses to environmental stimuli, a new factor in the evo¬lution of learning is proposed: environmental complexity. A simple mathematical model shows that a measure of environmental complexity, the number of possible stimuli in one's environ¬ment, is critical for the evolution of learning. In conclusion, this work opens roads for modeling interactions between evolving species and their environment in order to predict how natural se¬lection shapes animals' cognitive abilities. - La capacité d'apprendre à associer des sensations perceptives à des actions motrices appropriées est sous-jacente au succès évolutif de nombreuses espèces, depuis les insectes jusqu'aux êtres hu¬mains. L'importance évolutive de l'apprentissage est depuis longtemps un sujet d'intérêt pour les biologistes de l'évolution, et ces derniers mettent l'accent sur le bénéfice de l'apprentissage lorsque les conditions environnementales sont changeantes, car dans ce cas il est nécessaire de passer de manière flexible d'un comportement à l'autre. Cependant, deux questions non résolues sont importantes afin d'améliorer notre savoir quant aux avantages évolutifs procurés par l'apprentissage. Premièrement, puisqu'il est possible d'apprendre un comportement incorrect quand une tâche est trop complexe, les règles d'apprentissage qui permettent d'atteindre un com¬portement réellement adaptatif doivent être identifiées avec une plus grande précision, et doivent être mises en relation avec les problèmes écologiques spécifiques rencontrés par chaque espèce. Un cadre théorique ayant pour but de prédire le comportement à partir de la définition d'une règle d'apprentissage est développé ici. Il est démontré que les caractéristiques cognitives, telles que la tendance à explorer ou la capacité d'inférer les récompenses liées à des actions non ex¬périmentées, interagissent de manière non-intuitive dans les interactions sociales pour produire des comportements adaptatifs. Ces prédictions comportementales sont utilisées dans un modèle évolutif afin de démontrer que, de manière surprenante, l'apprentissage simple par essai-et-erreur n'est pas toujours battu par l'apprentissage basé sur l'inférence qui est pourtant plus exigeant en puissance de calcul, lorsque les membres d'une population interagissent socialement par pair. Une deuxième question quant à l'évolution de l'apprentissage concerne son lien et son avantage relatif vis-à-vis d'autres formes plus simples de plasticité phénotypique. Après avoir clarifié la distinction entre réponses aux stimuli génétiquement déterminées ou apprises, un nouveau fac¬teur favorisant l'évolution de l'apprentissage est proposé : la complexité environnementale. Un modèle mathématique permet de montrer qu'une mesure de la complexité environnementale - le nombre de stimuli rencontrés dans l'environnement - a un rôle fondamental pour l'évolution de l'apprentissage. En conclusion, ce travail ouvre de nombreuses perspectives quant à la mo¬délisation des interactions entre les espèces en évolution et leur environnement, dans le but de comprendre comment la sélection naturelle façonne les capacités cognitives des animaux.

The Value of Imperfection : the Wabi-Sabi Principle in Aesthetics and Learning

OER-based learning has the potential to overcome many shortcomings and problems of traditional education. It is not hampered by IP restrictions; can depend on collaborative, cumulative, iterative refinement of resources; and the digital form provides unprecedented flexibility with respect to configuration and delivery. The OER community is a progressive group of educators and learners with decades of learning research to draw from, who know that we must prepare learners for an evolving and diverse reality. Despite this OER tends to replicate the unsuccessful characteristics of traditional education. To remedy this we may need to remember the importance of imperfection, mistakes, problems, disagreement, and the incomplete for engaged learning, and relinquish our notions of perfection, acknowledging that learners learn differently and we need diverse learners. We must stretch our perceptions of quality and provide mechanisms for engaging the incredible pool of educators globally to fulfill the promise of inclusive education.

Guía de implantación del aprendizaje a través de la simulación y las TICs en los centros sanitarios

Este documento forma parte del proyecto Fomento de las TIC para mejorar el aprendizaje a través de simulación en centros de salud (SIMBASE). Implementation Handbook for Simulation and ICT-Based Learning in Training nad Healthcare Centres (Versión en inglés disponible en http://www.simbase.co/results/)

Hoja de ruta para la implantación y difusión del aprendizaje a través de la simulación para responsables y gestores de las políticas de salud y educación

Este documento forma parte del proyecto Fomento de las TIC para mejorar el aprendizaje a través de simulación en centros de salud (SIMBASE). Roadmap for the implementation and dissemination of simulation-based learning for health and education directors and public officer holders (Versión en inglés disponible en http://www.simbase.co/results/)

Evaluation of an online, case-based interactive approach to teaching pathophysiology

AIM: The aim of this study was to evaluate a new pedagogical approach in teaching fluid, electrolyte and acid-base pathophysiology in undergraduate students. METHODS: This approach comprises traditional lectures, the study of clinical cases on the web and a final interactive discussion of these cases in the classroom. When on the web, the students are asked to select laboratory tests that seem most appropriate to understand the pathophysiological condition underlying the clinical case. The percentage of students having chosen a given test is made available to the teacher who uses it in an interactive session to stimulate discussion with the whole class of students. The same teacher used the same case studies during 2 consecutive years during the third year of the curriculum. RESULTS: The majority of students answered the questions on the web as requested and evaluated positively their experience with this form of teaching and learning. CONCLUSIONS: Complementing traditional lectures with online case-based studies and interactive group discussions represents, therefore, a simple means to promote the learning and the understanding of complex pathophysiological mechanisms. This simple problem-based approach to teaching and learning may be implemented to cover all fields of medicine.

LdShake: learning design solutions sharing and co-edition

Two important challenges that teachers are currently facing are the sharing and the collaborative authoring of their learning design solutions, such as didactical units and learning materials. On the one hand, there are tools that can be used for the creation of design solutions and only some of them facilitate the co-edition. However, they do not incorporate mechanisms that support the sharing of the designs between teachers. On the other hand, there are tools that serve as repositories of educational resources but they do not enable the authoring of the designs. In this paper we present LdShake, a web tool whose novelty is focused on the combined support for the social sharing and co-edition of learning design solutions within communities of teachers. Teachers can create and share learning designs with other teachers using different access rights so that they can read, comment or co-edit the designs. Therefore, each design solution is associated to a group of teachers able to work on its definition, and another group that can only see the design. The tool is generic in that it allows the creation of designs based on any pedagogical approach. However, it can be particularized in instances providing pre-formatted designs structured according to a specific didactic method (such as Problem-Based Learning, PBL). A particularized LdShake instance has been used in the context of Human Biology studies where teams of teachers are required to work together in the design of PBL solutions. A controlled user study, that compares the use of a generic LdShake and a Moodle system, configured to enable the creation and sharing of designs, has been also carried out. The combined results of the real and controlled studies show that the social structure, and the commenting, co-edition and publishing features of LdShake provide a useful, effective and usable approach for facilitating teachers' teamwork.

Reusing IMS-LD formalized best practices in collaborative learning structuring

Designs of CSCL (Computer Supported Collaborative Learning)activities should be flexible, effective and customizable toparticular learning situations. On the other hand, structureddesigns aim to create favourable conditions for learning. Thus,this paper proposes the collection of representative and broadlyaccepted (best practices) structuring techniques in collaborative learning. With the aim of establishing a conceptual common ground among collaborative learning practitioners and softwaredevelopers, and reusing the expertise that best practicesrepresent, the paper also proposes the formulation of these techniques as patterns: the so-called CLFPs (CollaborativeLearning Flow Patterns). To formalize these patterns, we havechosen the educational modelling language IMS Learning Design (IMS-LD). IMS-LD has the capability to specify many of the collaborative characteristics of the CLFPs. Nevertheless, the language bears limited capability for describing the services that mediate interactions within a learning activity and the specification of temporal or rotated roles. This analysis isdiscussed in the paper, as well as our approaches towards thedevelopment of a system capable of integrating tools using IMSLDscripts and a CLFP-based Learning Design authoring tool.

Teaching evidence-based management with a focus on producing local evidence

We present an approach to teaching evidence-based management (EBMgt) that trains future managers how to produce local evidence. Local evidence is causally interpretable data, collected on-site in companies to address a specific business problem. Our teaching method is a variant of problem-based learning, a method originally developed to teach evidence-based medicine. Following this method, students learn an evidence-based problem-solving cycle for addressing actual business cases. Executing this cycle, students use and produce scientific evidence through literature searches and the design of local, experimental tests of causal hypotheses. We argue the value of teaching EBMgt with a focus on producing local evidence, how it can be taught, and what can be taught. We conclude by outlining our contribution to the literature on teaching EBMgt and by discussing limitations of our approach.

Oscillations, phase-of-firing coding, and spike timing-dependent plasticity: an efficient learning scheme

Recent experiments have established that information can be encoded in the spike times of neurons relative to the phase of a background oscillation in the local field potential—a phenomenon referred to as “phase-of-firing coding” (PoFC). These firing phase preferences could result from combining an oscillation in the input current with a stimulus-dependent static component that would produce the variations in preferred phase, but it remains unclear whether these phases are an epiphenomenon or really affect neuronal interactions—only then could they have a functional role. Here we show that PoFC has a major impact on downstream learning and decoding with the now well established spike timing-dependent plasticity (STDP). To be precise, we demonstrate with simulations how a single neuron equipped with STDP robustly detects a pattern of input currents automatically encoded in the phases of a subset of its afferents, and repeating at random intervals. Remarkably, learning is possible even when only a small fraction of the afferents (~10%) exhibits PoFC. The ability of STDP to detect repeating patterns had been noted before in continuous activity, but it turns out that oscillations greatly facilitate learning. A benchmark with more conventional rate-based codes demonstrates the superiority of oscillations and PoFC for both STDP-based learning and the speed of decoding: the oscillation partially formats the input spike times, so that they mainly depend on the current input currents, and can be efficiently learned by STDP and then recognized in just one oscillation cycle. This suggests a major functional role for oscillatory brain activity that has been widely reported experimentally.

Marketing education, distance learning and hypermedia : teaching 'current issues in marketing' in a virtual campus

This article reports on a project at the Universitat Oberta de Catalunya (UOC: The Open University of Catalonia, Barcelona) to develop an innovative package of hypermedia-based learning materials for a new course entitled 'Current Issues in Marketing'. The UOC is a distance university entirely based on a virtual campus. The learning materials project was undertaken in order to benefit from the advantages which new communication technologies offer to the teaching of marketing in distance education. The article reviews the main issues involved in incorporating new technologies in learning materials, the development of the learning materials, and their functioning within the hypermedia based virtual campus of the UOC. An empirical study is then carried out in order to evaluate the attitudes of students to the project. Finally, suggestions for improving similar projects in the future are put forward.

Improving Searching and Browsing Capabilities of Learning Object Repositories

Learning object repositories are a basic piece of virtual learning environments used for content management. Nevertheless, learning objects have special characteristics that make traditional solutions for content management ine ective. In particular, browsing and searching for learning objects cannot be based on the typical authoritative meta-data used for describing content, such as author, title or publicationdate, among others. We propose to build a social layer on top of a learning object repository, providing nal users with additional services fordescribing, rating and curating learning objects from a teaching perspective. All these interactions among users, services and resources can be captured and further analyzed, so both browsing and searching can be personalized according to user pro le and the educational context, helping users to nd the most valuable resources for their learning process. In this paper we propose to use reputation schemes and collaborative filtering techniques for improving the user interface of a DSpace based learning object repository.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.