Análisis vivencial de la interacción educativa para la determinación de condiciones espaciales de aula en Uruguay

La arquitectura educacional es un soporte crucial para lograr educación de calidad. Sin embargo, su diseño actual presenta una uniformidad formal basada en condiciones constructivas de hace un siglo con escasas referencias a cambios sociales y particularidades funcionales. Esto es notorio en el espacio de aula donde forma y dimensión son parámetros incuestionables por parte de los responsables de su diseño como por aquellos que lo usan. Este artículo presenta una metodología de análisis vivencial aplicada al aula escolar para diagnosticar la relación alumno - maestro que permita determinar características arquitectónicas que contribuyan a una mejor interacción. En aulas uruguayas se analizan: información fotográfica obtenida in situ, registros video-fotográficos, y entrevistas con maestras. Las conclusiones señalan que este corpus metodológico permite cuantificar variaciones perceptivas según relaciones de proporción y distribución espacial. Se enfatiza también la necesidad de integrar registros perceptivos al diseño arquitectónico para asegurar la calidad de las relaciones

Chronic Obstructive Pulmonary Disease: Emphysema

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease that causes obstructed airflow from the lungs. Emphysema and chronic bronchitis are the two most common conditions that contribute to COPD. The purpose of this poster is to investigate and transfer knowledge of the pathophysiological concept of emphysema along with the significance of pathophysiology, and implications of nursing. The research also includes the signs and symptoms and treatment options available. Sources used were published between 2013- 2018 in the United States. The poster provides valuable information for providers to be competent when caring for this patient population

Facilitating change in primary education: The role of existing school facilities in ICT initiatives

Purpose – The aim of this paper is to illuminate the impact that the implementation of the Plan Ceibal imposes on the existing school infrastructure and how the use and upkeep of available facilities might need to be altered and changed to accommodate the new technology. Uruguay is, through the Plan Ceibal, the first country to provide every public primary school child with a laptop free of charge. The Plan represents a major investment to promote digital literacy and improve the quality of education. Design/methodology/approach – Empirical data are drawn from a multiple case study of five public primary schools. Particular attention is given to how school facilities and their immediate surroundings mediate the successful introduction and adoption of individual laptops. Findings – Plan Ceibal has the potential to change traditional teaching methods and behavioural patterns, which will in turn have an impact on how facilities and spaces are used. Questions are raised regarding the ultimate effectiveness of the initiative and if the aspired to improvements might be curtailed by a lack of investment in other areas, such as the school infrastructure. We argue for a context-sensitive view on research that not only considers the technology and potential changes in pedagogical approaches but also the physical environment in which these changes are to take place. Originality/value – Research into facilities and asset management has an important role to play in the achievement of effective learning environments and the successful uptake of information communication technology (ICT) initiatives.postprin

Schools for the twenty-first century: School design and educational transformation

The Building Schools for the Future programme has been established to ensure that English secondary schools are designed or redesigned to allow for educational transformation. The programme represents the biggest single UK government investment in school buildings for over 50 years. For this reason, it poses a major challenge to those involved in the design of educational buildings. Inspiration is in part sought from exemplar schools around the world. The paper draws on a multiple case study of four such exemplar schools in Scandinavia that have been designed to address changes in the educational curriculum. The analysis depicts the degree to which the building design in each case supports the school approach to teaching and learning. The disjuncture between commercial and educational issues inherent in designing 'good' schools is highlighted. The findings show how it is important to find a balance between good design, commercial realities and educational approaches. © 2011 British Educational Research Association.preprin

SuFLexQA: an approach to Question Answering from the lexicon

We present SuFLexQA, a system for Question Answering that integrates deep linguistic information from verbal lexica into Quepy, a generic framework for translating natural language questions into a query language. We are participating in the QALD-3 contest to assess the main achievements and shortcomings of the system.Sociedad Argentina de Informática e Investigación Operativ

Disjoint Semi-supervised Spanish Verb Sense Disambiguation Using Word Embeddings

This work explores the use of word embeddings, also known as word vectors, trained on Spanish corpora, to use as features for Spanish verb sense disambiguation (VSD). This type of learning technique is named disjoint semisupervised learning [1]: an unsupervised algorithm is trained on unlabeled data separately as a first step, and then its results (i.e. the word embeddings) are fed to a supervised classifier. Throughout this paper we try to assert two hypothesis: (i) representations of training instances based on word embeddings improve the performance of supervised models for VSD, in contrast to more standard feature engineering techniques based on information taken from the training data; (ii) using word embeddings trained on a specific domain, in this case the same domain the labeled data is gathered from, has a positive impact on the model’s performance, when compared to general domain’s word embeddings. The performance of a model over the data is not only measured using standard metric techniques (e.g. accuracy or precision/recall) but also measuring the model tendency to overfit the available data by analyzing the learning curve. Measuring this overfitting tendency is important as there is a small amount of available data, thus we need to find models to generalize better the VSD problem. For the task we use SenSem [2], a corpus and lexicon of Spanish and Catalan disambiguated verbs, as our base resource for experimentation.Sociedad Argentina de Informática e Investigación Operativ

Reversing uncertainty sampling to improve active learning schemes

Active learning provides promising methods to optimize the cost of manually annotating a dataset. However, practitioners in many areas do not massively resort to such methods because they present technical difficulties and do not provide a guarantee of good performance, especially in skewed distributions with scarcely populated minority classes and an undefined, catch-all majority class, which are very common in human-related phenomena like natural language. In this paper we present a comparison of the simplest active learning technique, pool-based uncertainty sampling, and its opposite, which we call reversed uncertainty sampling. We show that both obtain results comparable to the random, arguing for a more insightful approach to active learning.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Reversing uncertainty sampling to improve active learning schemes

Active learning provides promising methods to optimize the cost of manually annotating a dataset. However, practitioners in many areas do not massively resort to such methods because they present technical difficulties and do not provide a guarantee of good performance, especially in skewed distributions with scarcely populated minority classes and an undefined, catch-all majority class, which are very common in human-related phenomena like natural language. In this paper we present a comparison of the simplest active learning technique, pool-based uncertainty sampling, and its opposite, which we call reversed uncertainty sampling. We show that both obtain results comparable to the random, arguing for a more insightful approach to active learning.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Disjoint Semi-supervised Spanish Verb Sense Disambiguation Using Word Embeddings

This work explores the use of word embeddings, also known as word vectors, trained on Spanish corpora, to use as features for Spanish verb sense disambiguation (VSD). This type of learning technique is named disjoint semisupervised learning [1]: an unsupervised algorithm is trained on unlabeled data separately as a first step, and then its results (i.e. the word embeddings) are fed to a supervised classifier. Throughout this paper we try to assert two hypothesis: (i) representations of training instances based on word embeddings improve the performance of supervised models for VSD, in contrast to more standard feature engineering techniques based on information taken from the training data; (ii) using word embeddings trained on a specific domain, in this case the same domain the labeled data is gathered from, has a positive impact on the model’s performance, when compared to general domain’s word embeddings. The performance of a model over the data is not only measured using standard metric techniques (e.g. accuracy or precision/recall) but also measuring the model tendency to overfit the available data by analyzing the learning curve. Measuring this overfitting tendency is important as there is a small amount of available data, thus we need to find models to generalize better the VSD problem. For the task we use SenSem [2], a corpus and lexicon of Spanish and Catalan disambiguated verbs, as our base resource for experimentation.Sociedad Argentina de Informática e Investigación Operativ

SuFLexQA: an approach to Question Answering from the lexicon

We present SuFLexQA, a system for Question Answering that integrates deep linguistic information from verbal lexica into Quepy, a generic framework for translating natural language questions into a query language. We are participating in the QALD-3 contest to assess the main achievements and shortcomings of the system.Sociedad Argentina de Informática e Investigación Operativ