Diseño y desarrollo de un sistema basado en Learning Analytics para evaluar la competencia de trabajo en equipo.Design and development of a Learning Analytics System to evaluate group work competence

La adquisición de la competencia grupal es algo básico en la docencia universitaria. Esta tarea va a suponer evaluar diferentes factores en un número elevado de alumnos, lo que puede supone gran complejidad y un esfuerzo elevado. De cara a evitar este esfuerzo se puede pensar en emplear los registros de la interacción de los usuarios almacenados en las plataformas de aprendizaje. Para ello el presente trabajo se basa en el desarrollo de un sistema de Learning Analytics que es utilizado como herramienta para analizar las evidencias individuales de los distintos miembros de un equipo de trabajo. El trabajo desarrolla un modelo teórico apoyado en la herramienta, que permite relacionar las evidencias observadas de forma empírica para cada alumno, con indicadores obtenidos tanto de la acción individual como cooperativo de los miembros de un equipo realizadas a través de los foros de trabajo. Abstract — The development of the group work competence is something basic in university teaching. It should be evaluated, but this means to analyze different issues about the participation of a high number of students which is very complex and implies a lot of effort. In order to facilitate this evaluation it is possible to analyze the logs of students’ interaction in Learning Management Systems. The present work describes the development of a Learning Analytics system that analyzes the interaction of each of the members of working group. This tool is supported by a theoretical model, which allows establishing links between the empirical evidences of each student and the indicators of their action in working forums.

Wind tunnel experiments to teach physics

Innovative teaching experimental activities for secondary school students have been developed in order to introduce some aerodynamic concepts, with the aim of making science subjects such as mathematics and physics more attractive. Post-graduate students of Universidad Politécnica de Madrid (UPM) and teachers of Deutsche Schule Madrid (DSM) have constructed a small wind tunnel. The main goal has been to provide a tool for secondary school students to become familiar with the scientific method developing curiosity, imagination, initiative, critical thinking and problem-solving skills. Students of DSM have performed wind tunnel experiments, resulting in a successful and amusing experience. The students were able to relate the experimental results obtained with the physic principle of flight, previously explained in class. Evaluations reveal that both, the teacher and the students, considered the experience as interesting and helpful to lead with teaching physics, mathematics and engineering sciences. The teacher observed the strong motivation factor developed for the students to continue learning engineering sciences. Some of the students expressed that this experience had changed their prejudices about physics and mathematics, based only on theoretical approaches.

Contributions to Speech Analytics based on Speech Recognition and Topic Identification

La última década ha sido testigo de importantes avances en el campo de la tecnología de reconocimiento de voz. Los sistemas comerciales existentes actualmente poseen la capacidad de reconocer habla continua de múltiples locutores, consiguiendo valores aceptables de error, y sin la necesidad de realizar procedimientos explícitos de adaptación. A pesar del buen momento que vive esta tecnología, el reconocimiento de voz dista de ser un problema resuelto. La mayoría de estos sistemas de reconocimiento se ajustan a dominios particulares y su eficacia depende de manera significativa, entre otros muchos aspectos, de la similitud que exista entre el modelo de lenguaje utilizado y la tarea específica para la cual se está empleando. Esta dependencia cobra aún más importancia en aquellos escenarios en los cuales las propiedades estadísticas del lenguaje varían a lo largo del tiempo, como por ejemplo, en dominios de aplicación que involucren habla espontánea y múltiples temáticas. En los últimos años se ha evidenciado un constante esfuerzo por mejorar los sistemas de reconocimiento para tales dominios. Esto se ha hecho, entre otros muchos enfoques, a través de técnicas automáticas de adaptación. Estas técnicas son aplicadas a sistemas ya existentes, dado que exportar el sistema a una nueva tarea o dominio puede requerir tiempo a la vez que resultar costoso. Las técnicas de adaptación requieren fuentes adicionales de información, y en este sentido, el lenguaje hablado puede aportar algunas de ellas. El habla no sólo transmite un mensaje, también transmite información acerca del contexto en el cual se desarrolla la comunicación hablada (e.g. acerca del tema sobre el cual se está hablando). Por tanto, cuando nos comunicamos a través del habla, es posible identificar los elementos del lenguaje que caracterizan el contexto, y al mismo tiempo, rastrear los cambios que ocurren en estos elementos a lo largo del tiempo. Esta información podría ser capturada y aprovechada por medio de técnicas de recuperación de información (information retrieval) y de aprendizaje de máquina (machine learning). Esto podría permitirnos, dentro del desarrollo de mejores sistemas automáticos de reconocimiento de voz, mejorar la adaptación de modelos del lenguaje a las condiciones del contexto, y por tanto, robustecer al sistema de reconocimiento en dominios con condiciones variables (tales como variaciones potenciales en el vocabulario, el estilo y la temática). En este sentido, la principal contribución de esta Tesis es la propuesta y evaluación de un marco de contextualización motivado por el análisis temático y basado en la adaptación dinámica y no supervisada de modelos de lenguaje para el robustecimiento de un sistema automático de reconocimiento de voz. Esta adaptación toma como base distintos enfoque de los sistemas mencionados (de recuperación de información y aprendizaje de máquina) mediante los cuales buscamos identificar las temáticas sobre las cuales se está hablando en una grabación de audio. Dicha identificación, por lo tanto, permite realizar una adaptación del modelo de lenguaje de acuerdo a las condiciones del contexto. El marco de contextualización propuesto se puede dividir en dos sistemas principales: un sistema de identificación de temática y un sistema de adaptación dinámica de modelos de lenguaje. Esta Tesis puede describirse en detalle desde la perspectiva de las contribuciones particulares realizadas en cada uno de los campos que componen el marco propuesto: _ En lo referente al sistema de identificación de temática, nos hemos enfocado en aportar mejoras a las técnicas de pre-procesamiento de documentos, asimismo en contribuir a la definición de criterios más robustos para la selección de index-terms. – La eficiencia de los sistemas basados tanto en técnicas de recuperación de información como en técnicas de aprendizaje de máquina, y específicamente de aquellos sistemas que particularizan en la tarea de identificación de temática, depende, en gran medida, de los mecanismos de preprocesamiento que se aplican a los documentos. Entre las múltiples operaciones que hacen parte de un esquema de preprocesamiento, la selección adecuada de los términos de indexado (index-terms) es crucial para establecer relaciones semánticas y conceptuales entre los términos y los documentos. Este proceso también puede verse afectado, o bien por una mala elección de stopwords, o bien por la falta de precisión en la definición de reglas de lematización. En este sentido, en este trabajo comparamos y evaluamos diferentes criterios para el preprocesamiento de los documentos, así como también distintas estrategias para la selección de los index-terms. Esto nos permite no sólo reducir el tamaño de la estructura de indexación, sino también mejorar el proceso de identificación de temática. – Uno de los aspectos más importantes en cuanto al rendimiento de los sistemas de identificación de temática es la asignación de diferentes pesos a los términos de acuerdo a su contribución al contenido del documento. En este trabajo evaluamos y proponemos enfoques alternativos a los esquemas tradicionales de ponderado de términos (tales como tf-idf ) que nos permitan mejorar la especificidad de los términos, así como también discriminar mejor las temáticas de los documentos. _ Respecto a la adaptación dinámica de modelos de lenguaje, hemos dividimos el proceso de contextualización en varios pasos. – Para la generación de modelos de lenguaje basados en temática, proponemos dos tipos de enfoques: un enfoque supervisado y un enfoque no supervisado. En el primero de ellos nos basamos en las etiquetas de temática que originalmente acompañan a los documentos del corpus que empleamos. A partir de estas, agrupamos los documentos que forman parte de la misma temática y generamos modelos de lenguaje a partir de dichos grupos. Sin embargo, uno de los objetivos que se persigue en esta Tesis es evaluar si el uso de estas etiquetas para la generación de modelos es óptimo en términos del rendimiento del reconocedor. Por esta razón, nosotros proponemos un segundo enfoque, un enfoque no supervisado, en el cual el objetivo es agrupar, automáticamente, los documentos en clusters temáticos, basándonos en la similaridad semántica existente entre los documentos. Por medio de enfoques de agrupamiento conseguimos mejorar la cohesión conceptual y semántica en cada uno de los clusters, lo que a su vez nos permitió refinar los modelos de lenguaje basados en temática y mejorar el rendimiento del sistema de reconocimiento. – Desarrollamos diversas estrategias para generar un modelo de lenguaje dependiente del contexto. Nuestro objetivo es que este modelo refleje el contexto semántico del habla, i.e. las temáticas más relevantes que se están discutiendo. Este modelo es generado por medio de la interpolación lineal entre aquellos modelos de lenguaje basados en temática que estén relacionados con las temáticas más relevantes. La estimación de los pesos de interpolación está basada principalmente en el resultado del proceso de identificación de temática. – Finalmente, proponemos una metodología para la adaptación dinámica de un modelo de lenguaje general. El proceso de adaptación tiene en cuenta no sólo al modelo dependiente del contexto sino también a la información entregada por el proceso de identificación de temática. El esquema usado para la adaptación es una interpolación lineal entre el modelo general y el modelo dependiente de contexto. Estudiamos también diferentes enfoques para determinar los pesos de interpolación entre ambos modelos. Una vez definida la base teórica de nuestro marco de contextualización, proponemos su aplicación dentro de un sistema automático de reconocimiento de voz. Para esto, nos enfocamos en dos aspectos: la contextualización de los modelos de lenguaje empleados por el sistema y la incorporación de información semántica en el proceso de adaptación basado en temática. En esta Tesis proponemos un marco experimental basado en una arquitectura de reconocimiento en ‘dos etapas’. En la primera etapa, empleamos sistemas basados en técnicas de recuperación de información y aprendizaje de máquina para identificar las temáticas sobre las cuales se habla en una transcripción de un segmento de audio. Esta transcripción es generada por el sistema de reconocimiento empleando un modelo de lenguaje general. De acuerdo con la relevancia de las temáticas que han sido identificadas, se lleva a cabo la adaptación dinámica del modelo de lenguaje. En la segunda etapa de la arquitectura de reconocimiento, usamos este modelo adaptado para realizar de nuevo el reconocimiento del segmento de audio. Para determinar los beneficios del marco de trabajo propuesto, llevamos a cabo la evaluación de cada uno de los sistemas principales previamente mencionados. Esta evaluación es realizada sobre discursos en el dominio de la política usando la base de datos EPPS (European Parliamentary Plenary Sessions - Sesiones Plenarias del Parlamento Europeo) del proyecto europeo TC-STAR. Analizamos distintas métricas acerca del rendimiento de los sistemas y evaluamos las mejoras propuestas con respecto a los sistemas de referencia. ABSTRACT The last decade has witnessed major advances in speech recognition technology. Today’s commercial systems are able to recognize continuous speech from numerous speakers, with acceptable levels of error and without the need for an explicit adaptation procedure. Despite this progress, speech recognition is far from being a solved problem. Most of these systems are adjusted to a particular domain and their efficacy depends significantly, among many other aspects, on the similarity between the language model used and the task that is being addressed. This dependence is even more important in scenarios where the statistical properties of the language fluctuates throughout the time, for example, in application domains involving spontaneous and multitopic speech. Over the last years there has been an increasing effort in enhancing the speech recognition systems for such domains. This has been done, among other approaches, by means of techniques of automatic adaptation. These techniques are applied to the existing systems, specially since exporting the system to a new task or domain may be both time-consuming and expensive. Adaptation techniques require additional sources of information, and the spoken language could provide some of them. It must be considered that speech not only conveys a message, it also provides information on the context in which the spoken communication takes place (e.g. on the subject on which it is being talked about). Therefore, when we communicate through speech, it could be feasible to identify the elements of the language that characterize the context, and at the same time, to track the changes that occur in those elements over time. This information can be extracted and exploited through techniques of information retrieval and machine learning. This allows us, within the development of more robust speech recognition systems, to enhance the adaptation of language models to the conditions of the context, thus strengthening the recognition system for domains under changing conditions (such as potential variations in vocabulary, style and topic). In this sense, the main contribution of this Thesis is the proposal and evaluation of a framework of topic-motivated contextualization based on the dynamic and non-supervised adaptation of language models for the enhancement of an automatic speech recognition system. This adaptation is based on an combined approach (from the perspective of both information retrieval and machine learning fields) whereby we identify the topics that are being discussed in an audio recording. The topic identification, therefore, enables the system to perform an adaptation of the language model according to the contextual conditions. The proposed framework can be divided in two major systems: a topic identification system and a dynamic language model adaptation system. This Thesis can be outlined from the perspective of the particular contributions made in each of the fields that composes the proposed framework: _ Regarding the topic identification system, we have focused on the enhancement of the document preprocessing techniques in addition to contributing in the definition of more robust criteria for the selection of index-terms. – Within both information retrieval and machine learning based approaches, the efficiency of topic identification systems, depends, to a large extent, on the mechanisms of preprocessing applied to the documents. Among the many operations that encloses the preprocessing procedures, an adequate selection of index-terms is critical to establish conceptual and semantic relationships between terms and documents. This process might also be weakened by a poor choice of stopwords or lack of precision in defining stemming rules. In this regard we compare and evaluate different criteria for preprocessing the documents, as well as for improving the selection of the index-terms. This allows us to not only reduce the size of the indexing structure but also to strengthen the topic identification process. – One of the most crucial aspects, in relation to the performance of topic identification systems, is to assign different weights to different terms depending on their contribution to the content of the document. In this sense we evaluate and propose alternative approaches to traditional weighting schemes (such as tf-idf ) that allow us to improve the specificity of terms, and to better identify the topics that are related to documents. _ Regarding the dynamic language model adaptation, we divide the contextualization process into different steps. – We propose supervised and unsupervised approaches for the generation of topic-based language models. The first of them is intended to generate topic-based language models by grouping the documents, in the training set, according to the original topic labels of the corpus. Nevertheless, a goal of this Thesis is to evaluate whether or not the use of these labels to generate language models is optimal in terms of recognition accuracy. For this reason, we propose a second approach, an unsupervised one, in which the objective is to group the data in the training set into automatic topic clusters based on the semantic similarity between the documents. By means of clustering approaches we expect to obtain a more cohesive association of the documents that are related by similar concepts, thus improving the coverage of the topic-based language models and enhancing the performance of the recognition system. – We develop various strategies in order to create a context-dependent language model. Our aim is that this model reflects the semantic context of the current utterance, i.e. the most relevant topics that are being discussed. This model is generated by means of a linear interpolation between the topic-based language models related to the most relevant topics. The estimation of the interpolation weights is based mainly on the outcome of the topic identification process. – Finally, we propose a methodology for the dynamic adaptation of a background language model. The adaptation process takes into account the context-dependent model as well as the information provided by the topic identification process. The scheme used for the adaptation is a linear interpolation between the background model and the context-dependent one. We also study different approaches to determine the interpolation weights used in this adaptation scheme. Once we defined the basis of our topic-motivated contextualization framework, we propose its application into an automatic speech recognition system. We focus on two aspects: the contextualization of the language models used by the system, and the incorporation of semantic-related information into a topic-based adaptation process. To achieve this, we propose an experimental framework based in ‘a two stages’ recognition architecture. In the first stage of the architecture, Information Retrieval and Machine Learning techniques are used to identify the topics in a transcription of an audio segment. This transcription is generated by the recognition system using a background language model. According to the confidence on the topics that have been identified, the dynamic language model adaptation is carried out. In the second stage of the recognition architecture, an adapted language model is used to re-decode the utterance. To test the benefits of the proposed framework, we carry out the evaluation of each of the major systems aforementioned. The evaluation is conducted on speeches of political domain using the EPPS (European Parliamentary Plenary Sessions) database from the European TC-STAR project. We analyse several performance metrics that allow us to compare the improvements of the proposed systems against the baseline ones.

Relação existente entre metavisualização e as representações simbólica e submicro na elaboração de atividade em química

O objetivo desse trabalho foi compreender em que medida uma estratégia metavisual, utilizada em sala de aula, pode ajudar na construção e reconstrução de ideias, especificamente numa atividade introdutória de eletroquímica e quais os fatores envolvidos nesse processo. Para isso, foi desenvolvida uma atividade para o estudo inicial de duas interações eletroquímicas, envolvendo ferro e soluções de sulfato de cobre (II) e ácido sulfúrico. Foi utilizada uma metodologia qualitativa, envolvendo 32 estudantes do 3.o ano do ensino médio de uma mesma escola, idades entre 16 e 18 anos, em que foram feitos os registros audiovisuais dos alunos realizando a atividade e as falas transcritas para análise. Além disso, eles responderam a um questionário para se pesquisar por indícios nas habilidades metavisuais em 1D e 2D e, por último, uma entrevista semiestruturada. Duas categorias foram elaboradas com o objetivo de se classificar as hipóteses propostas para posterior comparação, uma para o nível simbólico e a outra para o submicro, possibilitando a observação de possíveis evoluções e dificuldades encontradas. Com relação às habilidades metavisuais, também foram necessárias três categorias para compor a análise. Os resultados indicam que a estratégia metavisual mostrou-se eficiente para a construção e reconstrução de conceitos associados à eletroquímica, na medida em que as concepções alternativas e dificuldades, comuns nessa área, puderam ser discutidas e modificadas. Houve evolução das hipóteses dos alunos, com intensa modelagem de conceitos, propiciada pela comparação de imagens (metavisualização), tanto no nível simbólico quanto no submicro. Foi observado que os estudantes demonstraram maior dificuldade ao elaborar as hipóteses do submicro, possivelmente por esse nível ter mais detalhes, maior aprofundamento de conceitos, ser mais abstrato e, portanto, não ser natural para os estudantes. Adicionalmente, o tempo de aprendizagem e de modelagem revelou-se diferente para os grupos, o que sugere aos professores considerarem isso no processo ensino-aprendizagem. Finalmente, os resultados parecem apontar também que as habilidades metavisuais e as conexões entre os níveis representacionais podem estar associados a melhores aprendizados e que, muitas vezes, é necessária a utilização de diversas representações e de um tempo maior para que os alunos consigam evoluir. Vale ressaltar que o assunto ainda é pouco pesquisado, se comparado a outros temas e, sendo assim, recomendam-se mais pesquisas sobre as estratégias metacognitivas no ensino de ciências e de química, em que as suas contribuições, no aprendizado dos alunos, possam ser mais investigadas.

Características del desarrollo de una mirada profesional en estudiantes para profesor de matemáticas en un contexto b-learning

Esta investigación presenta un estudio cuyo objetivo es identificar aspectos que apoyan el desarrollo de la mirada profesional en estudiantes para profesores de matemáticas en un contexto b-learning. Analizamos las producciones de un grupo de estudiantes para profesores de matemáticas de educación secundaria (documentos escritos y participaciones en un debate on-line) cuando analizaban el razonamiento proporcional de estudiantes de educación secundaria. Los resultados indican que la interacción en el debate en línea permitió a algunos estudiantes para profesor mejorar su capacidad de identificar e interpretar aspectos relevantes del pensamiento matemático de los estudiantes de educación secundaria. Estos resultados indican que el desarrollo de “una mirada profesional” del profesor es un proceso complicado pero que la posibilidad de construir un discurso progresivo en línea es un factor importante para su desarrollo.

Learning representations for Information Retrieval

La recherche d'informations s'intéresse, entre autres, à répondre à des questions comme: est-ce qu'un document est pertinent à une requête ? Est-ce que deux requêtes ou deux documents sont similaires ? Comment la similarité entre deux requêtes ou documents peut être utilisée pour améliorer l'estimation de la pertinence ? Pour donner réponse à ces questions, il est nécessaire d'associer chaque document et requête à des représentations interprétables par ordinateur. Une fois ces représentations estimées, la similarité peut correspondre, par exemple, à une distance ou une divergence qui opère dans l'espace de représentation. On admet généralement que la qualité d'une représentation a un impact direct sur l'erreur d'estimation par rapport à la vraie pertinence, jugée par un humain. Estimer de bonnes représentations des documents et des requêtes a longtemps été un problème central de la recherche d'informations. Le but de cette thèse est de proposer des nouvelles méthodes pour estimer les représentations des documents et des requêtes, la relation de pertinence entre eux et ainsi modestement avancer l'état de l'art du domaine. Nous présentons quatre articles publiés dans des conférences internationales et un article publié dans un forum d'évaluation. Les deux premiers articles concernent des méthodes qui créent l'espace de représentation selon une connaissance à priori sur les caractéristiques qui sont importantes pour la tâche à accomplir. Ceux-ci nous amènent à présenter un nouveau modèle de recherche d'informations qui diffère des modèles existants sur le plan théorique et de l'efficacité expérimentale. Les deux derniers articles marquent un changement fondamental dans l'approche de construction des représentations. Ils bénéficient notamment de l'intérêt de recherche dont les techniques d'apprentissage profond par réseaux de neurones, ou deep learning, ont fait récemment l'objet. Ces modèles d'apprentissage élicitent automatiquement les caractéristiques importantes pour la tâche demandée à partir d'une quantité importante de données. Nous nous intéressons à la modélisation des relations sémantiques entre documents et requêtes ainsi qu'entre deux ou plusieurs requêtes. Ces derniers articles marquent les premières applications de l'apprentissage de représentations par réseaux de neurones à la recherche d'informations. Les modèles proposés ont aussi produit une performance améliorée sur des collections de test standard. Nos travaux nous mènent à la conclusion générale suivante: la performance en recherche d'informations pourrait drastiquement être améliorée en se basant sur les approches d'apprentissage de représentations.

Learning representations for Information Retrieval

La recherche d'informations s'intéresse, entre autres, à répondre à des questions comme: est-ce qu'un document est pertinent à une requête ? Est-ce que deux requêtes ou deux documents sont similaires ? Comment la similarité entre deux requêtes ou documents peut être utilisée pour améliorer l'estimation de la pertinence ? Pour donner réponse à ces questions, il est nécessaire d'associer chaque document et requête à des représentations interprétables par ordinateur. Une fois ces représentations estimées, la similarité peut correspondre, par exemple, à une distance ou une divergence qui opère dans l'espace de représentation. On admet généralement que la qualité d'une représentation a un impact direct sur l'erreur d'estimation par rapport à la vraie pertinence, jugée par un humain. Estimer de bonnes représentations des documents et des requêtes a longtemps été un problème central de la recherche d'informations. Le but de cette thèse est de proposer des nouvelles méthodes pour estimer les représentations des documents et des requêtes, la relation de pertinence entre eux et ainsi modestement avancer l'état de l'art du domaine. Nous présentons quatre articles publiés dans des conférences internationales et un article publié dans un forum d'évaluation. Les deux premiers articles concernent des méthodes qui créent l'espace de représentation selon une connaissance à priori sur les caractéristiques qui sont importantes pour la tâche à accomplir. Ceux-ci nous amènent à présenter un nouveau modèle de recherche d'informations qui diffère des modèles existants sur le plan théorique et de l'efficacité expérimentale. Les deux derniers articles marquent un changement fondamental dans l'approche de construction des représentations. Ils bénéficient notamment de l'intérêt de recherche dont les techniques d'apprentissage profond par réseaux de neurones, ou deep learning, ont fait récemment l'objet. Ces modèles d'apprentissage élicitent automatiquement les caractéristiques importantes pour la tâche demandée à partir d'une quantité importante de données. Nous nous intéressons à la modélisation des relations sémantiques entre documents et requêtes ainsi qu'entre deux ou plusieurs requêtes. Ces derniers articles marquent les premières applications de l'apprentissage de représentations par réseaux de neurones à la recherche d'informations. Les modèles proposés ont aussi produit une performance améliorée sur des collections de test standard. Nos travaux nous mènent à la conclusion générale suivante: la performance en recherche d'informations pourrait drastiquement être améliorée en se basant sur les approches d'apprentissage de représentations.

Discrepancy between older clients' ability to read and comprehend and the reading level of written educational materials used by occupational therapists

OBJECTIVE. The match between the reading level of occupational therapy education materials and older clients' reading ability and comprehension was determined. The sociodemographic and literacy characteristics that influenced clients' reading ability and comprehension were investigated. METHOD. The reading level of 110 written education materials (handouts, brochures, and information leaflets), distributed to older clients (65 years of age and older) by occupational therapists working in Queensland hospitals, was analyzed using the Flesch formula. The reading ability of 214 older persons (mean age 77 years, 63% female) was assessed using the Rapid Estimate of Adult Literacy in Medicine. Participants' comprehension of information of increasing reading difficulty was measured using the Cloze procedure. RESULTS. The written materials required a mean reading level between the ninth and tenth grades. Participants' mean reading ability was seventh to eighth grade. Therefore some materials may have been too difficult for participants to read and understand. Participants with a managerial or professional or clerical background (p = 0.001) and those who perceived they read well (p = 0.001) had a significantly higher reading ability, Older age was significantly related to poorer comprehension (p = 0.018), with participants 75 years of age and over having a mean comprehension score of 25.6 compared to 30.3 for those 65 to 74 years of age. CONCLUSION. Occupational therapists must analyze the reading level of the written education materials they develop for and use with clients by applying readability formulas. There should be a match between the reading level of written materials and clients' reading ability. Clients' reading ability may be assessed informally by discussing years of education and literacy habits or formally using reading assessments. Content and design characteristics should be considered when developing written education materials for clients.

A PSICOPEDAGOGIA SERIA UMA POSSIBILIDADE PARA O ENFRENTAMENTO DAS DIFICULDADES DE APRENDIZAGEM?

A prática do professor em sala de aula é de extrema importância para um bom desenvolvimento do educando. No ensino básico podemos perceber grande número de crianças com dificuldades de aprendizagem relacionadas à leitura e à escrita elas sabem ler o que está escrito, mas não conseguem interpretar o que estão lendo. Diante desse contexto, este estudo teve por objetivo realizar uma discussão para verificar se, efetivamente, os conhecimentos psicopedagógicos são facilitadores para a organização de intervenções na prática pedagógica de professores que enfrentam dificuldades de aprendizagem de alunos no processo de leitura e escrita, e investigar se os professores que possuem os conhecimentos psicopedagógicos têm mais sucesso em termos de resultados satisfatórios frente às intervenções com seus alunos, em relação aos professores que não possuem estes conhecimentos. Este estudo se delimitou no âmbito do Ensino Fundamental, e teve como sujeitos, seis professores pedagogos que atuam ou atuaram, nos 3º ou 4º anos do Ciclo I (das séries iniciais) em escolas públicas na grande São Paulo três que possuem o curso de psicopedagogia e três que não possuem o curso de psicopedagogia, e teve como motivadoras as seguintes questões: A prática psicopedagógica pode contribuir de forma positiva no contexto escolar? O professor pedagogo, com os conhecimentos psicopedagógicos, tem mais facilidade para lidar com dificuldades de aprendizagem? É realizada, também, uma recuperação histórica sobre o surgimento da Psicopedagogia no Brasil e seu campo de atuação, além de reflexões sobre se a discussão acerca das dificuldades de aprendizagem está relacionada com as dificuldades de ensinagem". O referencial teórico básico, para o aprofundamento de algumas discussões propostas, baseou-se em autores como Bossa, 2011; Fernández, 1991; Paín, 1992; Polity, 2002 e Franco, 2003. Para a coleta de dados dos sujeitos selecionados, realizamos entrevistas semi-estruturadas, gravadas em áudio e transcritas, para posterior organização de categorias de análises, por meio da metodologia de análise de conteúdo proposta por Franco (2003). Através desta investigação constatamos que como a psicopedagogia possui um caráter interdisciplinar, muito da sua contribuição teórica e prática vêm de outras áreas do conhecimento, como por exemplo, da pedagogia. Assim, muito das práticas interventivas dos professores com psicopedagogia para com os alunos que enfrentam dificuldades de aprendizagem na leitura e na escrita, são as mesmas que os professores, sem psicopedagogia, utilizam em sala de aula.

Learner initiative in the language classroom

This article looks at learner initiative in teacher-fronted activities and how this can influence classroom interaction. Extracts from lesson transcripts of adult evening classes in Italy are used to give a precise definition of what is meant by learner initiative and to illustrate how it can change interaction patterns. It is suggested that learner initiative could have an important role to play in promoting comprehensible input and output and therefore language learning. It will be seen how, by giving learners more space and time, initiative can be actively encouraged. However, there are direct implications for teacher training as it is necessary to change traditional interaction patterns and make learner initiative more effective.

Language against the odds, or rather not:the weak central coherence hypothesis and language

EV is a child with a talent for learning language combined with Asperger syndrome. EV’s talent is evident in the unusual circumstances of her acquisition of both her first (Bulgarian) and second (German) languages and the unique patterns of both receptive and expressive language (in both the L1 and L2), in which she shows subtle dissociations in competence and performance consistent with an uneven cognitive profile of skills and abilities. We argue that this case provides support for theories of language learning and usage that require more general underlying cognitive mechanisms and skills. One such account, the Weak Central Coherence (WCC) hypothesis of autism, provides a plausible framework for the interpretation of the simultaneous co-occurrence of EV’s particular pattern of cognitive strengths and weaknesses. Furthermore, we show that specific features of the uneven cognitive profile of Asperger syndrome can help explain the observed language talent displayed by EV. Thus, rather than demonstrating a case where language learning takes place despite the presence of deficits, EV’s case illustrates how a pattern of strengths within this profile can specifically promote language learning.

Brilliant mistake! Essays on incidents of management mistakes and mea culpa

Purpose – The purpose of this paper is to examine students’ perceptions of managerial mistakes and why (and why not) managers admit mistakes. Design/methodology/approach – This paper provides a reflective account of how students’ perceive management mistakes and deal with admitting “mea culpa” – “I am to blame”. Findings – The findings show a range of attitudes: they highlight the intermingling pressures associated with the cultural environment and mistakes; they identify media characteristics and its influences on mistakes and mea culpa; they highlight ceremonial processes and tasks that shape and influence the declaration of mea culpa; and they identify how the psychology and sociology of mistakes confronts and affects students. Taken together, the study highlights the varying degrees of wariness that is carried forward by the students from vicariously learning about management mistakes. Originality/value – This paper links up with recent discussions on retail failure and retail pedagogy. It is hoped that this paper will encourage more academics to address, and engage with, management mistakes creatively in their teaching.

The role of the undergraduate work placement in developing employment competences:results from a 5 year study of employers

There is increasing research interest into the nature of competences required to secure a graduate job. This paper examines the role of the undergraduate work placement in developing such employment competences. In order to do this we draw upon a framework of generic competences developed in a previous project by one of the authors, together with data on how these competences are valued by graduates and employers. We also draw upon a survey of employers and students who have participated in an Aston Business School work placement. The work placement year is an integral feature of Aston’s undergraduate business programme and gives up to 600 students a year the experience of working with well known companies. For the past five years we have conducted a survey of these companies to assess their experience of employing our undergraduates on work placements and to examine the skills and competencies developed by students in the learning process. In this paper we compare data from both pieces of research to examine how competences developed during the undergraduate work placement contribute to the enhancement of graduate employment.

Bilingualism and educational achievement:a study of young bilinguals in Birmingham schools and colleges

This study aimed firstly to investigate current patterns of language use amongst young bilinguals in Birmingham and secondly to examine the relationship between this language use and educational achievement. The research then focussed on various practices, customs and attitudes which would favour the attrition or survival of minority languages in the British situation. The data necessary to address this question was provided by a sample of three hundred and seventy-four 16-19 year olds, studying in Birmingham schools and colleges during the period 1987-1990 and drawn from the main linguistic minority communities in Birmingham. The research methods chosen were both quantitative and qualitative. The study found evidence of ethnolinguistic vitality amongst many of the linguistic minority communities in Birmingham: a number of practices and a range of attitudes indicate that linguistic diversity may continue and that a stable diglossic situation may develop in some instances, particularly where demographical and religious factors lead to closeness of association. Where language attrition is occurring it is often because of the move from a less prestigious minority language or dialect to a more prestigious minority language in addition to pressures from English. The educational experience of the sample indicates that literacy and formal language study are of key importance if personal bilingualism is to be experienced as an asset; high levels of oral proficiency in the L1 and L2 do not, on their own, necessarily correlate with positive educational benefit. The intervening variable associated with educational achievement appears to be the formal language learning process and literacy. A number of attitudes and practices, including the very close associations maintained with some of the countries of origin of the families, were seen to aid or hinder first language maintenance and second language acquisition.

Total quality management in English language teaching:a case study in Turkish higher education

The need to improve the management of language learning organizations in the light of the trend toward mass higher education and of the use of English as a world language was the starting point of this thesis. The thesis aims to assess the relevance, adequacy and the relative success of Total Quality Management (TQM) as a management philosophy. Taking this empirical evidence a TQM-oriented management project in a Turkish Higher Education context, the thesis observes the consequences of a change of organizational culture, with specific reference to teachers' attitudes towards management. Both qualitative and quantitative devices are employed to plot change and the value of these devices for identifying such is considered. The main focus of the thesis is the Soft S's (Shared Values, Style, Staff and Skills) of an organization rather than the Hard S's (System, Structure, Strategy). The thesis is not concerned with the teaching and learning processes, though the PDCA cycle (the Action Research Cycle) did play a part in the project for both teachers and the researcher involved in this study of organizational development. Both before the management project was launched, and at the end of the research period, the external measurement devices (Harrison's Culture Specification Device and Hofstede's VSM) were used to describe the culture of the Centre. During the management project, internal measurement devices were used to record the change including middle-management style change (the researcher in this case). The time period chosen for this study was between September 1991 and June 1994. During this period, each device was administered twice within a specific time period, ranging from a year to 32 months.