Generación de cuentos interactivos usando CBR

El proyecto consiste en un sistema interactivo que, a partir de una consulta que recibe del exterior y una base de cuentos genera nuevos cuentos haciendo modificaciones en los primeros. La base de conocimiento se compone de cuentos populares infantiles que sirven de base para crear los nuevos. Estos cuentos son representados mediante una ontología que incluye una jerarquía basada en la definición realizada por Vladimir Propp en base al estudio que desarrolló sobre la estructura común de los cuentos populares rusos. Como todo sistema interactivo una parte fundamental de este trabajo es la dedicada a la comunicación con el futuro usuario. Este flujo de información se lleva a cabo de tres formas diferentes. Una de ellas es a través del editor mediante el cual el usuario puede representar cuentos que se añaden a la base de conocimiento. No es necesario que el usuario tenga conocimientos de la representación ontológica debido a que la comunicación se desarrolla a través de una interfaz gráfica. El sistema traduce los datos introducidos por el usuario a su representación en la ontología. El segundo flujo de información corresponde con el generador de cuentos. El usuario elije una serie de parámetros que el generador tendrá en cuenta a la hora de recuperar información de la base de conocimiento para generar un nuevo cuento. Y el tercer y último flujo de información se desarrolla a lo largo del proceso de creación del nuevo cuento. Los cuentos se generan de manera gradual, lo que significa que en determinados momentos del proceso el generador puede ofrecer al usuario la posibilidad de decidir cómo continuar el cuento. [ABSTRACT] The project consists of an interactive system that, from the consult that receives from the outside and a tale’s base generates new tales doing modifications on the firsts. The knowledge base is made up of stories within the domain of fairytales that are used to generated new tales. These stories are represented by means of an ontology that include a hierarchy based on the definition made by Vladimir Propp on the basis of the study that he developed on the common structure of Russian popular stories. As every interactive system a fundamental part of this work is that one dedicated to the communication with the future user. This flow of information is carried out of three different forms. One of them is through publisher used by the user to represent stories that are added to the knowledge base. It is not necessary that the user has knowledge of the ontological representation because the communication is developed through a graphical interface. The system translates the data introduced by the user to its representation in the ontology. The second flow of information corresponds with the story generator. The user chooses several parameters that the generator will consider at the time of recovering information of the knowledge base to generate a new story. And the third and last flow of information is developed throughout the process of creation of the new story. The stories are generated incrementally, which means that at certain moments of the process the generator can offer to the user the possibility of deciding how to continue the story

Experiencia con un repositorio de ejercicios de programación en un campus virtual: de una colección de libre acceso a otra guiada por la progresión del estudiante

El Campus Virtual es el entorno en el que se ha implementado una Virtualización de Casos Prácticos para facilitar el aprendizaje activo de la materia “Introducción a la programación” en la Universidad Complutense de Madrid. El carácter multidisciplinar de esta colección de casos prácticos los hace útiles en diversas titulaciones de la citada universidad. En este artículo se presenta la evolución que ha experimentado la Virtualización de Casos Prácticos, desde una colección de libre acceso a contenidos hasta la actual con un acceso controlado por la progresión del estudiante.Peer Reviewe

Visuospatial processing improvements in students with Down Syndrome through the autonomous use of technologies

The main purpose of our study was to examine whether autonomous training through the use of technologies could be associated with improvements in selective attention, visuospatial short-term memory and visuospatial processing in students with Down Syndrome (DS). In addition, our study aimed to analyse how the improvements in selective attention and visuospatial short-term memory tasks could predict improvements in visuospatial processing. Twenty-six children and adolescents with DS who belong to specialized schools for ID participated in the study. Three different mobile applications, Bubbles (selective attention), Pairs and Learn (visuospatial short-term memory) and Tangram (visuospatial processing) developed by Smile and Learn were used during a three-month period by the students. The results showed significant improvements through training in both, Pairs and Learn and Tangram, whereas there was no significant improvement in Bubbles. The results also showed that Pairs and Learn performance could predict a 36% variance in Tangram one. Cognitive and educational implications of these results are discussed

Experiencia con un repositorio de ejercicios de programación en un campus virtual: de una colección de libre acceso a otra guiada por la progresión del estudiante

El Campus Virtual es el entorno en el que se ha implementado una Virtualización de Casos Prácticos para facilitar el aprendizaje activo de la materia “Introducción a la programación” en la Universidad Complutense de Madrid. El carácter multidisciplinar de esta colección de casos prácticos los hace útiles en diversas titulaciones de la citada universidad. En este artículo se presenta la evolución que ha experimentado la Virtualización de Casos Prácticos, desde una colección de libre acceso a contenidos hasta la actual con un acceso controlado por la progresión del estudiante.Este trabajo ha sido parcialmente financiado por el proyecto TIN2009-13692-C03-03

Estrategias de recomendación aplicadas a repositorios de recursos educativos

La abundancia de recursos disponibles en repositorios educativos plantea un nuevo reto: la necesidad de proporcionar soporte a la localización de aquellos recursos que se adapten a las necesidades, objetivos, preferencias, etc. de los estudiantes, en definitiva, a la localización de los recursos que les resulten más convenientes según el momento. Los sistemas recomendadores nacen con el propósito de facilitar la toma de decisiones en dominios y situaciones en los que las posibilidades de elección son muchas y variadas. Actúan sugiriéndonos buenos productos y/o servicios bien sea para comprar algo o para consumir. Aunque tradicionalmente los sistemas recomendadores se han aplicado al campo del comercio electrónico, recientemente su uso ha comenzado a llevarse al campo académico. El trabajo presentado en este Proyecto Fin de Máster se engloba precisamente dentro de esta reciente línea de investigación que afronta el traslado de técnicas de recomendación al ámbito educativo. En concreto, este trabajo aborda el uso de técnicas de recomendación como soporte al acceso personalizado de recursos educativos existentes en repositorios electrónicos. Para poder hacer una propuesta de una estrategia de recomendación, será necesario realizar un análisis del estado del arte en los sistemas recomendadores, extrayendo así las principales características de estos sistemas. Después, se estudiarán los inconvenientes de la estrategia de recomendación de recursos educativos que ha servido de punto de partida al presente trabajo. A partir de estos propondremos las nuevas estrategias de recomendación que alivian los inconvenientes detectados. Estas propuestas se ejemplificarán en el dominio concreto de la enseñanza de la Programación. [ABSTRACT] The abundance of educational resources available in on-line repositories inevitably poses a new challenge: providing support for locating those adapted to the individual knowledge, goals and/or preferences of the students. Research work on recommendation technologies helps to alleviate the process of selecting information, items or resources by supporting users in pre-selecting information they may be interested in. Recommender systems are designed to address many of these problems by offering users a more intelligent approach for navigating and searching in complex information spaces. They have been traditionally applied in ecommerce however, their use has been recently transferred to the academic field. The present work describes the use of recommendation techniques providing support for locating educational resources adapted to the student knowledge. Specifically, the use of recommendation techniques that provide personalized access to the educational resources that exist in repositories. It will be necessary to analyze the state of the art in recommender systems, in order to draw the main features of these systems. Then we examine the drawbacks of the recommendation strategy of learning objects that served as a starting point to this work. Then we will propose new strategies to alleviate the disadvantages showed. These proposals are exemplified in the specific domain of teaching Programming

Estrategias de recomendación basadas en conocimiento para la localización personalizada de recursos en repositorios educativos

La abundancia de recursos disponibles en repositorios educativos plantea un reto: la necesidad de proporcionar soporte a la localización de aquellos recursos que se adapten a las necesidades, objetivos, preferencias, etc. de los usuarios, en definitiva, a la localización de los recursos que les resulten más convenientes según el contexto. Además es conveniente que esta localización sea capaz de proponer listas de recursos que no contengan muchos elementos y que estos sean lo más variados posibles. Finalmente los usuarios echan en falta la existencia de mecanismos de interacción que permitan explorar el espacio de los recursos y que reduzcan el esfuerzo a realizar para localizar un recurso. Los sistemas de recomendación, que actúan sugiriendo productos a usuarios, nacen con el propósito de facilitar la toma de decisiones en dominios y situaciones en los que las posibilidades de elección son muchas y variadas. Aunque tradicionalmente los sistemas de recomendación se han aplicado al campo del comercio electrónico, su uso se ha extendido a otros campos entre los que se encuentra el dominio educativo. El trabajo presentado en esta memoria de tesis se engloba dentro de la línea de investigación que afronta el traslado de técnicas de recomendación al dominio educativo. En concreto, este trabajo aborda el diseño y el uso de estrategias de recomendación basadas en conocimiento como soporte al acceso personalizado a recursos educativos existentes en repositorios electrónicos. Las estrategias presentadas en este trabajo hacen uso de una representación del dominio rica en conocimiento, promueven la personalización haciendo uso de la información contextual de la actividad y del estudiante, introducen variedad en los recursos recomendados y exploran un modelo de interacción proactivo sobre el repositorio de recursos educativos que se complementa con un modelo de navegación por propuesta. ABSTRACT. The development of electronic repositories for the storage of educational resources has been intensified during the last years and in most educational disciplines. The availability of these educational resources eases and motivates student self-learning as a complementary activity to lectures. However, the high number of resources that exist in these repositories makes the access difficult to those adapted to the individual knowledge, goals and/or preferences of the students. It is necessary to provide support for personalized searching functionalities, which retrieve resources that fit the needs, goals and preferences of the students. Hence, one of the goals of our research is to design recommendation strategies that support locating educational resources adapted to the student knowledge. Furthermore, this recommendation must be intended to propose a set of resources that are appropriate to the student so that she cans take full advantage of a study session. It means that the proposals may not contain a lot of resources and it would be also desirable that the proposals be as varied as possible, in order to prevent the student get resources that are very similar among them. Finally this recommendation should explore mechanisms of interaction that allows to navigate through the space of resources and reduce the work load of the users. Research work on recommendation technologies helps to alleviate the aforementioned information overload by supporting users in pre-selecting information they may be interested in. The goal of our work on recommendation technologies in e-learning is to provide smart support for accessing to the Learning Objects that exist in repositories. This proposal has lead to the definition of three recommendation strategies that make use of existing knowledge of the domain, as well as additional information from both the student and the activity, with an ontology-based semantic representation. One of the strategies provides an student with a recommendation, list of educational resources that are adapted to the student's learning needs. The second one promotes diversity in the recommendation list. The third strategy explores a proactive model for user interaction based on a navigation-by-proposing model. The implementation of these three strategies has lead to the proposal of a developed framework for the rapid prototyping of knowledge-based recommenders to the learning field. These three strategies have been implemented and evaluated in a computational way and in a real learning field, where teachers and students have shown their satisfaction with the recommendation strategies designed. These three strategies presented will come to address the weaknesses identified in recommender systems in education

Design of a pollution ontology-based event generation framework for the dynamic application of traffic restrictions

The environmental damage caused by air pollution has recently become the focus of city council policies. The concept of the green city has emerged as an urban solution by which to confront environmental challenges worldwide and is founded on air pollution levels that have increased meaningfully as a result of traffic in urban areas. Local governments are attempting to meet environmental challenges by developing public traffic policies such as air pollution protocols. However, several problems must still be solved, such as the need to link smart cars to these pollution protocols in order to find more optimal routes. We have, therefore, attempted to address this problem by conducting a study of local policies in the city of Madrid (Spain) with the aim of determining the importance of the vehicle routing problem (VRP), and the need to optimise a set of routes for a fleet. The results of this study have allowed us to propose a framework with which to dynamically implement traffic constraints. This framework consists of three main layers: the data layer, the prediction layer and the event generation layer. With regard to the data layer, a dataset has been generated from traffic data concerning the city of Madrid, and deep learning techniques have then been applied to this data. The results obtained show that there are interdependencies between several factors, such as weather conditions, air quality and the local event calendar, which have an impact on drivers’ behaviour. These interdependencies have allowed the development of an ontological model, together with an event generation system that can anticipate changes and dynamically restructure traffic restrictions in order to obtain a more efficient traffic system. This system has been validated using real data from the city of Madrid

Regulation of matrix metalloproteinase-9 by the synthetic cannabinoid WIN in cells of the monocyte-macrophage system

Smile and Learn is an EdTech digital publisher that offers a smart library of close to 100 educational stories and gaming apps for mobile devices aimed at children aged 2 to 10 and their families. Given the complexity of navigating the content, a recommender system was developed. The system consists of two major components: one that generates content recommendations and another that provides explanations and recommendations relevant to parents and educators. The former was implemented as a hybrid recommender system that combines three kinds of recommendations. Among these, we introduce a collaborative filtering adapted to overcome specific limitations associated with younger users. The approach described in this work was tested on real users of the platform. The experimental results suggest that this recommendation model is suitable to suggest apps to children and increase their engagement in terms of usage time and number of games played

Visuospatial processing improvements in students with Down Syndrome through the autonomous use of technologies

The main purpose of our study was to examine whether autonomous training through the use of technologies could be associated with improvements in selective attention, visuospatial short-term memory and visuospatial processing in students with Down Syndrome (DS). In addition, our study aimed to analyse how the improvements in selective attention and visuospatial short-term memory tasks could predict improvements in visuospatial processing. Twenty-six children and adolescents with DS who belong to specialized schools for ID participated in the study. Three different mobile applications, Bubbles (selective attention), Pairs and Learn (visuospatial short-term memory) and Tangram (visuospatial processing) developed by Smile and Learn were used during a three-month period by the students. The results showed significant improvements through training in both, Pairs and Learn and Tangram, whereas there was no significant improvement in Bubbles. The results also showed that Pairs and Learn performance could predict a 36% variance in Tangram one. Cognitive and educational implications of these results are discussed