Introducción y bienvenida a la segunda edición Premios de Investigación e Innovación en ESO, Bachillerato y Formación Profesional, PIIECYL 2015

[ES]Introducción al Libro de Actas de los Premios de Investigación e Innovación de Educación Secundaria Obligatoria, Bachillerato y Formación Profesional de Castilla y León 2015 (PIIECYL 2015

Comprendiendo la comunicación visual en las redes sociales: una propuesta real de análisis

El presente trabajo se ha realizado dentro del Programa de Doctorado en Formación en la Sociedad del Conocimiento de la Universidad de Salamanca http://knowledgesociety.usal.es[ES]Este artículo presenta un proyecto de investigación actualmente en desarrollo que pretende implementar una serie de herramientas y sistemas que permitan a investigadores entender los flujos de comunicación visual que suceden en las redes sociales, permitiendo a su vez realizar análisis cualitativos y cuantitativos sobre dichos procesos. Dicho análisis trata de descubrir los patrones de aprendizaje por imitación que se dan en los contextos visuales de las redes sociales, así como analizar el uso del lenguaje visual dentro de las mismas, todo ello apoyado por el descubrimiento de contextos conversacionales reales donde los procesos de comunicación se producen de forma puramente visual entre usuarios que no tienen porqué tener conocimientos sobre la semántica, gramática o vocabulario implícito en el lenguaje visual. Con el fin de explicar cómo los investigadores están desarrollando los sistemas y herramientas que permiten realizar dicho análisis, el presente artículo incluye una explicación sobre el contexto de problema real, las consideraciones generales presentes en esta área de investigación, y la propuesta que los autores presentan para hacer frente a los problemas que presenta este tipo de análisis sobre imágenes y redes sociales, explicando al mismo tiempo los conceptos principales necesarios para resolver dicho problema desde un punto de vista técnico.El presente trabajo se ha realizado dentro del Programa de Doctorado en Formación en la Sociedad del Conocimiento de la Universidad de Salamanca http://knowledgesociety.usal.e

Competencia digital y su relación con la producción de textos en estudiantes de ingeniería de una universidad de Trujillo - 2022

El presente trabajo de investigación fue desarrollado con el objetivo de determinar cuál es la relación existente entre los niveles de competencia digital y producción de textos en los estudiantes de ingeniería de una universidad de Trujillo en el 2022. El tipo de investigación básica, diseño cuantitativo, no experimental transversal correlacional – causal, tuvo como muestra 35 estudiantes de ingeniería de una universidad de Trujillo, a quienes se le administró dos cuestionarios para el recojo de información de manera virtual mediante el aplicativo de Google forms. La técnica fue la encuesta y los instrumentos un cuestionario de competencia digital y producción de textos con una confiabilidad alfa de Cronbach de 0.961. Se usó la prueba de normalidad lo que permitió establecer distribución de datos paramétricos; por consiguiente, para establecer la correlación entre las variables se usó el coeficiente de correlación de Pearson. Los resultados que se obtuvieron confirmaron que existe relación directa, positiva y significativa entre competencia digital y producción de textos r=,653** (correlación positiva moderada entre variables) para todo Sig.<0.01. Se concluye que existe una correlación positiva directa y significativa entre competencia digital y producción de textos en los estudiantes de ingeniería de una universidad de Trujillo en 2022

Visual Literacy in New Media: Systematic Review and Mapping of the Literature

Many researchers have dealt previously with visual literacy in the context of new media and the use of images. The goal of this manuscript is to present a systematic review of the literature to identify, analyze and classify the published approaches and by this way find, give support or improve different research works which are carried out under the perspective of the new technologies. As results, this study identified 39 papers that link the visual literacy with the new technologies, or the images used in social networks. There have been found different main approaches where are related to the new media with visual literacy in education, with ICTs, art and design, communication, psychology, demography, professional aspects or information sciences. However, those approaches lacked standardization and were mainly ad-hoc solutions for each presented research scenario. The primary field of research where this concept is used is the use of images in education. In this field, the authors try to demonstrate how daily images can be related to formal learning. Some of the outcomes and solutions found in the literature (albeit not much frequent) conclude that thanks to some ad-hoc tools designed for each experiment, the researchers can achieve the goal of observing the status of visual literacy in users of new technologies and new media. Despite that several research efforts work in this subject and its challenges, the research community needs to continue improving the research in this area through the application of new techniques and methods which can lead to achieving standardized solutions. Moreover, thus, let researchers explore new ways of analyzing and interpreting the visual literacy avoiding custom solutions or evaluating well-known proposals from the literature.Muchos investigadores han tratado anteriormente con la alfabetización visual en los usuarios de nuevas tecnologías donde se utilizan imágenes. El objetivo de esta investigación es presentar una revisión sistemática de la literatura para identificar, analizar y clasificar los enfoques publicados y así encontrar, respaldar o mejorar las investigaciones que se realizan desde la perspectiva de las nuevas tecnologías. Como resultado, este estudio identifica 39 artículos en los que relacionan la alfabetización con las nuevas tecnologías o las imágenes en redes sociales. Se localizan varios enfoques principales donde se relacionan los nuevos medios con alfabetización visual: en educación, en tecnologías de la información y comunicación, en arte y diseño, comunicación, psicología, demografía, aspectos profesionales o ciencias de la información. Pero estos enfoques carecen de estandarización y son principalmente soluciones para cada uno de los hechos concretos presentados. El principal campo en el que se investiga este concepto es el que relaciona las imágenes con la educación. Se intenta demostrar la importancia de las imágenes en la vida diaria y su relación con el aprendizaje formal. Algunas soluciones encontradas en la literatura (aunque poco frecuentes) llegan a la conclusión de que, gracias a algunas herramientas diseñadas para ello, se podría llegar a observar el estado de la alfabetización visual en usuarios de nuevas tecnologías y nuevos medios. A pesar de diversos trabajos que tratan este tema y sus desafíos, es necesario seguir mejorando la investigación en esta área mediante la aplicación de técnicas y que den lugar a soluciones estandarizadas, que permitan explorar nuevas formas de analizar e interpretar la alfabetización visual, evitando las soluciones pensadas para cada investigación o evaluando soluciones propuestas

On data-driven systems analyzing, supporting and enhancing users’ interaction and experience

[EN]The research areas of Human-Computer Interaction and Software Architectures have been traditionally treated separately, but in the literature, many authors made efforts to merge them to build better software systems. One of the common gaps between software engineering and usability is the lack of strategies to apply usability principles in the initial design of software architectures. Including these principles since the early phases of software design would help to avoid later architectural changes to include user experience requirements. The combination of both fields (software architectures and Human-Computer Interaction) would contribute to building better interactive software that should include the best from both the systems and user-centered designs. In that combination, the software architectures should enclose the fundamental structure and ideas of the system to offer the desired quality based on sound design decisions. Moreover, the information kept within a system is an opportunity to extract knowledge about the system itself, its components, the software included, the users or the interaction occurring inside. The knowledge gained from the information generated in a software environment can be used to improve the system itself, its software, the users’ experience, and the results. So, the combination of the areas of Knowledge Discovery and Human-Computer Interaction offers ideal conditions to address Human-Computer-Interaction-related challenges. The Human-Computer Interaction focuses on human intelligence, the Knowledge Discovery in computational intelligence, and the combination of both can raise the support of human intelligence with machine intelligence to discover new insights in a world crowded of data. This Ph.D. Thesis deals with these kinds of challenges: how approaches like data-driven software architectures (using Knowledge Discovery techniques) can help to improve the users' interaction and experience within an interactive system. Specifically, it deals with how to improve the human-computer interaction processes of different kind of stakeholders to improve different aspects such as the user experience or the easiness to accomplish a specific task. Several research actions and experiments support this investigation. These research actions included performing a systematic literature review and mapping of the literature that was aimed at finding how the software architectures in the literature have been used to support, analyze or enhance the human-computer interaction. Also, the actions included work on four different research scenarios that presented common challenges in the Human- Computer Interaction knowledge area. The case studies that fit into the scenarios selected were chosen based on the Human-Computer Interaction challenges they present, and on the authors’ accessibility to them. The four case studies were: an educational laboratory virtual world, a Massive Open Online Course and the social networks where the students discuss and learn, a system that includes very large web forms, and an environment where programmers develop code in the context of quantum computing. The development of the experiences involved the review of more than 2700 papers (only in the literature review phase), the analysis of the interaction of 6000 users in four different contexts or the analysis of 500,000 quantum computing programs. As outcomes from the experiences, some solutions are presented regarding the minimal software artifacts to include in software architectures, the behavior they should exhibit, the features desired in the extended software architecture, some analytic workflows and approaches to use, or the different kinds of feedback needed to reinforce the users’ interaction and experience. The results achieved led to the conclusion that, despite this is not a standard practice in the literature, the software environments should embrace Knowledge Discovery and datadriven principles to analyze and respond appropriately to the users’ needs and improve or support the interaction. To adopt Knowledge Discovery and data-driven principles, the software environments need to extend their software architectures to cover also the challenges related to Human-Computer Interaction. Finally, to tackle the current challenges related to the users’ interaction and experience and aiming to automate the software response to users’ actions, desires, and behaviors, the interactive systems should also include intelligent behaviors through embracing the Artificial Intelligence procedures and techniques

On Data-driven systems analyzing, supporting and enhancing users’ interaction and experience

Tesis doctoral en inglés y resumen extendido en español[EN] The research areas of Human-Computer Interaction and Software Architectures have been traditionally treated separately, but in the literature, many authors made efforts to merge them to build better software systems. One of the common gaps between software engineering and usability is the lack of strategies to apply usability principles in the initial design of software architectures. Including these principles since the early phases of software design would help to avoid later architectural changes to include user experience requirements. The combination of both fields (software architectures and Human-Computer Interaction) would contribute to building better interactive software that should include the best from both the systems and user-centered designs. In that combination, the software architectures should enclose the fundamental structure and ideas of the system to offer the desired quality based on sound design decisions. Moreover, the information kept within a system is an opportunity to extract knowledge about the system itself, its components, the software included, the users or the interaction occurring inside. The knowledge gained from the information generated in a software environment can be used to improve the system itself, its software, the users’ experience, and the results. So, the combination of the areas of Knowledge Discovery and Human-Computer Interaction offers ideal conditions to address Human-Computer-Interaction-related challenges. The Human-Computer Interaction focuses on human intelligence, the Knowledge Discovery in computational intelligence, and the combination of both can raise the support of human intelligence with machine intelligence to discover new insights in a world crowded of data. This Ph.D. Thesis deals with these kinds of challenges: how approaches like data-driven software architectures (using Knowledge Discovery techniques) can help to improve the users' interaction and experience within an interactive system. Specifically, it deals with how to improve the human-computer interaction processes of different kind of stakeholders to improve different aspects such as the user experience or the easiness to accomplish a specific task. Several research actions and experiments support this investigation. These research actions included performing a systematic literature review and mapping of the literature that was aimed at finding how the software architectures in the literature have been used to support, analyze or enhance the human-computer interaction. Also, the actions included work on four different research scenarios that presented common challenges in the Human-Computer Interaction knowledge area. The case studies that fit into the scenarios selected were chosen based on the Human-Computer Interaction challenges they present, and on the authors’ accessibility to them. The four case studies were: an educational laboratory virtual world, a Massive Open Online Course and the social networks where the students discuss and learn, a system that includes very large web forms, and an environment where programmers develop code in the context of quantum computing. The development of the experiences involved the review of more than 2700 papers (only in the literature review phase), the analysis of the interaction of 6000 users in four different contexts or the analysis of 500,000 quantum computing programs. As outcomes from the experiences, some solutions are presented regarding the minimal software artifacts to include in software architectures, the behavior they should exhibit, the features desired in the extended software architecture, some analytic workflows and approaches to use, or the different kinds of feedback needed to reinforce the users’ interaction and experience. The results achieved led to the conclusion that, despite this is not a standard practice in the literature, the software environments should embrace Knowledge Discovery and data-driven principles to analyze and respond appropriately to the users’ needs and improve or support the interaction. To adopt Knowledge Discovery and data-driven principles, the software environments need to extend their software architectures to cover also the challenges related to Human-Computer Interaction. Finally, to tackle the current challenges related to the users’ interaction and experience and aiming to automate the software response to users’ actions, desires, and behaviors, the interactive systems should also include intelligent behaviors through embracing the Artificial Intelligence procedures and techniques

Actas de los Premios de Investigación e Innovación de Educación Secundaria Obligatoria, Bachillerato y Formación Profesional de Castilla y León 2017 (PIIECYL 2017)

[ES]Libro de Actas de los Premios de Investigación e Innovación de Educación Secundaria Obligatoria, Bachillerato y Formación Profesional de Castilla y León 2017 (PIIECYL 2017), organizados por la Junta de Castilla y León en colaboración con el Instituto Universitario de Ciencias de la Educación (IUCE) y el Grupo de Investigación en InteraAcción y eLearning (GRIAL) de la Universidad de Salamanc

Automatic generation of software interfaces for supporting decisionmaking processes. An application of domain engineering & machine learning

[EN] Data analysis is a key process to foster knowledge generation in particular domains or fields of study. With a strong informative foundation derived from the analysis of collected data, decision-makers can make strategic choices with the aim of obtaining valuable benefits in their specific areas of action. However, given the steady growth of data volumes, data analysis needs to rely on powerful tools to enable knowledge extraction. Information dashboards offer a software solution to analyze large volumes of data visually to identify patterns and relations and make decisions according to the presented information. But decision-makers may have different goals and, consequently, different necessities regarding their dashboards. Moreover, the variety of data sources, structures, and domains can hamper the design and implementation of these tools. This Ph.D. Thesis tackles the challenge of improving the development process of information dashboards and data visualizations while enhancing their quality and features in terms of personalization, usability, and flexibility, among others. Several research activities have been carried out to support this thesis. First, a systematic literature mapping and review was performed to analyze different methodologies and solutions related to the automatic generation of tailored information dashboards. The outcomes of the review led to the selection of a modeldriven approach in combination with the software product line paradigm to deal with the automatic generation of information dashboards. In this context, a meta-model was developed following a domain engineering approach. This meta-model represents the skeleton of information dashboards and data visualizations through the abstraction of their components and features and has been the backbone of the subsequent generative pipeline of these tools. The meta-model and generative pipeline have been tested through their integration in different scenarios, both theoretical and practical. Regarding the theoretical dimension of the research, the meta-model has been successfully integrated with other meta-model to support knowledge generation in learning ecosystems, and as a framework to conceptualize and instantiate information dashboards in different domains. In terms of the practical applications, the focus has been put on how to transform the meta-model into an instance adapted to a specific context, and how to finally transform this later model into code, i.e., the final, functional product. These practical scenarios involved the automatic generation of dashboards in the context of a Ph.D. Programme, the application of Artificial Intelligence algorithms in the process, and the development of a graphical instantiation platform that combines the meta-model and the generative pipeline into a visual generation system. Finally, different case studies have been conducted in the employment and employability, health, and education domains. The number of applications of the meta-model in theoretical and practical dimensions and domains is also a result itself. Every outcome associated to this thesis is driven by the dashboard meta-model, which also proves its versatility and flexibility when it comes to conceptualize, generate, and capture knowledge related to dashboards and data visualizations