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Item Content-validation questionnaire of a meta-model to ease the learning of data visualization concepts(CEUR-WS.org, 2022-10-09) Vázquez-Ingelmo, A.; García-Holgado, A.; García-Peñalvo, F. J.; Therón, R.; Colomo-Palacios, R.Data visualizations and dashboards are powerful means to convey information to large audiences. However, the design and understanding of these tools are not straightforward because several factors are involved. It is essential to rely on theoretical frameworks to design and implement data visualizations for these reasons. In this context, we propose a meta-model to identify and arrange the main characteristics and elements of data visualizations and dashboards. The proposed meta-model provides a powerful artifact to generate information visualizations and dashboards automatically, but also a learning resource to understand how data visualizations elements interact and influence each other. However, it is necessary to validate this artifact to ensure its quality and usefulness. In this paper, we present a work-in-progress or a quality assessment and content validation of the me-ta-model to seek weaknesses and tackle them in subsequent iterations.Item KoopaML, a Machine Learning platform for medical data analysis(Brazilian Computing Society (SBC), 2022-08-20) García-Holgado, A.; Vázquez-Ingelmo, A.; Alonso-Sánchez, J.; García-Peñalvo, F. J.; Therón, R.; Sampedro-Gómez, J.; Sánchez-Puente, A.; Vicente-Palacios, V.; Dorado-Díaz, P. I..; Sánchez, P. L.Machine Learning allows facing complex tasks related to data analysis with big datasets. This Artificial Intelligence branch allows not technical contexts to get benefits related to data processing and analysis. In particular, in medicine, medical professionals are increasingly interested in Machine Learning to identify patterns in clinical cases and make predictions regarding health issues. However, many do not have the necessary programming or technological skills to perform these tasks. Many different tools focus on developing Machine Learning pipelines, from libraries for developers and data scientists to visual tools for experts or platforms to learn. However, we have identified some requirements in the medical context that raise the need to create a customized platform adapted to end-user found in this context. This work describes the design process and the first version of KoopaML, an ML platform to bridge the data science gaps of physicians while automatizing Machine Learning pipelines. The platform is focused on enhanced interactivity to improve the engagement of physicians while still providing all the benefits derived from the introduction of Machine Learning pipelines in medical departments, as well as integrated ongoing training during the use of the tool’s featuresItem Following up the progress of doctoral students and advisors’ workload through data visualizations: a case study in a PhD program(CEUR-WS.org, 2021-07-07) Vázquez-Ingelmo, A.; García-Holgado, A.; Hernández-Payo, H.; García-Peñalvo, F. J.; Therón, R.One of the most important aspects to consider during the development of a PhD is the students’ progress, both for their advisors and the students themselves. However, several achievements of different natures are involved during a PhD (research stays, publications, seminars, research plans, etc.). For these reasons, we propose a set of data visualizations to support decision-making processes in a PhD program. A preliminary requirement elicitation process was carried out to obtain a design basis for the implementation and integration of these tools in the PhD portal. Once the visualizations were implemented, a usability study was performed to measure the perceived usability of the newly added PhD portal functionalities. This paper presents the design process and usability study outcomes of applying data visualizations to the learning outcomes of the PhD Programme in Education in the Knowledge Society at the University of Salamanca.Item Development of a SPOC of Computer Ethics for students of Computer Science degree(IEEE, 2021-09-30) García-Holgado, A.; García-Peñalvo, F. J.; Therón, R.; Vázquez-Ingelmo, A.; Gamazo-García, A.; González-González, C. S.; Gil Iranzo, R.; Frango Silveira, I.; Alier-Forment, M.Technology brings different benefits to society and involves challenges and ethical dilemmas that must be considered during any technology development. In this sense, graduates must recognise the social, legal, ethical and cultural issues inherent to the discipline of computer science. However, there is a lack of integration of computer ethics in the computer science curriculum in Spanish universities. This work introduces a pilot experience to develop a Small Private Open Course (SPOC) to introduce computer ethics as an extracurricular activity in the Bachelor’s Degree of Computer Engineering at the University of Salamanca.Item Experiencia piloto para incorporar la ética informática de forma transversal en el Grado de Ingeniería Informática(Servicio de Publicaciones Universidad de Zaragoza, 2021-10-20) García-Holgado, A.; García-Peñalvo, F. J.; Therón, R.; Vázquez-Ingelmo, A.; Gamazo, A.; González-González, C. S.; Gil Iranzo, R. M.; Frango Silveira, I.; Alier-Forment, M.Cuando se realiza cualquier desarrollo software se deben tener en cuenta una serie de implicaciones éticas relacionadas con el impacto que ese desarrollo puede tener en los valores humanos y sociales. En este sentido, de acuerdo con el ACM/IEEE-CS Computer Science Curriculum 2013, los graduados deben ser capaces de reconocer las cuestiones sociales, jurídicas, éticas y culturales inherentes a la disciplina de la informática. El presente trabajo describe una experiencia de innovación docente cuyo objetivo es incorporar los aspectos éticos relacionados con el desarrollo software en el Grado en Ingeniería Informática a través de un SPOC (Small Private Open Course). Para ello, se han realizado un conjunto de charlas online en torno al temario del SPOC, de tal forma que al finalizar el curso, se dispone de los recursos base para crear un conjunto de píldoras de vídeo.Item A Dashboard to Support Decision-Making Processes in Learning Ecosystems: A Metamodel Integration(ACM, 2020-11-06) Vázquez-Ingelmo, A.; García-Holgado, A.; García-Peñalvo, F. J.; Therón, R.There are software solutions to solve most of the problems related to information management in any company or institutions, but still, there is a problem for transforming information into knowledge. Technological ecosystems emerge as a solution to combine existing tools and human resources to solve different problems of knowledge management. In particular, when the ecosystem is focused on learning processes associated with knowledge are named learning ecosystems. The learning ecosystem metamodel defined in previous works solves several problems related to the definition and implementation of these solutions. However, there are still challenges associated with improving the analysis and visualization of information as a way to discover knowledge and support decision making processes. On the other hand, there is a metamodel proposal to define customized dashboards for supporting decision-making processes. This proposal aims to integrate both metamodels as a way to improve the definition of learning ecosystems.Item A meta-model to develop learning ecosystems with support for knowledge discovery and decisionmaking processes(IEEE, 2020-06-24) Vázquez-Ingelmo, A.; García-Holgado, A.; García-Peñalvo, F. J.; Therón, R.There are software solutions to solve most of the problems related to information management in any company or institutions, but still, there is a problem for transforming information into knowledge. Technological ecosystems emerge as a solution to combine existing tools and human resources to solve different problems of knowledge management. In particular, when the ecosystem is focused on learning processes associated with knowledge are named learning ecosystems. The learning ecosystem metamodel defined in previous works solves several problems related to the definition and implementation of these solutions. However, there are still challenges associated with improving the analysis and visualization of information as a way to discover knowledge and support decision making processes. On the other hand, there is a metamodel proposal to define customized dashboards for supporting decision-making processes. This proposal aims to integrate both metamodels as a way to improve the definition of learning ecosystems.Item A Meta-modeling Approach to Take into Account Data Domain Characteristics and Relationships in Information Visualizations(Springer, 2021-03-30) Vázquez-Ingelmo, A.; García-Holgado, A.; García-Peñalvo, F. J.; Therón, R.Visual explanations are powerful means to convey information to large audiences. However, the design of information visualizations is a complex task, because a lot of factors are involved (the audience profile, the data domain, etc.). The complexity of this task can lead to poor designs that could make users reach wrong conclusions from the visualized data. This work illustrates the process of identifying features that could make an information visualization confusing or even misleading with the goal of arranging them into a meta-model. The meta-model provides a powerful resource to automatically generate information visu-alizations and dashboards that take into account not only the input data, but also the audience’s characteristics, the available data domain knowledge and even the data context.Item Specifying information dashboards’ interactive features through meta-model instantiation(CEUR-WS.org, 2020-09-19) Vázquez-Ingelmo, A.; García-Peñalvo, F. J.; Therón, R.; García-Holgado, A.Information dashboards1 can be leveraged to make informed decisions with the goal of improving policies, processes, and results in different contexts. However, the design process of these tools can be convoluted, given the variety of profiles that can be involved in decision-making processes. The educative context is one of the contexts that can benefit from the use of information dashboards, but given the diversity of actors within this area (teachers, managers, students, researchers, etc.), it is necessary to take into account different factors to deliver useful and effective tools. This work describes an approach to generate information dashboards with interactivity capabilities in different contexts through meta-modeling. Having the possibility of specifying interaction patterns within the generative workflow makes the personalization process more fine-grained, allowing to match very specific requirements from the user. An example of application within the context of Learning Analytics is presented to demonstrate the viability of this approach.Item A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare(MDPI, 2020-07-22) Vázquez-Ingelmo, A.; García-Holgado, A.; García-Peñalvo, F. J.; Therón, R.Knowledge management is one of the key priorities of many organizations. They face different challenges in the implementation of knowledge management processes, including the transformation of tacit knowledge—experience, skills, insights, intuition, judgment and know-how—into explicit knowledge. Furthermore, the increasing number of information sources and services in some domains, such as healthcare, increase the amount of information available. Therefore, there is a need to transform that information in knowledge. In this context, learning ecosystems emerge as solutions to support knowledge management in a different context. On the other hand, the dashboards enable the generation of knowledge through the exploitation of the data provided from different sources. The model-driven development of these solutions is possible through two meta-models developed in previous works. Even though those meta-models solve several problems, the learning ecosystem meta-model has a lack of decision-making support. In this context, this work provides two main contributions to face this issue. First, the definition of a holistic meta-model to support decision-making processes in ecosystems focused on knowledge management, also called learning ecosystems. The second contribution of this work is an instantiation of the presented holistic meta-model in the healthcare domain