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Permanent URI for this collectionhttps://repositorio.grial.eu/handle/123456789/34
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Item Evaluating the Effectiveness of Human-Centered AI Systems in Education(Departamento de Informática y Automática. Universidad de Salamanca, 2024-03-01) Shoeibi, N.; Therón, R.; García-Peñalvo, F. J.This thesis examines how AI can improve human-computer interaction (HCI) and user experience in education. A systematic litera-ture review (SLR) and LATILL case study show how AI can be used in education. The SLR examines existing literature to determine how AI af-fects user experience and HCI in education, highlighting personalization and adaptability of learning experiences, improved task performance, and improved user experience for teachers and students. AI implementation in education faces obstacles. Using CEFR levels and linguistic traits, the LATILL project uses a user-centered design to give students personali-zed guidance and support. It transforms language instruction and fosters engaging and successful learning by encouraging educator collaboration and resource sharing. This study emphasizes the importance of user ex-perience and HCI principles in designing AI-driven educational systems. AI and user-centered design can improve learning, student engagement, and educational outcomes.Item A proposal to measure the understanding of data visualization elements in visual analytics applications(CEUR-WS.org, 2022-10-09) Vázquez-Ingelmo, A.; García-Peñalvo, F. J.; Therón, R.; Byrd, V.; Camba, J. D.Data visualizations and information dashboards are useful but complex tools. They must be fully understood to draw proper insights and to avoid misleading conclusions. However, several elements and factors are involved in this domain, which makes it difficult to learn. In previous works, we proposed a meta-model to capture the primitive elements that compose visualizations and dashboards. This meta-model has served as a framework for conducting data visualization research, but also to develop a graphical tool for generating data visualizations and dashboards. This tool (namely MetaViz) enables users to create data visualizations through fine-grained components based on the entities represented in the meta-model. The main goal of the system is to provide a learning experience in which users can freely add and configure elements to understand how they influence the final display. This work describes work in progress to validate the pedagogical value of MetaViz in terms of the understanding of data visualization concepts.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 Enabling adaptability in web forms based on user characteristics detection through A/B testing and machine learning(IEEE, 2018-02-14) Cruz-Benito, J.; Vázquez-Ingelmo, A.; Sánchez-Prieto, J. C.; Therón, R.; García-Peñalvo, F. J.; Martín-González, M.This paper presents an original study with the aim of improving users' performance in completing large questionnaires through adaptability in web forms. Such adaptability is based on the application of machine-learning procedures and an A/B testing approach. To detect the user preferences, behavior, and the optimal version of the forms for all kinds of users, researchers built predictive models using machine-learning algorithms (trained with data from more than 3000 users who participated previously in the questionnaires), extracting the most relevant factors that describe the models, and clustering the users based on their similar characteristics and these factors. Based on these groups and their performance in the system, the researchers generated heuristic rules between the different versions of the web forms to guide users to the most adequate version (modifying the user interface and user experience) for them. To validate the approach and con rm the improvements, the authors tested these redirection rules on a group of more than 1000 users. The results with this cohort of users were better than those achieved without redirection rules at the initial stage. Besides these promising results, the paper proposes a future study that would enhance the process (or automate it) as well as push its application to other eldsItem 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 Advances in the use of domain engineering to support feature identification and generation of information visualizations(ACM, 2020-10-21) Vázquez-Ingelmo, A.; García-Peñalvo, F. J.; Therón, R.Information visualization tools are widely used to better understand large and complex datasets. However, to make the most out of them, it is necessary to rely on proper designs that consider not only the data to be displayed, but also the audience and the context. There are tools that already allow users to configure their displays without requiring programming skills, but this research project aims at exploring the automatic generation of information visualizations and dashboards in order to avoid the configuration process, and select the most suitable features of these tools taking into account their contexts. To address this problem, a domain engineering, and machine learning approach is proposed.