Persona: González Boticario, Jesús
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0000-0003-4949-9220
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González Boticario
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Jesús
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Publicación Red de Innovación Docente Accesibilidad y Diversidad Funcional en la Educación Superior: Análisis y desarrollo de los Servicios TIC requeridos(UNED, 2009-09) Campo, Elena del; González Boticario, Jesús; Saneiro Silva, María del Mar; Rodríguez Ascaso, Alejandro; Finat Walford, Cecilia RosaPublicación Should Conditional Self-Driving Cars Consider the State of the Human Inside the Vehicle?(ACM, 2021-06-22) Puertas Ramírez, David; Serrano Mamolar, Ana; Martín Gómez, David; González Boticario, JesúsAutonomous vehicles with conditional automation are said to be the next step in the development of self-driving cars. The human driver still performs a critical role in them, by taking over the control of the vehicle if prompted. As the technology is still facing pending challenges, the human drivers are also required to be able to detect and react in case of Autonomous Drive System (ADS) malfunctions. Within this context, in this work we argue that to assure safety during autonomous operation the user state should be measured all the time, which is intended to support a ”fallback ready state”. From an in-depth literature review, this article identifies the human factors involved in the aforementioned ”fallback ready state” that affect the personalization of human-vehicle interaction.Publicación BIG-AFF: Exploring low cost and low intrusive infrastructures for affective computing in secondary schools(ACM, 2017-07-09) González Boticario, Jesús; Santos, Olga C.; Cabestrero Alonso, Raúl; Quirós Expósito, Pilar; Salmeron Majadas, Sergio; Uría Rivas, Raúl; Arevalillo Herráez, Miguel; Ferri, Francesc J.Recent research has provided solid evidence that emotions strongly affect motivation and engagement, and hence play an important role in learning. In BIG-AFF project, we build on the hypothesis that ``it is possible to provide learners with a personalised support that enriches their learning process and experience by using low intrusive (and low cost) devices to capture affective multimodal data that include cognitive, behavioural and physiological information''. In order to deal with the affect management complete cycle, thus covering affect detection, modelling and feedback, there is lack of standards and consolidated methodologies. Being our goal to develop realistic affect-aware learning environments, we are exploring different approaches on how these can be supported by either by traditional non-intrusive interaction sources or low intrusive and inexpensive sensing devices. In this work we describe the main issues involved in two user studies carried out with high school learners, highlight some open problems that arose when designing the corresponding experimental settings. In particular, the studies involved varied nature of information sources and each focused on one of the approaches. Our experience reflects the need to develop an extensive knowledge about the organization of this type of experiences that consider user-centric development and evaluation methodologies.Publicación Changing technological infrastructure and services in higher education : towards a student-centred approach(2005-02-12) González Boticario, JesúsPublicación A Machine Learning Approach to Leverage Individual Keyboard and Mouse Interaction Behavior From Multiple Users in Real-World Learning Scenarios(Browse Journals & Magazines, 2018) Salmeron Majadas, Sergio; Baker, Ryan S.; Santos, Olga C.; González Boticario, Jesús; https://orcid.org/0000-0002-0544-0887; https://orcid.org/0000-0002-3051-3232; https://orcid.org/0000-0002-9281-4209There is strong evidence that emotions influence the learning process. For this reason, we explore the relevance of individual and general mouse and keyboard interaction patterns in real-world settings while learners perform free text tasks. To this end, we have modeled users' mouse movements and keystroke dynamics with data mining techniques, building on previous related research and extending it in terms of some critical modeling issues that may have an impact on detection results. Inspired by practice in affective computing where physiological sensors are used, we argue for the creation of an interaction baseline model, as a reference point in the way how learners interact with the keyboard and mouse. To make the proposed affective model feasible, we have adopted a simplified 2-D self-labeling approach for labeling the users' affective state. Our approach to affect detection improves results when there is a small amount of data instances available and does not require additional affect-oriented tasks from the learners. Specifically, learners are only asked to self-reflect their emotional state after finishing the tasks and immediately selecting two values in the affect scale. The approach we have followed aims to distill two types of interaction patterns: 1) within-subject patterns (from a single participant) and 2) between-subject patterns (across all participants). Doing this, we aim to combine both the approaches as modeling factors, thus taking advantage of individual and general interaction patterns to predict affect.Publicación Aprendizaje basado en tareas compartidas: una metodología consolidada para fomentar la involucración en el aprendizaje "online"(Universidad Nacional de Educación a Distancia (España). Instituto Universitario de Educación a Distancia (IUED), 2019) González Boticario, JesúsCualesquiera que sean los medios y circunstancias presentes en los procesos de enseñanza y aprendizaje, un objetivo siempre presente es lograr un aprendizaje en el que el estudiante se involucre realmente, a través de su trabajo y el de otros con los que comparte el proceso. Desde 2001 hasta la fecha se ha venido puliendo una estrategia de aprendizaje en cursos virtuales basada en tareas y en colaboración, aplicada en una gran variedad de escenarios, incluyendo asignaturas, cursos esporádicos y MOOC s. El planteamiento se basa en potenciar la adquisición de competencias de colaboración e interacción social. Se aprende construyendo documentación compartida y elaborando soluciones a partir de situaciones y casos reales de aplicación relacionados con la materia. Todo se realiza a través de la red y las fuentes de información abiertas son la base del proceso. Se resumen aquí algunos aspectos de interés en asignaturas de grado, máster y curso orientado a la investigación y doctorado. Los resultados son variados precisamente por la propia naturaleza de dichos cursos, siendo las asignaturas de grado en las que se observa mayor éxito.Publicación An Approach for an Affective Educational Recommendation Model(Springer, 2014-01-01) Santos, Olga C.; González Boticario, Jesús; Manjarrés Riesco, ÁngelesThere is agreement in the literature that affect influences learning. In turn, addressing affective issues in the recommendation process has shown their ability to increase the performance of recommender systems in non-educational scenarios. In our work, we combine both research lines and describe the SAERS approach to model affective educational recommendations. This affective recommendation model has been initially validated with the application of the TORMES methodology to specific educational settings. We report 29 recommendations elicited in 12 scenarios by applying this methodology. Moreover, a UML formalized version of the recommendations model which can describe the recommendations elicited is presented in the paper.Publicación Alf : un entorno abierto para el desarrollo de comunidades virtuales de trabajo y cursos adaptados a la educación superior(2005-02-23) Raffenne, Emmanuelle; Aguado, M.; Arroyo, D.; Cordova, M. A.; Guzmán Sánchez, José Luis; Hermira, S.; Ortíz, J.; Pesquera, A.; Morales, R.; Romojaro Gómez, Héctor; Valiente, S.; Carmona, G.; Tejedor, D.; Alejo, J. A.; García Saiz, Tomás; González Boticario, Jesús; Pastor Vargas, RafaelAlf, entorno de trabajo, comunidades virtuales, enseñanza superiorPublicación MAMIPEC - Affective modeling in inclusive personalized educational scenarios(IEEE Technical Committee on Learning Technology,, 2012) Santos, Olga C.; González Boticario, Jesús; Arevalillo Herráez, Miguel; Saneiro Silva, María del Mar; Cabestrero Alonso, Raúl; Campo Adrián, María del Campo; Manjarrés Riesco, Ángeles; Moreno Clarí, Paloma; Quirós Expósito, Pilar; Salmeron Majadas, SergioThere is agreement in the literature that affect influences learning. In turn, addressing affective issues in the recommendation process has shown their ability to increase the performance of recommender systems in non-educational scenarios. In our work, we combine both research lines and describe the SAERS approach to model affective educational recommendations. This affective recommendation model has been initially validated with the application of the TORMES methodology to specific educational settings. We report 29 recommendations elicited in 12 scenarios by applying this methodology. Moreover, a UML formalized version of the recommendations model which can describe the recommendations elicited is presented in the paper.Publicación Fundamentos de la virtualización : experiencia en investigación y formación del profesorado(Facultad de Ciencias UNED, 2001-02-23) González Boticario, Jesús
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