Persona:
González Boticario, Jesús

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ORCID
0000-0003-4949-9220
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González Boticario
Nombre de pila
Jesús
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2013 - 20175
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Nivel de acceso: info:eu-repo/semantics/closedAccess × Autor: Santos, Olga C. ×

Resultados de la búsqueda

Mostrando 1 - 5 de 5
  • Miniatura
    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.
  • Miniatura
    Publicación
    Supporting growers with recommendations in redvides: some human aspects involved
    (Springer Nature, 2014-10-10) Santos, Olga C.; Salmeron Majadas, Sergio; González Boticario, Jesús
    This paper discusses some human aspects that are to be considered when designing recommendations for RedVides, a cloud based networking environment that collects the status of the crop with sensors and can take decisions through corresponding actuators. The goal behind is to support growers in decision making processes, which can be benefited from collaborations among growers and with other stakeholders.
  • Miniatura
    Publicación
    Exploring arduino for building educational context-aware recommender systems that deliver affective recommendations in social ubiquitous networking environments
    (Springer, 2014-10-10) Santos, Olga C.; González Boticario, Jesús
    One of the most challenging context features to detect when making recommendations in educational scenarios is the learner’s affective state. Usually, this feature is explicitly gathered from the learner herself through questionnaires or self-reports. In this paper, we analyze if affective recommendations can be produced with a low cost approach using the open source electronics prototyping platform Arduino together with corresponding sensors and actuators. TORMES methodology (which combines user centered design methods and data mining techniques) can support the recommendations elicitation process by identifying new recommendation opportunities in these emerging social ubiquitous networking scenarios.
  • Miniatura
    Publicación
    Towards multimodal affective detection in educational systems through mining emotional data sources
    (Springer Nature, 2015) Salmeron Majadas, Sergio; Santos, Olga C.; González Boticario, Jesús
    This paper introduces the work being carried out in an ongoing PhD research focused on the detection of the learners’ affective states by combining different available sources (from physiological sensors to keystroke analysis). Different data mining algorithms and data labeling techniques have been used generating 735 prediction models. Results so far show that predictive models on affective state detection from multimodal-based approaches provide better accuracy rates than single-based.
  • Miniatura
    Publicación
    Inclusive personalized e-Learning based on affective adaptive support
    (Springer Nature, 2013) Salmeron Majadas, Sergio; Santos, Olga C.; González Boticario, Jesús
    Emotions and learning are closely related. In the PhD research presented in this paper, that relation has to be taken advantage of. With this aim, within the framework of affective computing, the main goal proposed is modeling learner’s affective state in order to support adaptive features and provide an inclusive personalized e-learning experience. At the first stage of this research, emotion detection is the principal issue to cope with. A multimodal approach has been proposed, so gathering data from diverse sources to feed data mining systems able to supply emotional information is being the current ongoing work. On the next stages, the results of these data mining systems will be used to enhance learner models and based on these, offer a better e-learning experience to improve learner’s results.