A Framework for Students Profile Detection

Some of the biggest problems tackling Higher Education Institutions are students’ drop-out and academic disengagement. Physical or psychological disabilities, social-economic or academic marginalization, and emotional and affective problems, are some of the factors that can lead to it. This problematic is worsened by the shortage of educational resources, that can bridge the communication gap between the faculty staff and the affective needs of these students. This dissertation focus in the development of a framework, capable of collecting analytic data, from an array of emotions, affects and behaviours, acquired either by human observations, like a teacher in a classroom or a psychologist, or by electronic sensors and automatic analysis software, such as eye tracking devices, emotion detection through facial expression recognition software, automatic gait and posture detection, and others. The framework establishes the guidance to compile the gathered data in an ontology, to enable the extraction of patterns outliers via machine learning, which assist the profiling of students in critical situations, like disengagement, attention deficit, drop-out, and other sociological issues. Consequently, it is possible to set real-time alerts when these profiles conditions are detected, so that appropriate experts could verify the situation and employ effective procedures. The goal is that, by providing insightful real-time cognitive data and facilitating the profiling of the students’ problems, a faster personalized response to help the student is enabled, allowing academic performance improvements

Music Composed For Calm And Catharsis Using A Compositional Toolkit For Emotional Evocation - Inspired By And Directed Towards Healthcare Contexts And Self-Managed Wellness

Emotional experience through music listening is a universal experience. In the age of COVID-19 and an ever-mentally enslaved population, music that encourages calm and/or catharsis is more relevant than ever (Gallagher et al., 2020). As composers, can we form a framework for and create music to pointedly evoke an intentional emotion? This dissertation seeks to build on the solid foundation of music and emotion researchers’ past theories, and demonstrate how to further utilise the power that music has in both our everyday lives, and also in healthcare settings – providing an output of a large suite of music for use for calm and catharsis, and a Compositional Toolbox for Emotional Evocation that composers might use to effect positive emotional change. In two pilot studies: one for children and one for adults, this dissertation tests music written using said Toolbox, to observe its effect on arousal and pleasure. The studies also utilise visuals as a secondary means of sensory control, and to investigate whether the multisensory application of music and visuals enhances emotional evocation over isolated experience. Participants rated on a Likert-type scale, how they think each sample would make someone feel, or how it made them feel. An analysis of pieces from these studies is included in this dissertation. Mixed-method, deductive, and thematic analysis was used for data, which was collected via surveys and interviews. It was found that music using the Toolbox was more emotionally evocative, more calming, and happier overall than that written without. Most of the pieces achieved their emotional aims, and positive correlations between the use of music and visuals together have arisen. Music without the visuals appeared to be calmer than that with visuals in one of the studies. This dissertation begins to promote the use of the Compositional Toolbox for Emotional Evocation as a framework for emotional composition

Innovación disruptiva para la educación superior. Implementación en América Latina

La cuarta revolución industrial plantea cambios y transformaciones en todos los ámbitos de la sociedad y la educación no es la excepción; problemáticas tradicionales que enfrenta la educación superior como la deserción, el comportamiento y la diversidad estudiantil, son analizadas desde enfoques fisiológicos y emocionales, ante ello, se plantean diversas iniciativas de soluciones con base en tecnologías disruptivas como la Inteligencia Artificial, la computación afectiva y la web semántica denominadas en el libro como estudios de casos donde se describen las innovaciones con tecnologías disruptivas. Finalmente, y ante la gran interrogante y preocupación de académicos y científicos; por el desarrollo de la robótica, las inteligencias artificiales y de software en general se abordan las cuestiones y el impacto ético