LA MINERÍA DE DATOS APLICADA A LA GESTIÓN DOCENTE DE LA UNIVERSIDAD NACIONAL EXPERIMENTAL DE LAS FUERZAS ARMADAS (UNEFA)

La Universidad Nacional Experimental de las Fuerzas Armadas (UNEFA) cuenta con un sistema estandarizado de gestión para la docencia, que registra toda la información relacionada con los estudiantes, sin embargo, en el momento de tomar alguna decisión sobre el aprovechamiento docente de los estudiantes en los primeros años de la carrera, no tiene en cuenta el conocimiento oculto (información no evidente, desconocida a priori y potencialmente útil) de los datos que mantiene almacenados para sustentar determinadas líneas estratégicas en el proceso enseñanza-aprendizaje. El objetivo de la presente investigación es crear una herramienta de evaluación de los estudiantes de nuevo ingreso, a partir del empleo de técnicas de minería de datos que permita a los profesores mejorar los métodos pedagógicos y didácticos en la formación de profesional altamente calificados en la UNEFA. Se realizan cuatro tareas de minería, relacionadas con la asociación, el agrupamiento, la selección de atributos y la clasificación, desarrollándose un total de 48 experimentos, aplicando la metodología CRISP-MD. Como resultados de la la investigación se obtuvieron un conjunto de reglas que presentan parámetros aceptados para ser consideradas útiles durante la toma de decisiones por la Junta Directiva de la UNEFA. La investigación realizada aporta nuevos conocimientos, que permiten redefinir algunos objetivos del negocio, y replantearse un nuevo proceso de KDD

E3: Emotions, Engagement, and Educational Digital Games

The use of educational digital games as a method of instruction for science, technology, engineering, and mathematics has increased in the past decade. While these games provide successfully implemented interactive and fun interfaces, they are not designed to respond or remedy students’ negative affect towards the game dynamics or their educational content. Therefore, this exploratory study investigated the frequent patterns of student emotional and behavioral response to educational digital games. To unveil the sequential occurrence of these affective states, students were assigned to play the game for nine class sessions. During these sessions, their affective and behavioral response was recorded to uncover possible underlying patterns of affect (particularly confusion, frustration, and boredom) and behavior (disengagement). In addition, these affect and behavior frequency pattern data were combined with students’ gameplay data in order to identify patterns of emotions that led to a better performance in the game. The results provide information on possible affect and behavior patterns that could be used in further research on affect and behavior detection in such open-ended digital game environments. Particularly, the findings show that students experience a considerable amount of confusion, frustration, and boredom. Another finding highlights the need for remediation via embedded help, as the students referred to peer help often during their gameplay. However, possibly because of the low quality of the received help, students seemed to become frustrated or disengaged with the environment. Finally, the findings suggest the importance of the decay rate of confusion; students’ gameplay performance was associated with the length of time students remained confused or frustrated. Overall, these findings show that there are interesting patterns related to students who experience relatively negative emotions during their gameplay