This paper is about a mini-course that we developed to train teachers, how to teach basic mathematic concepts to their students by relating those concepts to a popular game like "Candy Crush". In order to facilitate this process, we used GeoGebra, a free and open source application that is frequently used for teaching mathematics. The Mini-Course is being delivered through a WordPress platform. This idea may be extended, afterwards, to other mathematical concepts and other games.
ResumenEste trabajo expone, mediante el uso de técnicas de minería de datos e inteligencia artificial, una alternativa para determinar posibles factores ajenos a los académicos que puedan interferir de manera positiva o negativa en la calidad del aprendizaje de estudiantes universitarios del área de Matemática. Para tal fin se relevó una serie de datos socioeconómicos considerados relevantes por especialistas, sociólogos y pedagogos, incorporando adicionalmente una serie de evaluaciones prediseñadas con aspectos conceptuales, algebraicos y de modelización. Se emplea el método de clasificación bietápico el cual es una herramienta de exploración diseñada para descubrir las agrupaciones naturales (o conglomerados) de un conjunto de datos que, de otra manera, no sería posible detectar. A partir de este agrupamiento se establecerá la base para la elaboración de reglas que alimentarán al sistema experto para la formulación de conclusiones y recomendaciones para los estudiantes y docentes.Palabras clave: Algoritmos de agrupamiento, arquitectura, problemas en el aprendizaje, minería de datos, sistemas expertos.
Today the increasing complexity of the computer systems used in industry, medicine field and even in everyday life often requires other systems to monitor and control its correct functioning. These monitoring and control systems in turn, require some analysis and interpretation of the indicators provided to later make decisions for the context presented. This analysis needs a human cognitive process based on knowledge previously acquired by experience or a predefined decision flow, generally through an operation manual. Speech and voice recognition systems tend to be highly effective in reducing analysis time and allowing accurately summarizing and interpreting an emergency or high criticality. This paper develops a proposed architecture that provides a mechanism to monitor industrial computer systems with voice interpreter that warns of predefined critical situations using free-license tools.
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