Aprendizaje experiencial en ciencia de datos: satisfacción de los estudiantes para tres modelos de enseñanza y aprendizaje [Experiential learning in data science: student satisfaction for three models of teaching and learning]
Serrano, Emilio (Universidad Politécnica de Madrid, España) ; Molina, Martin (Universidad Politécnica de Madrid, España) ; Manrique, Daniel (Universidad Politécnica de Madrid, España) ; Baumela, Luis (Universidad Politécnica de Madrid, España) ; Zanardini, Damiano (Universidad Politécnica de Madrid, España)Abstract: La Ciencia de Datos es una revolución que ya está cambiando la manera en la que nos ocupamos de sanidad, política, educación e innovación. Hay una gran variedad de cursos online, másteres, grados, y asignaturas que se enfocan a la enseñanza de este campo interdisciplinar, donde existe una demanda creciente de profesionales. Este artículo describe tres modelos de enseñanza y aprendizaje diferentes para Ciencia de Datos, inspirados en el paradigma del aprendizaje experiencial. Además, estos modelos han sido empleados en una asignatura de Deep Learning, dentro del contexto de un máster internacional de Ciencia de Datos. Finalmente, la satisfacción de los estudiantes es cuantificada por medio de una encuesta para: evaluar los tres modelos, decidir el enfoque favorito y considerar una metodología de aprendizaje experiencial pura.X49
[Data science is a revolution that is already changing the way we do business, healthcare, politics, education and innovation. There is a great variety of online courses, masters, degrees, and modules that address the teaching of this interdisciplinary field, where is a growing demand of professionals. This paper describes three different teaching and learning models for Data Science inspired by the experiential learning paradigm. Moreover, these models have been employed in a Deep Learning course in the context of an international master of data science. Finally, the student satisfaction is quantified by a survey to: evaluate the three models, decide their favorite approach, and consider a pure experiential learning methodology. ]
[Data science is a revolution that is already changing the way we do business, healthcare, politics, education and innovation. There is a great variety of online courses, masters, degrees, and modules that address the teaching of this interdisciplinary field, where is a growing demand of professionals. This paper describes three different teaching and learning models for Data Science inspired by the experiential learning paradigm. Moreover, these models have been employed in a Deep Learning course in the context of an international master of data science. Finally, the student satisfaction is quantified by a survey to: evaluate the three models, decide their favorite approach, and consider a pure experiential learning methodology. ]
Idioma: Español
DOI: 10.26754/CINAIC.2017.000001_058
Año: 2017
En: IV Congreso Internacional sobre Aprendizaje, Innovación y Competitividad-CINAIC (Zaragoza 4-6 Octubre 2017)
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Record created 2017-09-26, last modified 2017-11-07
