No abstract

The curricular inclusion of topics, study plans, and teaching programs related to the study of Data Science has been trending mostly in higher-level education for the last years. However, the previous knowledge requirements for students to adequately assimilate these lessons are more specialised than the ones they obtain during secondary education. On the one hand, the interaction with complexes techniques and materials is needed, and on the other, tools to practice on-demand are required in the current learning. So, this is an excellent opportunity for the creation of data analysis tools for educational purpose that could be considered as a starting point of a broad area of application. This paper presents a pedagogical support tool aimed to facilitate the student approach to the basic knowledge of data mining through the practice of the analysis of online analytical processing (OLAP). It is a prototype that allows the visualisation of the multidimensional cubes generated with all possible combinations of the dimensions of the data set, as well as their storage in databases, the recovery operations for views, and the implementation of an algorithm for the selection of the optimal view set for materialising the set of records resulting from a search of the database, and computing the materialisation costs and total records recovered. The prototype also carries out and present recurrent patterns and association rules while considering factors such as support variables and reliability. All of this is steps are done explicitly to aid the students to comprehend the generation process of data cubes in the data mining discipline.

En el presente artículo se describe una estrategia didáctica que contempla la realidad del estudiante para trabajar el tema de modelado de datos, el cual forma parte de la materia Base de Datos que se imparte en el Centro de Estudios Científicos y Tecnológicos (CECyT) 9, perteneciente al Instituto Politécnico Nacional (IPN). En el grupo experimental se aplicó una estrategia didáctica basada en la experimentación y la practicidad de la teoría constructivista; en el grupo de control se trabajó el tema de forma tradicional. Como parte de los instrumentos metodológicos, se empleó la observación y el cuestionario. La primera se llevó a cabo antes de trabajar con el tema y el cuestionario fue utilizado para evaluar la propuesta. Se analizaron los resultados y se observó que el grupo experimental obtuvo mejores resultados que el grupo control. Se concluyó que el uso de la estrategia didáctica trabajada con el grupo de estudio permitió que los estudiantes tuvieran un mejor desempeño en el tema de modelado de datos.

No abstract

The widespread availability of new computational methods and tools for data analysis represents a great challenge for new students who need to now the basics. It is difficult the selection of the most appropriate strategy and the collection of methods in data mining it's a good example. Some of these methods require guidelines that may help practitioners in the appropriate selection of data mining tools. In the present paper it is showed the proposal of a tool which shows visually the implementation of an algorithm for the selection of the optimal set of views to materialize from a multidimensional cube, being the main parameter the materialization cost of those views. The tool allows defining operations with cubes on different dimensions from a list of business questions that can be performance on them, all this in order to ease students the learning and understanding of data cube generation in data mining discipline.