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Autonomous cycle of data analysis applied in the academic planning of educational institutions

Abstract:

This work describes the use of data analytics to plan teaching courses in the academic periods of an educational institution. Basically, an academic course planning system is proposed based on the concept of “autonomous cycles of data analysis tasks”, which analyze the historical behavior of student demands and courses, with the aim of planning the following year academic, considering the restrictions on the capacities of the courses and available professors. For the development of the system, the MIDANO methodology was used, which establishes three steps to develop autonomous cycles of data analysis tasks: specification of their objectives and tasks; data preparation; and development, integration and testing of tasks. The system was instantiated in a University, for which several academic data analysis tasks were developed using machine learning techniques, obtaining promising results.