Mining Academic Data Using Visual Patterns

Abstract

The Mexican Educative System collects thousands of records each year, related with student performance to support academic decisions. In this paper the data analysis, structures and different visual alternatives are used to discover student trajectories and mobility patterns. A model and a software tool have been developed and complemented with available visualization tools to enable visual pattern detection. The development has been tested with samples of data from several Mexican states and the results encourage the proposal to be used as an alternative to discover data patterns following a visual approach. The implementation of the proposal facilitates timely detection of student progress and bottlenecks for the teacher to provide students with supplementary materials and guides focused towards knowledge acquisition, skills and master concepts, techniques, tools management or production and development of innovative ideas.