Title :
Mining Academic Data Using Visual Patterns
Author :
Martinez Luna, Gilberto Lorenzo ; Olivares-Ceja, Jesus-Manuel ; Ortega Villanueva, Eric ; Guzman Arenas, Adolfo
Author_Institution :
Data Sci. & Software Technol. Lab., IPN, Mexico City, Mexico
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.
Keywords :
data analysis; data mining; data structures; data visualisation; educational administrative data processing; software tools; Mexican educative system; academic data mining; academic decisions; data analysis; data pattern discovery; data structures; knowledge acquisition; knowledge skills; master concepts; software tool; student mobility pattern discovery; student trajectories; tool management; visual pattern detection; visualization tools; Cities and towns; Data visualization; Education; Proposals; Software; Trajectory; Visualization; data analysis; student trajectory and mobility; visual patterns;
Conference_Titel :
Artificial Intelligence (MICAI), 2014 13th Mexican International Conference on
Print_ISBN :
978-1-4673-7010-3
DOI :
10.1109/MICAI.2014.20
