EXPLORATORY VISUALIZATION ON DATA OF LEARNING PERFORMANCE IN AN ADAPTABLE SOFTWARE ENVIRONMENT

Abstract

Visualization research deals with the use of
graphical models to represent data, coupled with interaction
operations that support an active user to explore data
representations. The vast quantity of information in learning
progress database increases the difficulty of analysis of the
student’s performance. Educational indicators such as
grade, approval and fail index cannot be considered as
unique performance indicators; however, these indicators
along with student’s learning styles can reveal educational
progress. The visualization area combined with statistical
analysis has been considered an alternative to the
exploration of data in the process of knowledge discovery.
This paper presents a methodology to identify the patterns
that demonstrate the learning performance through the
development of a visualization tool in an adaptable software
environment. Using the developed methodology it is possible
to combine students and courses styles to detect possible
problems on the courses outline and suggest changes in
some methodologies and teaching strategies.

Key-words - Engineering Education, Information
Visualization, Learning Performance, Learning Styles.