Academic Performance Analysis Supported by a Web-Based Visual Analytics Tool

Understanding the academic performance of students in colleges is an essential topic in Education research field. Educators, program coordinators and professors are interested in understanding how students are learning specific topics, how specific topics may influence the learning of other topics, how students' grades/attendances in each course may represent important indicators to measure their performance, among other tasks. In this paper, we present a visual analytic tool that combines data visualization and machine learning techniques to perform some visual analysis of students' data from program courses. Using this tool, we visually analyzed the students' performance in some Computer Science program courses, and demonstrated that the results of such analysis will help the education experts to understand deficiencies on course structures.