The individual stability of student spatial deployment and its implications

In spite of the advances in educational data mining, there have not been many data mining driven efforts directed at the analysis of the student spatial deployment in a computer classroom. In order to uncover the regularities accompanying the student classroom seat choices, we focus on the issue of deployment stability, which denotes the student unwillingness to move from the usual classroom seat. We examine different aspects of the deployment stability and introduce the necessary metric. Furthermore, by using this metric together with various data analysis methods, we demonstrate a low degree of student seat switching in a data set covering computer laboratory seat choices and grades in a university course in computer science during one semester. Student clusters generated according to deployment stability levels are investigated with respect to student gender and course performance, thus leading to the identification of significant patterns, which may be additionally inspected and possibly applied in the classroom.