Publication :Visualization of Longitudinal Student Data
Publisher :Physical Review Special Topics, Physics Education Research
Abstract: We use visualization to find patterns in educational data. We represent student scores from high-stakes exams as flow vectors in fluids, define two types of streamlines and trajectories, and show that differences between streamlines and trajectories are due to regression to the mean. This issue is significant because it determineshow quickly changes in long-term educational patterns can be deduced from score changes in consecutive years.To illustrate our methods, we examine a policy change in Texas that put increased pressure on public school students to pass several exams, and gave them resources to accomplish it. The response to this policy is evident from the changes in trajectories, although previous evaluation had concluded the program was ineffective. We pose the question of whether increased expenditure on education should be expected to correspond to improved student scores, or whether it should correspond to an increased rate of improvement in student scores.