Data Visualization to Assess Interventions to Improve STEM Learning in K-12
Abstract
Louisiana tests about 300,000 thousand students annually and as in many states, statistical modeling of this data is being proposed as a means of assessing teacher performance. The data, complete with teacher identifiers, is available to researchers. In this presentation, I will demonstrate some visualization formats and methods that our project has developed to guide the use of this data. Users of all levels of sophistication can explore the data meaningfully, generate hypotheses and examine model assumptions. Interactive features enable viewers to select level of analysis (state, district, school, student) and make comparisons within and across levels. We show applications to real data to demonstrate usefulness, but it is not our purpose present any performance judgments at this time.View All Paper Session Presentations from the 2011 MSP LNC Conference