The pandemic caused numerous disruptions and alterations to education in the United States. In this presentation we introduce ourselves and provide attendees with an overview of the training session followed by an introduction to analytic approaches that will be investigated during the training session.
Before getting started on analyzing data, we need to install the software we will use to analyze our data. We use the R Software Environment together with its robust eco-system of packages for all of our data prepreparation analysis, and reporting.
Investigating pandemic related academic impact on student learning. During the third and fourth hours, participants will be introduced to several ways to investigate the academic impact students encountered due to the pandemic. Including: Skip year baseline referenced growth analyses. Status based methods of looking at impact based upon propensity score matching Andrew Ho’s Fair Trend method as used to look at academic impact. Using a toy data set that mimic 2020 test cancellations, students will learn to calculate academic impact and use those results to investigate impact by demographic subgroups.
Investigating pandemic related academic impact on student learning. During the third and fourth hours, participants will be introduced to several ways to investigate the academic impact students encountered due to the pandemic. Including: Skip year baseline referenced growth analyses. Status based methods of looking at impact based upon propensity score matching Andrew Ho’s Fair Trend method as used to look at academic impact. Using a toy data set that mimic 2020 test cancellations, students will learn to calculate academic impact and use those results to investigate impact by demographic subgroups.