Sources

Our research studies the relationship between the COVID-19 pandemic and K-12 education. Our team utilized different data sets from the Stanford Education Data Archive, or SEDA Data Downloads, such as seda_cov_state_pool_5.0; SEDA holds publicly available data files, technical documentation, and codebooks. In addition to the data accessible on this site, we used a combination of trustworthy, peer-edited books, scholarly journal articles, and official organization websites for background information, providing a perspective and placing the data set into a place and time. Our 15 articles that we reviewed in our annotated bibliography elucidated the already known effects of the COVID-19 pandemic on students in all grades, whether it be K-12 or higher education. They also directed us toward gaps in research.

Using the information available from our literature as well as the data provided on SEDA, we developed two research questions, as we commonly noticed the consistent trend of those who have access to fewer resources performing even worse than before due to remote learning and increased risk of disease (Chung and Kim 2022). Moreover, states and the effects of individual state policies on education were hardly analyzed by any journal article. Using an approach where we consider socioeconomic, political, and geographic factors—even if it’s only in the United States—is necessary for the growth of our nation and the welfare of our future, as moving forward to improve the education of students post-pandemic is integral to the success of our future.

Processing

Many of our SEDA data sets were separated into pre-COVID results (up to 2019 data) and post-COVID results (2022 and 2023 data) with no data points during the years at the height of the pandemic (2020 and 2021). This data consisted of many different categories, though we mainly focused on racial index, socioeconomic status [SES composite], standard mean achievement, and standard error of achievement. While the information from the Stanford Education Data Archive was mostly clean, some cleaning and manipulations of the data were necessary because of the strictly specific and different categories that were provided between each of the data sets.

The map created was important for showing the geographical context of our data: how different states affect test-based achievement. We used Tableau to graph our locations. Tableau was also used for our data visualizations, with each visualization contributing to answering our research question. Data visualizations were integral for comparing states and noticing patterns between categories. The benefit of Tableau was its interactivity and its varying graphs that can include many different variables. Google Sheets was also used for one of our bar graphs displaying average poverty rate.

Presentation

We used Humspace portal, provided by the University of California, Los Angeles’s Digital Humanities Department, to host this WordPress. Editing with Kubio, we created an easily navigable user-friendly website. We used the font Mullish in varying sizes and weights for all of our copy, with consistent styling for headlines and copy. There is one main color in our palette: blue. We have one accent color, which is yellow. Separating out information into expected formatting makes it easier to digest. Our charts and visualizations are embedded with HTML code to enhance the user experience.

To ensure accessibility, every image and visualization has a short blurb describing the graphic. Our website has high-contrast colors.