Washington Kinder Readiness - WaKids

Background:

WaKids is an assessment that measures the readiness of children entering into kindergarten. WaKids uses 6-8 different measures, depending on schools kids are in, to help inform different level decisions about education policy and classroom decisions about individual children. The measures/domains are cognitive, language, literacy, math, physical, social-emotional, Spanish language, and Spanish literacy (only some districts add the Spanish language and Spanish literacy domains).

In this project myself and my colleague Rachel Searles were put in the shoes of an analyst at a school and tasked with building a dashboard that was able to show the readiness of different schools in Washington. Since we both have backgrounds in teaching this was a logical choice of datasets and it demonstrates skills with SQL and Tableau.

Ask:

One of the dashboards created shows the overall standing of all schools in Washington that use WaKids, and has the ability to show a more focused version of the readiness by each school. The other shows the top 10 and bottom 10 school districts and which domains they excel of fall short in.

The questions we aimed to answer through these visualizations were:

• Which domain are Kinder's typically most ready for?
• What are the top performing districts?
• What are the bottom performing districts?

Prepare/Process:

The data was downloaded from data.gov, here is the link. The dataset contains many columns including, OrganizationLevel, Measure (domains), District Name, School Name, Student Groups, and Percent. For our analysis, we focused on Organization Level, District name, School name, Measure, and Percent columns.

Once the data was pulled it was immediately brought into SQL to clean it. Luckily not much cleaning was necessary. The IDs of the schools were checked to make sure they all had only numbers and to see if the length was correct for school, ESD organization, and district ID numbers. The data also had suppressed data so the NULLS in the percent column were removed as that was assumed to be part of the suppression, and that and aggregated data would be skewed because of it.

Next, after looking through all the data it was concluded that using one type of measure would show the actual readiness of the kids. That measure was any that ended in "ReadinessFlag" so SQL queries were written to show that.

Analyze:

Below shows the final query that was used to get the .csv file that was used in for the visualizations in tableau.

SELECT OrganizationLevel,
  DistrictName,
  Measure, 
  SchoolName, 
  ROUND([Percent], 2)* 100 AS Percentage
FROM report_card_wa.dbo.[Report_Card_WaKids_2021-22]
WHERE Measure LIKE '%ReadinessFlag'
  AND StudentGroup ='All Students'
  AND MeasureValue = 'Y'
ORDER BY OrganizationLevel, DistrictName, SchoolName;

By using this query we were able to focus on just a few columns because by looking at these measures, users can easily identify kinder readiness on multiple levels. We only wanted to show the percentage (as a percent instead of the decimals that were shown) of the students that were ready in all demographics or StudentGroups.

The first visualization is a tree map displaying Kinder Readiness by domain. This map represents all Washington state school districts. Physical readiness being the highest percentage, and math being the lowest. Spanish language and literacy are also at the lowest, but not every school has those domains in them to test. There is also a way that you can look at the readiness of any school across Washington.

The next viz was to show the top 10 and bottom 10 school districts in Washington. found it interesting that all districts within the top 10 only had 2 or 3 schools, and most districts in the bottom 10 also had 2 or 3 schools, with a few outliers (Quincy, and Yakima).

Share/Act:

The questions we aimed to answer through these visualizations were:

• Which domain are Kinder's typically most ready for?
• What are the top performing districts?
• What are the bottom performing districts?

Which, after the analysis we can answer each one using our visualizations.

• Physical is the domain Kinder is most ready for.
• Adna, Almira, Cape Flattery, Dayton, Impact, Naselle-Grays River Valley, Oaksdale, Pullman, Republic, and Waitsburg and the top performing districts.
• Brewster, Bridgport, Colton, Quincy, Reardan-Edwall, Summit Valley, Wapato, Wilbur, Yakima, and Zillah are bottom performing districts.

For next steps, I would want to look further at what Top districts are doing well to support their students, and also look at what factors contribute to lack of Kinder readiness in the bottom performing schools.

Thank you for reading and a big thank you to Rachel Searles who was a joy to work with during the project!