Analyzing Kindergarten Readiness
Using AI to analyze anonymous WaKIDS data to share with local reporter on Kindergarten readiness.
Overview
We were trying to determine if participation in Transitional Kindergarten (TK) made a difference on students' kindergarten readiness as measured on the WaKIDS state assessment. This was complicated by the fact that admission to a TK program is selected based on low levels of kindergarten readiness, so our comparison populations are different.
Project Description
Prompt 1:
We will be using this file for a data analysis project. Please review the file structure and provide a short summary.
Prompt 2:
Let's start with a table showing the mean, median, and standard deviation in scale score each domain for the Was TK=YES group compared to the Was TK=NO group.
Prompt 3:
What percent of the variation in students' scale scores in each domain can be explained by their Was TK status?
Prompt 4:
Try making a stacked bar chart for a domain that shows the percentage of students at each level for the two "Was TK" groups. Use the colors of the level on the chart, order the levels from the lowest on the bottom to the highest on the top, and include data labels. Let's begin with the SocialEmotional domain.
Prompt 5:
That's great. Please do the same thing for each of the other five domains.
Other Content Provided
An anonymized set of WaKIDS data.
Any Other Info
The visualizations generated helped explain the situation more effectively with local media. Ultimately, students in TK were assessed as slightly more ready than their peers in the domains targeted by the program, which was noteworthy given the initial set of observations determining their eligibility.