Anonymous wrote:
Anonymous wrote:Chris, great app. Many thanks. Is there a way to use the data to show where the out-of-boundary students attending each school are from? ...
Glad you asked. We worked on a project to answer that question on last year. Find the answer to where student from your school live, or where students from your neighborhood go to school, using this tool:
http://edu.codefordc.org
Yes, I love that tool. But it's exactly the one that got me thinking about the in-bounds vs out-of-bounds question. That tool shows which neighborhood clusters send students to each school, but does not differentiate on in-bounds vs out-of-bounds. For example, with Wilson high school (
http://edu.codefordc.org/#!/school/463), I can see that 168 students come from the Brightwood/Crestwood/Petworth neighborhood cluster. But since the Zone Attendance boundary line for Wilson runs right through the middle of that neighborhood, I cannot tell what percentage of the 168 students are in-bounds for Wilson. Maybe it's 100%, and all 168 live in Crestwood ... or maybe it's only 5%, and the rest live in other out-of-boundary neighborhoods. The same "split cluster" problem applies to 177 students from the cluster south of that (Columbia Heights, Mt Pleasant, Pleasant Plains, Park View). Focusing just on those two clusters as an example, if we discovered that two-thirds of the Wilson students from those clusters (227 students) are out-of-boundary for Wilson, that might suggest that those neighborhoods are thriving and need more investment in their neighborhood high school (Roosevelt).
Any ideas on this score? Does the Code For DC data set allow this additional layer of granularity?