10-02-2016 11:09 AM - last edited 12-05-2016 10:51 AM
My oldest sister Laurie is a superintendent for an Ohio school district and she sent me data about all of schools and school districts in Ohio. Ohio uses a system of 16 different measures of school performance. To understand more about the different metrics used in Ohio, go here. The data presented in this report came from my sister Laurie, which originally received the data from the State of Ohio. Additional information was added to this, such as the revenue spent per pupil, which came from the Ohio Department of Education's website here.
The data as provided was challenging to work with in a number of ways. Achieving the desired capabilities required merging various tables of data together, specifically for the District Comparison report to function properly. Additionally, the raw data provided for the rankings of the measures were in a format of A-F grading as well as a number of "NR" designations, meaning that certain schools and districts were not measured on that particular category. In order to create meaningful insights into the data, these letter grades were translated to numeric values 0-5 (A=5, B=4, C=3, D=2, F=1, NR=0). This allowed trends and calculations to happen on these measures of school performance. However, care was necessary to exclude NR (0) values from the calculation of averages, etc. This conversion also allowed the creation of an overall measure that averaged the 16 measures into a single value. Once these numeric translations and calculations were made, additional work was required in order to translate these calculated values back to the A-F ranking system used by the State of Ohio.
Page 1, Ohio Overall, presents a snap shot of all school performance in the State of Ohio with the ability to filter using the county map in the lower left corner. The coloring of the county map is based upon the calculated measure of overall school performance with teal being better and pink being worse. This page also displays overall information on the amount of money spent per pupil, the number of districts, schools (buildings), students, % poverty and % minority.
Page 2, District Comparison, is a tour de force in the ability to edit visual interactions. Color coding has been added to provide the user a visual cue as to what slicers affect which visuals. This report was designed to allow educators to find districts that are similar in classification and poverty level as their own and is specifically designed to identify outliers that significantly overperform based upon their classification. By identifying overperformers, it is hoped that other educators can learn what these overperformers are doing well that they are not and thereby facilitate learnings by school administrators that will ultimately benefit students in lower performing districts. The way that overperforming districts are identified is through simple calculations involving standard deviation. By translating the letter grades to numeric grades and creating the overall measure of school performance, it is possible to calculate the average (mean) of that value as well as its standard deviation. By subtracing this mean from a school district's overall score and then deviding by the standard deviation, a number is calculated that is that school district's number of standard deviations above or below the mean. School districts with higher, positive numbers are overperforming districts and those with lower, negative numbers are underperforming.
Page 3, District Buildings, provides administrators with a snap shot of individual district and school performance similar to page
Page 4, Trends and Correlations, provides interesting insights into the relationship of overall performance with respect to things like % poverty, % minority, revenue per pupil and enrollment. Some specific insights include:
Finally, page 5, County Map, provides a larger view of overall school performance by county with the ability to select individual counties and see vital statistics.
Proud to be a Datanaut!
Ah, sadly, that is slight of hand, it is not dynamic, it is statically set in the formatting (paintbrush) options for that visual. If you slice/filter to a school district that gets an "A" in that category, it will still be red. Sadly, no dynamic ability to set the gauge color based on a measure value. At least I am not aware of that capability with the default visualizations, and I prefer to not use custom visuals if I can at all help it.
Proud to be a Datanaut!
Great Work! I wish there were more examples like this, to encourage educators to use these type of tools to help us use data to measure and improve our performance.
Good day. It's really interesting and truthful information, i'm glad to read it. Especially i like this part: "The data as provided was challenging to work with in a number of ways. Achieving the desired capabilities required merging various tables of data together, specifically for the District Comparison report to function properly. Additionally, the raw data provided for the rankings of the measures were in a format of A-F grading as well as a number of "NR" designations, meaning that certain schools and districts were not measured on that particular category". It would be great if you share this information at https://pro-papers.com/proofreading-and-editing-services. I would be very grateful
Ohio is one of the most important states in our country. We should do everything that we can to get them essay help at https://paperleaf.ca/. I hope that kids from there will have the brightest future possible. They are our future and we should help them. Just like what LeBron is doing right now. We need more scholarships so our kids could have an ability to go to college one day.
I hope that kids will have the brightest future possible. They are our future and we should not help them. Just like what LeBron is doing right now. We couldn’t be able to go to college one day. Now in our schools we introduce additional metrics of estimation, cost metrics that are intended, of course, not for students. I do not know what benefit this can bring if no real action is taken on the basis of these metrics.
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