I worked with On the Ground to try and find out if there are any factors that determine success rates of children in school. They wanted to find out if there was a way to help out these kids, whether it be through tutoring services or helping establish internet access for children without it. The end goal is to get a grant to help fund these children across Idaho, to help increase graduation rates.
For the past 12 weeks, I have been working on compiling data and information on different counties in Idaho. I first started looking at four smaller counties, Butte, Clark, Custer, and Lemhi. These different counties are more rural and have little, to no access to resources. For example, in Lemhi, there were no primary care physicians reported in any of the data for the entirety of the county. After the first month, I decided that it would be a good idea to include a larger county, Ada county. This was to help determine if the factors were truly affecting everyone equally, or if these smaller counties were more of secluded and not so common events. Lastly, I tried to find these correlating factors and present them in a fashion to make them more easily understandable.
There were actually a significant amount of setbacks and difficulties with this project. First and foremost, there were several issues with the data itself. Much of the information was not presented in the same way, nor in the same time frames. For example, with graduation rates the times would go from each year to an average over four year spans. These inconsistencies with the data made it infinitely more difficult to draw conclusive results. A big reason for these inconsistencies was due to the fact that my information was drawn from several different sources. Another setback was that I was dead-set on trying to find out if the information could satisfy a P-Value.
Most of the information that I used was taken from two sources, Indicatorsidaho.org and from general census information provided by the government of Idaho. Through these two sources I would take info and put them into excel files where I would use pivot tables and other like functions to see if the info correlated. Afterward, I created different charts to try and showcase these findings in a much more digestible format.
These have been a very long 12 weeks filled with frustration and learning. Different processes have been tried and have proven to not work, or otherwise. All in all this has been a beneficial undertaking. I cannot in good faith claim that any of my findings were conclusive. With more time and better data, I would like to say that I would be able to find data that would work.
As previously stated, I cannot say that this project was a success based off of the criteria that I was trying to follow. But this was at the very least a successful start in a good direction. If one were to take this information further and delve deeper into it, I would confidently say that we could easily get grant funding for these school kids.