Category: xSpr14 Assignments

MoveUP! Writing about Data

Posted on Author Sarah Keane

Demographics can play a large role in literacy, and what MoveUP! wants to try to figure out is what types of demographics are making an effect on their students. If certain factors make a large enough impact, it could potentially be something that MoveUP! would want to take into consideration when they advertise their adult literacy programs.

This graph shows the median household income per each census tract in Hartford County. It is evident that the western part of Hartford county has a higher median income, whereas the actual city of Hartford seems to have the lowest. When you click on the tracts, though, you are able to see that many more people are attending adult literacy programs in the tracts that are in the city of Hartford in comparison to those that are in towns that have higher median incomes such as West Hartford.

Building upon the first map of income, this map shows the distribution of the poverty status for individuals 18-64 years of age within the various census tracts of Hartford County. This map essentially shows the inverse of what the previous map showed: it accentuates the lowest income areas, which is, again, primarily the city of Hartford.

Another demographic that isn’t related to income that is important to look at, particularly in relation to literacy is employment. There is typically a strong correlation between employability and literacy skills, therefore it is important to look at what kinds of match ups there are in terms of unemployment. What is essential to note about what is considered to be “unemployed” in this particular map and data set is that those individuals are part of the labor force. There are also individuals included in the data set that are under the category of “not in labor force”. It is interesting to note, however, that the highest rate of unemployment isn’t necessarily in the same tracts as the lowest income.

Assignment 9

Posted on Author Marissa Block

As a result of school choice programs, Hartford students are not limited to simply attending their neighborhood school. Students can apply to attend any district school within the HPS system, or participate in interdistrict choice, which includes magnets, charters, or district schools in the Hartford metropolitan region. Since Achieve Hartford! focuses on education in the HPS system, the former choice program will be the most important.

In conjunction with Achieve Hartford’s report detailing the results of the Connecticut Mastery Test (CMT), the following visualizations enable viewers to grasp the most salient results by amalgamating the series of achievement scores into one place. Though most of the schools are HPS district schools, there are a few magnets and one charter (Achievement First), which are all located within the boundaries of Hartford. It is clear that achievement, based on the percentage of students who met proficiency (3 and above) on the CMT has steadily increased since 2007, though in the last two years (2012 and 2013) it has leveled off. Now, if a Hartford parent would like to send his or her child to a different school within Hartford, this chart will facilitate making an informed decision. The parent can choose any number of schools to compare with each other, or with the Hartford average. As seen in the chart, the magnet schools tend to perform above the Hartford average. Magnets typically have specialized curricula, and they are designed to draw students from across districts. High achievement may stem from the peer effect, so lower-income Hartford students are benefiting from learning side-by-side with higher-income suburban students.

The performance of district schools is more difficult to generalize and there is no clear pattern. On the whole, most district schools do not seem to exhibit a steady increase in scores, but rather fluctuate from year to year.

If parents are unfamiliar with the many school options within Hartford, a map is more relevant to helping them make an informed decision. This map incorporates the achievement data from the graph, but displays it spatially. Thus, parents can easily see the distribution of schools based on achievement throughout Hartford, and type in their address to identify schools nearby. When the data are displayed spatially, it seems that Zone 1 (top right) has the best school options, several of which are magnets.

A8: Lying with Maps

Posted on Author Shaina Lo

The first Google Fusion table here shows three different SmartChoices types of schools in Connecticut. To learn more about the description of SmartChoices schools, please click here. SmartChoices includes public schools in the city of Hartford as well as 19 other suburban towns. It is important to note that it does not include other types of schools, such as private.

Below I have divided my schools into three different SmartChoices: 1=interdistrict, 2=district, and 3=more PreK centers. By combining the data with the city KML layer, the polygon map shows the most prevalent types of schools in each city area with a shade of blue.

The second map I formed with the same data and boundary lines. However, the map shows points of the three types of schools present, instead of polygon layers. It is interesting to view these maps together because by looking at the one below, it is clear that especially within the Hartford city area, one may get easily confused by the amounts of dots present. They can overwhelm an audience unfamiliar with this type of data. The map above only shows one color per city and identifies that city with a type color. One may think that that particular city only contains mainly those types of schools. However, the other types are available as well.

How to Lie with Maps

Posted on Author Marissa Block

The first map below shows the four school zones of the Hartford school district, which are shaded based on the average percentage of CMT proficiency of the schools in the that zone in 2013. The averages range from 50.4 to 74.09, so in the first map the red shaded areas are 50.4-62.23 and the green shaded areas are 62.24-74.09. This splits the zones into either good or bad, which is obvious in the map. Additionally, the use of red also further highlights the negative performance of the school zones. In shading an entire school zone in red, such as Zone 2 (top right), viewers might react negatively towards all the schools in that zone, even though one point (Capital Prep) is green, meaning the percentage at proficient is 70% and above.

The second map shows the exact same data, but rather than dividing school zones into good versus bad, zones are shaded as a gradient, so identifying the worse performing school zones does not quite jump out at the viewer as much as the last map. Again, the range for the gradient is 50.4-74.09, and as the shading gets darker the percentage at proficient increases. In this map, the viewer can determine that Zone 1 (top left) seems to be the darkest shaded, and this is confirmed by the yellow and green points, which are schools with percentage at proficient of 51% and above. In terms of the other zones, it is not quite clear which are better performing. For example, it does not seem that Zone 2 (top right) and Zone 3 (bottom left) are any worse than Zone 4 (bottom right), whereas in the first map, Zone 2 and 3 were shaded red, while Zone 4 was green.