Monthly Archives: November 2014
Our colleague Linda Zellmer, government and data services librarian at Western Illinois University Libraries, has once again created a series of maps indicating where foods traditionally eaten on Thanksgiving Day in the USA are grown, raised, and produced. The maps and this poster can be used at any time during the academic year and from primary school to university level to examine the geography behind a familiar phenomenon.
This year she also created a series of ArcGIS Online maps that can be used to explore the spatial relationships and data interactively. The foods that can be examined include turkey, cranberries, squash, green beans, and many more. Using ArcGIS Online’s visualization, classification, filtering, and analysis functions, students can investigate states meeting specific criteria, such as those that grow many green beans but not so many carrots. They can think about the forces in physical and cultural geography that might affect the raising and processing of these products.
To dig deeper into what GIS is and how it can be used, consider having your students read this newspaper article about the project as well.
On a related note, see the Esri story map featuring where 4 specific Thanksgiving foods are grown as a set of dot density maps.
Esri has launched a “Share Your View!” crowd-sourcing initiative. You are invited to participate! The theme, “Share Your View!”, focuses on a seemingly local experience – the view from your window (or door). However, by placing these locations on the map, the application puts things in a broader perspective — presenting a tapestry of views from all over the world. Visit the live web map to submit your view and see entries that others have submitted.
What can you do with “Share Your View”? You can use it as a starting point for discussing geotechnologies, crowdsourcing, citizen science, story mapping, and location privacy. By examining the submitted photographs, you can compare vegetation, building types, land use, language, weather, climate, presence or absence of water, population density, and other aspects of the physical and cultural geography from a wide variety of locations around the world that your students observe in this map and photographs.
In what other ways can you use this resource for teaching and learning?
Does the size of a school district matter? Specifically, does the size of the school district (as measured by the Average Daily Attendance – ADA) affect school academic performance? In California, elementary serving school districts range from an ADA of just over 5 (Panoche Elementary School District – located in San Benito County about 13 miles south of Hollister) to well over half a million (Los Angeles Unified School District).
Because municipalities arguably contribute resources to educational achievement, accounting for the location of schools in municipalities is essential in assessing school performance. However, school district and municipal boundaries do not often coincide in California, resulting in a “crazy quilt” of overlapping jurisdiction lines. ArcGIS was crucial in constructing the dataset used in this study because schools needed to be geocoded and then located both within their school district and within their municipality.
Regression analysis – a statistical technique that allows one to test various hypothesized causal relationships – was used to determine the strength and significance of the ADA of the school district in explaining the API of the school. The analysis controlled for a large number of other variables related to school outcomes, like parents’ educational attainment, demographic variables, district spending per ADA, population density, enrollment growth in the school, and enrollment growth in the district. The study also accounted for whether the school was a charter school. As suggested by previous literature, many of these variables accounted for a significant part of school API.
Looking at the effect that ADA has on API, however, provided some new insight. To capture potential scale effects, two terms associated with ADA were used in the regression analysis – ADA and ADA squared; the effect of ADA was modeled as if it were a quadratic equation – a form that allows the effect of the impact to change direction – for example, to first rise and then fall. The estimated coefficients of the quadratic equation give an “ADA Impact Factor” as represented in Fig. 1.
The estimated ADA Impact Factor suggests that an ADA of approximately 71,200 is the optimal school district size. The regression allows one to estimate the “API bump” that a school district imparts to its schools by virtue of being closer to the right size. One hundred of the eight hundred elementary serving districts had an ADA Impact Factor greater than or equal to 15.
The “Goldilocks Zone” of school district size is not just a statistical curiosity. It correlates with significant fiscal and governance features. School districts with a high ADA Impact Factor are predominantly unified school districts. School districts with a low ADA Impact Factor are predominantly elementary school districts. The average spending per ADA of high ADA Impact Factor districts was more than 6% lower than the average spending per ADA of low ADA Impact Factor districts. This suggests that the unified school district may have advantages in both fiscal terms and in terms of school quality. Indeed, it suggests that there are economies of scope – efficiencies associated with producing many kinds of education as unified school districts do.
- J. M. Pogodzinski, Guest Contributor
Department of Economics
San Jose State University
1. Elementary serving districts are either elementary school districts or unified school districts.
2. First, some adjustments were made to the data. I excluded the Los Angeles Unified School District from the statewide sample because LA was an extreme outlier in ADA, and its inclusion materially affected the results. Second, I excluded a few very small districts because their expenditures per ADA were more than three standard deviations above the mean. These appear to be very small districts that have high fixed costs, so their spending patterns are abnormal.
Recently, while at the Applied Geography Conference in Atlanta, I decided to test the spatial accuracy of my smartphone’s GPS in a challenging environment–a rooftop running track. Although on a roof, the track was surrounded by buildings far taller, and in downtown Atlanta, to boot, a location with many other buildings impeding signals from GPS, wi-fi hotspots, and cell phone towers. Another challenge was that each lap on the track was only 0.10 miles, and therefore, I would not travel very far across the Earth’s surface.
After an hour of walking, and collecting the track on my smartphone with a fitness app (Runkeeper), I uploaded my track as a GPX file and created a web map of it in ArcGIS Online. As I expected, the track’s position was compromised by the tall buildings–I only had a view of about half the sky during my time on the roof. As you can measure for yourself on the map linked above, the track lines formed a band about 15 meters wide, but interestingly, were more spatially precise along the eastern side of the track, where the signal was better, as you can see in my video that I recorded at the same time.
Also, as I have encountered numerous times in the past, a line about 100 meters long stretches to the north. Rest assured that I did not leap off the building, but rather, the first point that the GPS app laid down as I opened the doors to walk outside was about a block away. Then, as I remained outside, the points became more accurate. When you collect data with students, the more time you have on the point you are collecting, typically the more accurate that point is spatially.
Another interesting aspect of this study is that if the basemap is changed to satellite imagery, it appears that the track overlaps the tall building to the west. Try it! However, a closer investigation reveals that this is a result of the orthocorrection that was done to the imagery; the buildings do not appear from “straight overhead”, but rather, “fall away” to the east. Turn this into another teachable moment: Images, like maps, are not perfect. However, both are very useful and we can learn to manage error and imperfection through critical thinking and through the use of geotechnologies.
To dig deeper into issues of GPS track accuracy, see my related post on errors and teachable moments in collecting data, and on comparing the accuracy of GPS receivers and smartphones and mapping field collected data in ArcGIS Online here and here.
Despite these challenges, overall, I was quite pleased with my track’s spatial accuracy, even more so considering that I had the phone in my pocket most of the time I was walking.
We receive many inquiries about how GIS and spatial thinking can be used with primary (elementary) aged students. In honor of GIS Day and Geography Awareness Week being upon us, I thought it would be the perfect time to highlight a few ideas and resources that you could use to develop and apply spatial thinking skills.
We have always advocated (1) that the most appropriate tool be used for the objective at hand; and (2) spatial thinking skills are developed through a variety of means, methods, settings, and media. These include the appropriate use of ArcGIS Online, for example, to examine world biomes, the locations and growth of cities, land use and demography of their local community, population change by country, the frequency and distribution of earthquakes and other natural hazards, the shape and size of watersheds, and so on. A selective use of the ArcGIS Online presentation mode, for example, to foster students as “map detectives” can be used effectively, as I have done with this “Name That Place” presentation and with another entitled “Weird Earth.”
However, fostering spatial thinking at young ages in particular needs to use all five senses, and needs to include outdoor experiences. Using globes, mapping trees on campus, watching videos about scale coupled with measuring objects around school and the perimeter of the school building are just a few activities that can be effectively used. I am a firm believer in fostering spatial thinking using tactile-based activities such as this lesson I developed that asks students to create a thematic map on a translucent sheet of paper based on ArcGIS Online imagery, described here and in video form here. Another tried-and-true lesson is to ask students to draw a map of their classroom, and, depending on the students’ age, incorporating map scale. Another simple but powerful activity I have used during hundreds of school visits over the past 20 years is to ask the students to draw an outline of the school building, as it would look from above, orienting it according to cardinal directions, and labeling the different sections of the building and school grounds. Then, I ask students to check their maps against the imagery in ArcGIS Online and discuss differences and similarities and the reasons for them.
Our colleagues in education and industry continue to create a rich body of resources. For example, Barbaree Duke created a series of language-arts based activities, some of which can be used in primary school. The 20 Minute GIS for Young Explorers curriculum from GISetc spans multiple disciplines and though rich in content, each can truly be taught in 20 minutes.
Finally, exploring history, geography, art, science, mathematics, and other disciplines can be easily done through studying the gallery of storymaps or … having the students make their own storymap. Other ideas exist on the GIS Day website. I’ve run out of space. What are your ideas for fostering spatial thinking at young ages?