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September 03, 2009
September 09, 2009
Fordham and Community Research Partners’ student mobility project, released last week, measures the frequency and describes the pattern of student movement in Ohio's schools. The mobility data, while dense, have practical and strategic uses for school-level and district-level practitioners.
Here’s one possible use.
Our research provides educators with information about student mobility networks. This information can help superintendents, principals, and teachers know which schools they are most connected to, by way of student moves.
At a school building level, network data can help educators identify which schools they need to work closely with—perhaps aligning curricular or instructional approaches or making sure their textbooks are the same. At a district-level, network data can help administrators plan facilities or personnel. For example, administrators may find highly-connected schools easier to consolidate, if facility costs are a concern. Similarly, to save on personnel costs, districts could share staff across highly-connected schools. Rather than having a school counselor for each school building, a single counselor may just as effectively serve multiple but highly-connected schools.
To illustrate what a student mobility network looks like (see, D. Kerbow, 1996), I use Bond Hill Elementary School as an example—for no reason other than for illustration. Bond Hill, enrollment 400, is part of Cincinnati Public Schools, 91 percent economically disadvantaged, and nearly 100 percent minority. The school received a C rating (Continuous Improvement) in 2010-11 and in 2011-12.
Bond Hill had an above average one-year churn rate in 2010-11 (32 percent) compared to Cincinnati Public Schools (on average, 16 percent churn). The churn rate measures the amount of student mobility a school experiences during the school year, relative its enrollment size.
The figure below shows the mobility patterns for Bond Hill, the red point on the map. The blue points indicate the public schools that Bond Hill shared 10 or more students with, between October 2009 and May 2011. There were, in total, 17 Cincinnati schools that Bond Hill had more than 10 or more exchanges with: 14 were Cincinnati Public schools and 3 were charter schools.
(For simplicity, I exclude exchanges with district and charter schools outside of Cincinnati, as well as exchanges with Cincinnati schools with whom Bond Hill had less than 10 total exchanges--which are exlcluded in CRP's data set.)
Student mobility patterns for Bond Hill Elementary School (Cincinnati Public Schools), October 2009 to May 2011
Map created through Google Maps. Data can be accessed in spreadsheet format via Community Research Partners. Analysis excludes non-Cincinnati schools and Cincinnati schools that had less than 10 incidents of mobility with Bond Hill. Red lines indicate highly-connected schools; black lines indicate medium-connected schools; no line (but with school marker) indicates low-connected school.
To establish which schools Bond Hill had stronger connection with, I calculate the number of moves into and out of Bond Hill and its exchanging school, as a percentage of all student moves into and out of Bond Hill (again, with the noted exclusions).
For example, there were 19 moves out of Bond Hill into Roselawn. And there were 108 total moves out of Bond Hill. So, 17.6 percent of moves out of Bond Hill were to Roselawn (19/108).
The direction of the arrow indicates whether the movement was out of or into Bond Hill. The lines, or lack thereof, on the map describe whether the magnitude of movement of students was high, medium, or low:
The map shows that the strongest two-way exchange patterns were between:
The map also indicates that Bond Hill receives a large proportion of students (greater than 10 percent) from Alliance Academy charter school and sends a large proportion of its students to Parker. Interestingly for both Alliance Academy and Parker, the relationship wasn’t a strong two-way migratory pattern.
Maps and tables like these can be a very useful data tool for educators (see table with underlying data at the end of this article). Knowing where students are coming from and where they’re going can help create and improve communication channels and facilitate planning across school building lines, and even across traditional district and charter school lines.
An analysis like this one, for example, could alert the Bond Hill Elementary School principal that he or she has to work closely with the Roselawn principal, perhaps coordinating curricula, sharing student records, or simply knowing the culture of each other’s school. Any one of these types of collaborative efforts could help improve our schools, and in so doing, mitigate the negative effects of mobility for students who are on the go.
Bond Hill Elementary School, exchanges to and from other Cincinnati schools, October 2009 to May 2011