Rock Hill School Board To Talk About School Balance

The Rock Hill School Board retreat will take place Monday, July 13, 2009, from 2 p.m. - 8 p.m. in the District Office Board Room. The purpose of the retreat will be:

• Determine the Board's philosophy for maintaining balance in our schools
• Determine the criteria to be used for balance
• Determine the triggers that would cause the district to reassign students
• Review a reassignment draft policy

Questions To Be Asked

1. Are we still in agreement to maintain balance in our schools?

2. What criteria should we consider as factors to be included on the scenario builder for balance?

• Capacity
• Socioeconomics_(F/RLunch)
• Test scores
• Proximity
• Ethnicity/Race_

3. What triggers would cause district reassignment?

• 15 to 20% over district average F/R Lunch increased over a 2 year period
• % of students performing below basic or basic increasing over time; or remaining +/-15% overtime
• School reached capacity enrollment

How would you answer these questions? How about leaving a response and an explanation for your answers.

The district has used a company out of Raleigh to help with the statistics since 2003. Their brief overview is below:

Analysis of Socio-Economic and Racial Balance Metrics

Rock Hill School District 3

Prepared by OR/Ed. Lab, ITRE, Centennial Campus @ North Carolina State Univesity

July 8, 2009

The Operations Research and Education Laboratory and Rock Hill School District 3 have been jointly involved in school planning since 2003. One of the hallmarks of the initial and subsequent studies is the use of student-derived metrics in the creation of "balanced" school districts. These metrics are used to define optimization constraints and allow for the creation of attendance boundaries that simultaneously minimize student travel distance and meet building capacity and student balance constraints.

The following summary describes some of the dynamics encountered when using these metrics. The primary question is: how do these metrics change over time in a given area? When creating optimal attendance boundary scenarios, OR/Ed. does not attempt to "project" the metric over time, but instead uses the values given by student data at the capture time-point.

Assumptions:

1. The 17 2008-09 elementary districts were used as the geometry for all analysis. Metric values are calculated for students residing within these districts. It is important to note that the metric values in this analysis are based on residence and may not represent the values for any particular school.

2. 2006-07, 2007-08, and 2008-09 geocoded K-12 student databases were provided by RHSD3. Student records included an ethnicity code (Race) and a free/reduced lunch (FRL) eligibility tag. These attributes were aggregated to the elementary district geometry.

3. Metric values are calculated using K-12 student counts. The percentages shown are defined within each elementary district as follows:

• Race - percentage of non-white students

• FRL - percentage of students eligible for free/reduced lunch

Results:

It is helpful to view these results within the context of system-wide means. When an optimal scenario is generated, a metric's system-wide mean is the balance point for that metric. Optimal attendance boundaries are generated with metric values that fall within a defined distance of the system-wide mean.

2007-08 2008-09

Race 48.1% 48.7%

FRL 39.7% 48.3%

Note the fluctuation in the FRL mean, particularly between 2007-08 and 2008-09.

As one might expect from the system-wide means, metric values for individual elementary districts vary significantly over the same time period. The maximum one-year change in Race occurred in the Independence district between 2006-07 and 2007-08. The maximum one-year change in FRL occurred in the Northside district between 2007-08 and 2008-09.

2006-07 2007-08

Race(Independence) 47.0% 40.2%

2007-08 2008-09

FRL (Northside) 46.3% 65.2%

OR/ED case study of Rock Hill