race and magnet school choice: a mixed-methods neighborhood study in urban connecticut jesse wanzer,...

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Race and Magnet School Choice: A Mixed-Methods Neighborhood Study in Urban Connecticut Jesse Wanzer, Heather Moore, and Jack Dougherty Cities, Suburbs, and Schools Research Project at Trinity College, Hartford CT http://www.trincoll.edu/depts/educ/css

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Race and Magnet School Choice: A Mixed-Methods Neighborhood

Study in Urban Connecticut

Jesse Wanzer, Heather Moore, and Jack DoughertyCities, Suburbs, and Schools Research Project

at Trinity College, Hartford CThttp://www.trincoll.edu/depts/educ/css

What questions can be asked with these types of data?

Part 1: Quantitative Research Questions

1) School quality: What is the relationship between magnet application rates and standardized test scores, for both the neighborhood schools and the magnet schools?

2) Geography: How do magnet schools vary in their level of

“magnetism,” meaning the average distance they attract applicants?

3) Neighborhood race: How do magnet applicant rates vary across neighborhoods, and are they statistically representative of the racial demographics of each area?

Part 2: Qualitative Research Questions

4) Neighborhood rate: How do Hartford parental rationales on magnet school choice vary in neighborhoods with high versus low magnet applicant rates?

5) Parental race: How Hartford parental rationales on magnet

school choice vary by race?

Pooled data from over

4,000 applications

to 6 HPS elementary magnets in Spring 2007

lottery

Includes student race,

address, magnet

preferences

Part 1: Methodology -- Data

Geographic Information System software (like ArcGIS) allows one to conduct spatial analysis of demographic patterns in magnet school applications or enrollments

Part 1: Methodology -- GIS

Link data to street map

Part 1: Methodology -- Geocoding

Geocode street address data as individual points

on map

Part 1: Methodology -- Geocoding

Overlay neighborhood boundary lines(census tracts,

elementary school zones, etc)

Part 1: Methodology -- Geocoding

Use colors to represent data groups

Zone BZone A

Part 1: Methodology -- Geocoding

Part 1: Methodology -- Geocoding

RQ 1) Magnet applicants driven by School Quality? Relation of CMT Scores to Elementary Magnet Schools

R2 = 0.420

200

400

600

800

1000

1200

1400

1600

1800

20.0 30.0 40.0 50.0 60.0 70.0 80.0

Average Percent of 4th Graders Scoring at Proficient Level on CMTs

Total Number of Applications

Modest “Pull” relationship toward

high-scoring magnets

RQ 1) Magnet applicants driven by School Quality? Relation of CMT Scores to Elementary Magnet Schools

R2 = 0.420

200

400

600

800

1000

1200

1400

1600

1800

20.0 30.0 40.0 50.0 60.0 70.0 80.0

Average Percent of 4th Graders Scoring at Proficient Level on CMTs

Total Number of Applications

Modest “Pull” relationship toward

high-scoring magnets

Relation of Magnet Applications and CMT Scores

R2 = 0.1894

0

5

10

15

20

25

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0

Average Percentage of 4th Graders Scoring at Goal Level on CMTs

Applications per School Zone Enrollment

Weak “Push” relationship away from

low-scoring neighborhood schools

Magnet School Average Distance (miles)

Simpson-Waverly 1.9

Mary Hooker 2.8

Noah Webster 2.9

Breakthrough 3.1

Annie Fisher 3.2

Kinsella 3.2

RQ 2) Magnet applicants driven by Geography?

Wide variation across small city suggests that parents are not simply

choosing a magnet based solely on

geographical convenience of location

3) Magnet applicants driven by Neighborhood Race?

Hartford Public Schools: 41% Black (mostly North End) and 52% Hispanic (mostly South End)

3) Magnet applicants driven by Neighborhood Race?

Chi-square analysis comparing expected applicants (based on neighborhood racial composition) to observed

3) Magnet applicants driven by Neighborhood Race?

In about half of the city’s neighborhoods, Black students statistically more likely to apply if they were a racial minority (relative to Hispanics); similarly, Hispanics less likely to apply when they were the racial majority (relative to Blacks)

Part 2: Qualitative Research Questions

4) Neighborhood rate: How do Hartford parental rationales on magnet school choice vary in neighborhoods with high versus low magnet applicant rates?

5) Parental race: How Hartford parental rationales on magnet

school choice vary by race?

Part 2: Methodology -- Interview Design

Door-to-door interviews with parents of school-age children in four neighborhoods– 2 high-rate of magnet

applicants – 2 low-rate of magnet

applicants

– Current school and whether applied to magnet

– Perceptions of neighborhood school and magnet schools

– Demographics

Part 2: Methodology -- Interview Design

Part 2: Methodology -- Interview SampleTable 13: Parent Interviews by Neighborhood Type and Chooser Status

High-rate magnet applicant neighborhood

Low-rate magnet applicant neighborhood

Total

Choosers 5 7Non-choosers 5 16Others (applied and enrolled in magnets in previous years)

2 1

Total 12 24 36

Table 14: Interviews by Race of the ChildBlack 14Hispanic 14White 5Multi-racial 2Asian 1

RQ 4) Parental Rationale & Neighborhood Magnet Rates?

No meaningful differences between parents’ views on schools in high- versus low-rate neighborhoods

RQ 4) Parental Rationale & Neighborhood Magnet Rates?

No meaningful differences between parents’ views on schools in high- versus low-rate neighborhoods

• Choosers expressed similar rates of “pull” motivations in both types of neighborhoods

“My niece goes to Hartford Magnet Middle School and it has a good reputation”

-Chooser from low-rate area

“The information that I got was that the curriculum was different, and they provide more programs for the children.”

-Chooser from high-rate area

RQ 4) Parental Rationale & Neighborhood Magnet Rates?

No meaningful differences between parents’ views on schools in high- versus low-rate neighborhoods

• Non-choosers expressed similar rates of satisfaction with current school in both types of neighborhoods

“They are doing so well. When you got a good thing going, why change it?”

-Non-chooser from low-rate area

“My kids are doing good there. Most of their teachers were my teachers. They take care of them.”

-Non-chooser from high-rate area

Racial differences in talking about magnet choices

RQ 5) Parental Rationale & Race?

Racial differences in talking about magnet choices

RQ 5) Parental Rationale & Race?

Over half of white families rejected all Hartford Public Schools:

“Never thought of it. I just knew I was never sending them to a Hartford school”

“[My children] have always had a Catholic school education.”

Racial differences in talking about magnet choices

RQ 5) Parental Rationale & Race?

Over half of white families rejected all Hartford Public Schools:

“Never thought of it. I just knew I was never sending them to a Hartford school”

“[My children] have always had a Catholic school education.”

None of the 31 non-white families followed this pattern

Instead, close to half of African-American parents constructively criticized their neighborhood school:

“There isn’t much that they do with them to make them really think and focus. So I’m just trying to find something that will challenge them more and get better grades.”

Conclusion:

Our mixed-methods neighborhood-level analysis emphasizes how race influences the magnet school choice process. Based on our small-scale study, it is possible that magnet schools may not be reducing racial isolation, as originally designed.

http://www.trincoll.edu/depts/educ/css