Magnet Schools and Peers: Effects on Student Achievement Dale Ballou Vanderbilt University November, 2007 Thanks to Steve Rivkin, Julie Berry Cullen, Adam Gamoran, Ellen Goldring and Keke Liu. Research Questions • Has attending a magnet school caused an increase in mathematics achievement? • How large is the influence of peers on mathematics achievement? • How much of the magnet school effect remains after controlling for the influence of peers? Study Setting • Middle Schools in a Large Southern District 1 selective academic magnet 4 non-selective magnets 5 student cohorts 6 years: 1998-99 through 2003-04 Grades 5 & 6 Admissions Lotteries • Oversubscribed magnets conduct lotteries • Students may enter multiple lotteries • Students who are not outright winners are placed on wait lists • Wait-listed students accepted until the first week of school Non-lottery Admissions • Sibling preferences • Promotion from a feeder school • Geographic priority zone These students are not included in the study sample (though they do enter the calculation of peer characteristics). Research Design • Lotteries assign students randomly to school type and to peers (magnet school peers vs. non-magnet peers). • Randomized design circumvents biases arising from self-selection of schools and peers. Limitations of Design • Results may not generalize beyond lottery participants. • Effects are relative (magnet schools vs. mix of non-magnet schools attended by lottery losers). Lottery Participation Academic Composite Non-Academic Applicants 2315 2594 Outright 883 1450 Winners Delayed 223 756 Winners Losers,This 1209 388 Lottery Losers, All 539 199 Lotteries Grade 5 Enrollments Academic Composite Non-Academic This Magnet 758 1061 Other Magnets 287 339 Non-Magnets 834 846 Left system or 436 346 Not Tested Potential Pitfalls • Substantial non-compliance, especially among winners of non-academic lotteries, attenuates estimated treatment & peer effects based on comparison of winners and losers. Remedy: Use lottery outcomes as instruments to predict probability of attending magnet school, outcomes interacted with peer variables at magnet & zoned schools as instruments for peer characteristics. • High rates of attrition from district can introduce systematic differences between treatment and control groups. Remedies: Control for student characteristics (race, income, ESL, special ed, gender, prior achievement). Analyze attrition patterns for evidence of differences between winners and losers. • Participating in multiple lotteries increases chances of winning. “Multiple participants” may differ in ways related to achievement. Remedy: Control for the combination of lotteries each student entered. Winners are compared to losers who entered the same combination. • Lotteries randomly assign students to magnet school peers or peers in their neighborhood (zoned) school, but lotteries do not determine the characteristics of the latter—residential decisions do. Remedy: Control for characteristics of the peers in the zoned school. Peer Characteristics • Percentages black, low income (free & reduced-price lunch program), special ed, ESL, female • Absenteeism rate • Disciplinary incidents (rate per student) • Intra-year mobility • Prior achievement in math and reading Model (Summary) • Two treatment variables (academic magnet, composite non-academic magnet) • Variation in peers resulting from lottery outcomes • Other controls (student characteristics, peers at the zoned school, lottery participation indicators, year by grade effects) Findings • When model does not include peer characteristics - Academic magnet, + 18% in grade 5, drops to +10% in grade 6 (% of normal year growth) - Non-academic magnet, no grade 5 effect, +54% in grade 6 • When models include peer characteristics - Reducing percent black from 75% to 25% increases scores by 60% of normal year growth. - Effect of percent low income is about half that large. - Other peer characteristics have no statistically significant effect. - Controlling for either percent black or percent low income, the effect of the academic magnet disappears. - The large 6th grade effect in the non- academic magnets remains substantially undiminished. Checking Alternative Interpretations • Are peers a proxy for heterogeneous response to treatment? Check: Interact magnet treatment indicators with all observed student characteristics. Finding: Peer effects are undiminished. • Are peers a proxy for teacher quality? Check: Control for teacher quality by including teacher fixed effects. Finding: Peer effects are undiminished. Attrition, Academic Magnet Lottery Participants Left System After Grade: Winners Losers 4 13% 21% 5 8% 14% 6 9% 11% 7 6% 9% Attrition, Composite Non-Academic Magnet Lottery Participants Left System After Grade: Winners Losers 4 8% 12% 5 12% 9% 6 10% 4% 7 12% 16% Potential Attrition Biases • Lottery losers are more likely to leave the system than winners. • Losers are also more likely to leave when they can afford private schooling. These tend to be higher-achieving students. Result: Losers who remain in the system have lower achievement than winners who remain. • Unfavorable peers at zoned school make losers more likely to leave system. • Effect greatest among those who can afford private schooling. Result: Quality of peers positively correlated with losers’ achievement. Estimated peer effects appear too strong. Checking Attrition Bias • Are rates of attrition correlated with variables that predict individual achievement (race, income, prior achievement)? • Yes, but not differently for winners and losers. Conclusions • For at least some students in some places, magnet schools have a positive effect on academic achievement. • There are very strong peer effects on middle school achievement. Do not appear to operate through behaviors readily quantified with administrative data (attendance, disruptions, mobility).
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