Stage I (Characterization): Hypothesis:

1. Bridging the Achievement Gap in Elementary EducationLincoln J. Chandler, Operations Research Center, MIT (ljc@mit.edu)Dr. Arnold I. Barnett, Sloan School of Management, MIT (abarnett@mit.edu) Abstract: When education systems report significant difference in the academic performance of its minority students, this phenomenon is referred to as an “Achievement Gap.” Using extensive longitudinal data from an ethnically diverse elementary school district, we investigate existing and alternative approaches to identifying the factors that promote the gap and the reform strategies that will be most effective in closing the gap. STUDENT – LEVEL PERSPECTIVES OF THE GAPS RESEARCH OVERVIEW ALTERNATIVE CHARACTERIZATIONS: AN EXAMPLE Suppose the following scenario: Total Population (n) = 10; Group A = 3, Group B = 7 Stage I (Characterization): Hypothesis: Alternative (e.g., nonparametric) methods of gap assessment may provide additional insights how particular groups fare Approach Using 8th Grade achievement data for a single year, assess how different characterizations increase and diminish the appearance of the gap Stage II (Gaps over Time): Hypothesis: There will be discernable patterns in an longitudinal analysis, both for a single group of students and different cohorts of a given grade level Approach: Applying the characterizations developed in Stage I, extend the dataset to examine the evolution of the gap over time. Temporal analyses Stage III (Best Practices): Hypothesis: The analysis will reveal environments in which the achievement gap is minimized, facilitating the ability to benchmark and prioritize reform efforts Approach: Leverage the relationships observed in Stages I and II to identify instances of high overall performance with low or no gap. Use these instances to gauge size of near-term opportunity and to make recommendations regarding reform efforts, where possible. 1 2 3 4 5 6 7 8 9 10 Score Rank (highest) (lowest) For Group A, sum of ranks (S)= 11. X = (S-E[S]) / (E[S]-min(S)) X = -0.47 S = 11 min(S) 6 max(S) 27 E[S] =15.5 -1 0 1 Group B outperforms Group A Group A outperforms Group B We renormalize S over its range to obtain an index for the relative achievement of Group A. Comparing mean performance characterizes the overall gap, but provides no information about variance within the different populations. TEMPORAL ANALYSES OF ACHIEVEMENT DATA – 2004 – 8thGrade – 2001 – 8th Grade – 2002 – 8th Grade – 2003 – 8th Grade Analysis over multiple cohorts of a single grade level permits study of school effects – 2003 – 7th Grade – 2002 – 6th Grade Analysis of a single cohort of students over multiple grade levels provides insight into how the gap evolves within a given group Student - level data allows one to depict the gap across the population, providing a view of the score distribution at every level of achievement. – 2001 – 5th Grade