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Four Ways to Monitor Achievement Gaps

Bloomington Public Schools - MDE Guest Blogger, David Heistad, Ph.D., Executive Director of the Research and Evaluation Department
Second in a five-part series

Published: April 16, 2014

One reason that Bloomington has had success in decreasing achievement gaps over the past few years is the use of assessment information for data-based decision-making. This blog provides four examples depicting achievement gap reductions in reading and math.

Example 1: Using Minnesota Data on MCAIII Index Rates to reduce achievement gaps 50% by 2017

Index rates for each group of students are calculated as (the number of proficient students in the district) plus (one half of the number of partially proficient students in the district) divided by the total number of students in the district. Only students continuously enrolled in the district since Oct. 1 and taking the MCAIII test in the spring are included in this calculation. In the example above, all groups of students must decrease their gaps to an index rate by 50% from 2013 to 2017. Asian students start off in 2013 with an index rate of 72, which is 28 short of 100. This group must increase 14 points in four years, or 3.5 points per year.

Districts may increase their index rates a half point by moving students from “partially proficient” to “proficient” or from “not proficient” to “partially proficient.” If a student improves from “not proficient” to “proficient,” the index rate would increase by a full point.

Example 2: Using Multiple Measurement Ratings (MMR) Growth and Gap Reduction Data compared to similar schools in Minnesota

MMR data and demographics for each school can be viewed on the Minnesota Department of Education website’s Report Card.

The table below compares the MMR Rating, Focus Rating, Proficiency Points, Growth Points and GAP Reduction points for Valley View Middle School in Bloomington and five middle schools in Minnesota with similar demographics.

MMR comparisons were provided to each elementary, middle and high school principal in Bloomington. Principals were encouraged to contact comparable schools in the state with higher MMR ratings.

Example 3: Using Measures of Academic Progress (MAP) Math Growth versus national norms for groups of students by Income Level

Similar to the calculation of Growth for MMR using state growth norms, the Measures of Academic Progress (MAP) used by many districts in Minnesota compares each student’s growth in reading and math to a national norm of students at the same grade with the same pretest level of performance. The graph above shows MAP Math testing results for students receiving free or reduced price lunches compared to students who received full price lunches over two consecutive school years. From 2011 to 2012, only 39.8% of students in poverty made national norm growth. From 2012 to 2013, students in poverty increased their rate of growth in Math considerably, with 57.3% of students making national norm growth.

Example 4: Using Measures of Academic Progress (MAP) Math Growth versus national norms for groups of students by Income Level

A final way of tracking the progress of groups of students in Bloomington is through the Pathways to Graduation “rainbow charts,” based on a study of NWEA MAP scores that predict eligibility for 2 and 4 year college, a select college, such as the University of MN Twin Cities and a very select college, like Carleton.

This pathway graph depicts the progress of continuously enrolled African American students in Bloomington from 2007 (Kindergarten) through 2013 (Grade 6). Each year the average score improves and nears the “on course for 4-year college eligibility” pathway.