Mine MAP Test Data with Stop Highlighting
I recently attended a workshop entitled "Using Assessment Results" which had some great ways of disaggregating and looking at data. We have established a data committee PLC at our school that has been meeting but we are taking steps to use data we receive from MAP to improve program, and we're starting to take steps of how to do it at a team and department level. Our school is lucky. We are using this data to improve teaching, not use it as a means to fire teachers which seems to be the norm in many schools across the US.
MAP test data has been hard to analyze for us. We're all aware of how RIT scores show comparison and growth, but other than putting them on a scale, we haven't had any definitive ways of grouping students together for interventions.
Determining Cut Scores
One of the key workshop points was to determine "cut scores" as an institution. This should be done first and foremost and these cut scores give a basis for comparison. Some examples of what cut scores look like are as follows:
- Who is exceeding expectations, meeting expectations, just below expecations, or a concern?
- Who is at grade level, just below grade level, or grades above or below grade level?
Identifying Stanines on A Bell Distribution Curve
One method for determining cut scores is using the stanines on a bell distribution curve as seen below:
Although this could be a potential area for debate amongst your school, one could use stanines and percentile rank to determine cut scores. For example
- Students in stanine #8 and #9 are above average and higher. The sum of their percentages is 11% so students in the top 11% of the test taking population are exceeding expectations. This translates to "Students in the 89th percentile and up are exceeding expectations"
- Students in stanine #5, #6 and #7 are just above the middle. Stanine #4 could be as it is near the middle, but if you're trying to develop a high quality academic program, consider using stanines #5-#7 as students who are meeting grade level expectations. This translates to: "Students in the 77th to 88th percentile are proficient, at or just above grade level norms"
- Students in stanines #5 and #6 are close to, but just under grade level norms. The sum of their percentiles are 37% so this translates to "Students in the 41st percentile to the 76th percentile are just under grade level expectations but are making progress to it"
- Finally, students in stanines #1-#4 are well below average. The sum of their stanines are 40% so "Students in the bottom 40% are a concern"
Now we have established cut scores for our population. The are:
89%-99% Exceeding Expecations
77%-88% Meeting Grade Level Expectations
41%-76% Just Below Grade Level Expectations
1%-40% Concern
77%-88% Meeting Grade Level Expectations
41%-76% Just Below Grade Level Expectations
1%-40% Concern
Enter Stop Highlighting
Now that our cut scores have been established we can determine who in the class is in each category and look at distrbutions. Stop highlighting involves marking with green who is exceeding, yellow who is meeting or just below grade level and marking with red who is a concern.
The black line through the middle is the 77th percentile. From this we can see that there is one student who is a concern, five who are exceeded expectations, and the majority of the class progressing to or proficient in grade level expectations.
We Have Cut Scores-Now What?
Instead of teaching to the middle, consider offering learning activities of various levels of complexity. For instance, the green students need to be challenged. The red students need a lot of entry level help and should be monitored more frequently in class. Rather than "pidgeon holing" students into activities which is likely to make them feel like they're being stereotyped, consider giving them choices of meeting the curriculum. These different levels of challenge by choice can be packaged with different levels of difficulty (for example through blooms taxonomy) which lead to targeting instruction to their ability.
Ok, am I missing something? You seem to have stanines 5 and 6 in two categories.
ReplyDelete•Students in stanine #5, #6 and #7 are just above the middle. Stanine #4 could be as it is near the middle, but if you're trying to develop a high quality academic program, consider using stanines #5-#7 as students who are meeting grade level expectations. This translates to: "Students in the 77th to 88th percentile are proficient, at or just above grade level norms"
•Students in stanines #5 and #6 are close to, but just under grade level norms. The sum of their percentiles are 37% so this translates to "Students in the 41st percentile to the 76th percentile are just under grade level expectations but are making progress to it"
Dear Anonymous,
DeleteGood points. Some schools will have the top three stanines as considered "exceeding". I was told Singapore American uses #8 and #9 (top 11%) were exceeding and #5 #6 and #7 were at or just below grade level. The bottom 40# are a concern and should have a specialized plan for action.
There is some ambiguity if a student sits on the fence like you allude to. For example, if a student is at the 89th percentile, are they in stanine #8 or #9? I'm been told that this hinges on their previous score. If in the fall they were lower and the spring were higher, the improvement bumps them up into a higher classification. Same thing for a fall.
However, with standard of error being +/- 3 points, students could be placed in a number placements, so it's good to use this as "a" data point and not "the" data point. If teachers use good assessment practices, they'll generate some good internal data that will also give a broader perspective into the students learning at a more authentic level.
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