Normal vs. Necessary Academic Growth


“How is it possible that our students are showing good growth on the MAP test but failing to meet proficiency on our state test?” 

This question arises occasionally with NWEA partner school districts using MAP assessments, and it highlights the need for clarity about the distinctions between state proficiency standards and NWEA norms for growth and status.  One really has nothing to do with the other.

Unlike content standards, which designate what students should know about any given subject or content area, proficiency standards designate what minimum state test score constitutes sufficient subject mastery.  Even when content standards remain the same, states may adjust their proficiency standards (that is, the state test scores that students must meet) upwards or downwards over time.  Increasing the cut scores upwards tends to lower state proficiency rates, while decreasing the cut scores tends to boost rates.

NWEA’s status and growth norms, on the other hand, are established independently of specific state proficiency standards.  Instead, these norms show the distributions of performance and growth that are representative of students across the nation as a whole.  These norms can tell us, for example, that a sixth grader with a fall math score of 227 is performing at about the 68th percentile, relative to other sixth graders across the nation at that point in the school year.  Those norms also tell us that typical growth between fall and spring for such a student is, on average, about 6 points (with a standard deviation of 6.1).

If that sixth grader with the fall math score of 227 makes average (about 6 points of) growth, will she/he meet the spring proficiency target?  Yes, probably, since 233 represents 68th percentile standing for sixth graders in the spring, an achievement level far higher than the proficiency bar set by most states (e.g., The State of Proficiency).  But students with lower initial achievement would need to make far more than typical growth in order to meet proficiency in the spring.  For example, a sixth grader with a fall MAP math score of 201 is performing at about the 11th percentile, according to NWEA norms, and such a student will show average growth of about 6 points between fall and spring (with a standard deviation of 6.1).  But a RIT score of 207 (about the 11th percentile for sixth graders in spring) is lower than most sixth grade proficiency standards for nearly all states.  For this student, meeting typical growth will not be enough.

So, while the norms may be insufficient for setting “Growth to Standards” goals that would provide reasonable assurance of meeting state proficiency standards, they provide important context for understanding how reasonable such goals may be.  If the sixth grader with the fall math score of 201 from the previous example lived in Oregon, for example, the estimated MAP score in the spring associated with “meeting standards” is 219 (based on the Oregon/MAP Linking Study), implying that at least 18 points of growth would be required over the interval between fall and spring.  Since we already know that the typical growth is 6 points, then 18 points between fall and spring constitutes 98th percentile growth, something only 2% of kids with this starting score could achieve.  In other words, very few students could meet such a growth goal without extraordinary assistance.

Assigning a student growth percentile to any particular growth goal is a useful strategy for identifying students who require additional resources in order to meet the goal.  The student whose growth goal requires 98th percentile growth is very unlikely to meet that target without considerable assistance, whereas a student whose growth goal is associated with 10th percentile growth would be 90% likely to meet that target under normative conditions.  Under such circumstances, a student whose growth goal was associated with a percentile less than 50 is likely to meet their growth goals, whereas growth percentiles greater than 50 require greater than average growth. Consequently, growth percentiles may be useful as one point of consideration when determining how best to allocate limited additional resources.