There are at least 5 fundamental components to a well-designed MTSS (Multi-Tiered System of Support). One of those components is data-based decision making.
Our friends at OregonRTI have suggested “Teams should use data and decision rules to determine effectiveness of the core program, identify students in need of interventions, and evaluate student progress to determine next steps.”
But, what exactly should that look like? If you are new to the idea of setting targets and triggers for your environment, where should you start?
We’re going to offer a few suggestions that will help you get started. In this post, we will assume that your state has a state assessment of some sorts, and that your district has a Universal Screening assessment in place (such as MAP, STAR, iREADY) – by the way – we are not endorsing – just mentioning for reference.
Method 1: Percentiles
Perhaps the most straightforward way to determine who among your students needs intervention is to set a cut point based on national percentiles.
A common starting point is somewhere between the 25th and 30th percentiles. Mileage on this will vary – depending on your actual population and their performance.
If students score below the trigger point, they should be considered for an intervention of some sorts – or at least some follow-up screening to determine what skills need additional support.
This methodology is fine – as long as your students are like most students in the country. These norms are national norms – meaning that the scores reflect the population of students across the country.
Most school districts aren’t like most of the country (whatever that means anyway). So, how helpful is that really? It may not be. It may be more helpful to look at norms and scores that more accurately reflect the learners within your own state.
Method 2: Linking Study
When state assessments are administered, there is a score on that assessment that the state deems as “proficient.” That’s the target – that’s the goal. The state is asking schools to get students in their systems to “proficient.”
Many of the main universal screening assessments (MAP, STAR, iREADY, etc) have done linking studies – studies in which a state’s assessment data is mapped to proficiency levels for a certain state.
We are located in Wisconsin – and our state assessment is the Forward exam.
NWEA MAP has performed a linking study – and as you can see in the table, proficiency in ELA at grade 5 is a score of 610. MAP has determined that if a student scores a 211 on the MAP assessment in the fall of grade 5, they are likely to be proficient on the Forward exam.
Now, when determining what cut scores to use to indicate need for intervention – the situation is slightly more murky. As a starting point, we can use the “Below Basic” proficiency level.
Looking at the table, students who score below a 194 on the Fall MAP assessment in grade 5 should be considered for some type of intervention – or at least some follow-up screening to determine what skills need additional support.
So – there are two ways you can get to targets and triggers using your Universal Screening data.
We have one more method – but it’s going to have to be an entire post. It involves some decently mid level statistics – and it’s just too much to put in one place.