Data, Data, and More Data...

In our experience with RTI, we have really made a transition to look at data and, more importantly, look at what the data are telling us. As long as you have good data, the data will tell you who needs an intervention, what intervention they need, and whether the intervention is working. I have seen schools that have a lot of data but do not have the desire, the means, or the time to look at and interpret the data. Why waste the time collecting it if you are not going to use it and use it well to help students? With that being said, here is how we use some of our data in our RTI model.

I would like to take a little time to review last year's data and see how we did and where we need to go. As I mentioned in the last blog post, last year 95% of our 4^th grade students scored proficient or above on our state assessment in reading. As 3^rd graders, 71% of this same group of students scored proficient or higher on our state assessment in reading. This shows an increase of 24%, or in our case about five students. When we look at our 3^rd grade data from last year, we see a little different story and still have some work to do. Only 48% of last year's 3^rd grade class scored proficient or better on our state assessment. At first glance this does not seem very good, but when we look at the data and realize that at the beginning of the year only 32% of these students were reading at grade level then once again we have made substantial progress using RTI. We obviously still have some work do with this group of students, but with the increases that we have seen by using RTI last year we expect to make bigger gains this year! We attribute these increases to our use of RTI and to implementing with fidelity research-based quality interventions. We used our data to identify the individual needs of each student and then put in place an RTI model to provide specific interventions that focus on the individual needs of each student.

With the success that we have seen with our reading scores by using RTI, we also have begun to implement an RTI model with math. Unfortunately, there just isn't enough time in the day to implement this with the same intensity as we do with our reading interventions; nonetheless, we have divided our 3^rd and 4^th grades into to small groups with similar needs and are providing small-group instruction based on these needs. We have once again used a flooding model, bringing in our Title I teacher, special education teacher, and our math facilitator to deliver instruction to these small groups. The students who are at grade level are working with the classroom teacher on extension and enrichment activities. Our math facilitator is also working with this group of teachers to identify and implement specific interventions based on the needs of students. The math facilitator is working to ensure that the interventions we provide are research-based and that we are implementing them with fidelity. We hope to see an improvement in our math scores as a result of this model; I will keep you updated on how this is going.

We also have used the data from last year to evaluate our interventions and identify areas where we need new or better interventions. In analyzing our data, we see that a significant number of our students struggle with reading fluency, which research has shown to have a direct effect on comprehension. So, we have put in place two new interventions to help students with their reading fluency. These interventions are mainly directed toward students at the upper elementary grades — in our case, 3^rd and 4^th grade. In our lower grade levels, mainly kindergarten through 2^nd grade, we have seen that many of our students had a need in phonemic awareness and vocabulary, so we have identified new interventions to address these needs in our primary grade students. With the progress that we have made, we have left many of our other interventions in place and have supplemented in areas where the data have shown us there is a need.

So let's take a little look at some special education data. We currently have 1, that’s right 1, student identified with learning disabilities in our school of 114 students. We also have seen a drastic decrease in the number of referrals for special education for a learning disability — going from 6 students 2 years ago to just 1 last year. This student did not qualify for special education because at the time we tested we still had to meet the discrepancy model (our state has been a little slow to allow the use of RTI in identifying students as having learning disabilities), so we had no new students qualify for special education last year with a learning disability. We have put a couple of new interventions in place this year and now this student is taking off and will likely not even be referred for special education.

Hopefully, all this talk about data has not bored you. Our staff really enjoys looking at data and letting the data tell us what is happening and where we need to go. Sometimes looking at the data is not always fun and the story that it tells is not always the most pleasant, but you have to look at it and face it in order to change it.