Andy and I were just confirmed to conduct a workshop on graphing, calculating, and interpreting rate of improvement in June 2013! Our state technical assistance network is hosting an implementers forum to have school-based RtI teams within the state come together for professional development. We’re looking forward to presenting to a mixed group of professionals!
I’m in my second year at my current district where I serve the secondary student population (grades 7-12). My district’s elementary schools are doing a really nice job with their response to intervention (RtI) framework but we have a lot of work to do at my middle and high schools. At the end of last year, we purchased licenses to use STAR Math and STAR Reading (and STAR Early Literacy for the Elementary folks) through Renaissance Learning. I’ve recently been through a couple of trainings for how to administer and interpret the assessment and reports. I’m hopeful that these assessments will do a better job of capturing my older students’ skills, especially for the student’s in special education since they’ve been using the same CBM probes for years. Our STAR assessments can be used for universal screening, progress monitoring, and diagnostic purposes. Plus, they tie into the Common Core standards, which is so helpful for teachers who need to make the connection between assessment to high school classes!
Another feature I’m impressed with so far (surprise) is that the system provides you with a Student Growth Percentile. For instance, if a 7th grade student scores a grade equivalent of 4.5 on the Reading assessment, the report will tell me how much a student with that same profile (7th grade scoring 4.5) will typically “grow” by the end of the year. I’ve always wondered “how much growth can we expect?” from our students. I’ll have to see how this plays out for the school year. Because I need another project…
After attending some sobering workshops at my national school psych convention in February, I’m a little worried about the weight we place on student rate of improvement data when research suggests that we need at least 14 data points to have a reliable oral reading fluency trendline (Christ, Zoplouglu, Long, & Monaghen, 2012)!!! The STAR assessments can provide a reliable trendline after 4 data points. Think about how much sooner we could be making solid instructional decisions?! I’m curious if anyone else is using computer adaptive tests. It will certainly be a learning curve (ha…) for me this year!
Thanks to everyone who came out to the workshop session yesterday! Our workshop focused several aspects of rate of improvement including (a) how we arrived at the conclusion that rate of improvement is a meaningful statistic that can be used as part of data-based decision-making, and a need to be consistent with how to calculate, graph, and interpret rate of improvement. It was a great opportunity for us to work with practitioners and educators interested in the topic of student growth in relation to eligibility decision-making. While a presentation that incorporates technology, especially the variability between software versions can be daunting, we seemed to get through the workshop in a way that reached everyone. However, if you have lingering questions, feel free to email us! We will be posting the latest PowerPoint to the Downloads section of the site this weekend. We appreciate feedback, comments, and questions! We are hoping to be invited to present again at next year’s convention in Seattle, WA!
Andy McCrea and I are presenting next month in Philadelphia for the National Association of School Psychologists Annual Convention. We are hoping to have an informative and interactive session with our participants. To sign up visit http://www.nasponline.org/conventions/2012/workshops.aspx and click on WS36. All participants are strongly encouraged to bring a laptop or tablet with Excel or Numbers!!! Our workshop can be attended as “Part II” to Dr. Joe Kovaleski’s workshop WS31.
Our workshop on Thursday, February 23, 2012, 12:30-3:30PM. Andy and I review the research on interpreting student growth using curriculum-based measurement data, model how to use Excel or Numbers to calculate a rate of improvement statistic, and discuss how student growth fits into the eligibility conversation within an RTI model. Data analysis and graphing will be featured. Participants are strongly encouraged to bring a laptop or tablet computer equipped with Excel or Numbers. This workshop can stand alone or serve as Part II to Dr. Kovaleski’s introductory workshop entitled Determining Eligibility for Special Education in an RTI System: Basic Concepts and Procedures (WS31), Thursday, February 23, 2012, 8:30–11:30 a.m.
Bring a colleague! Hope to see you there!
If you were to open your old graduate level stats book, you might not find the phrase “rate of improvement,” in the index, but you would find some text on “slope.” Essentially, they are synonymous terms, one being slightly more angled toward the positive.
In algebraic terms, rate of improvement can be defined as the vertical change (y-axis) over the horizontal change (x-axis). More simply put, slope is the rise over run. Or the steepness of a line. The key word here is line. In order to calculate slope, one must first have a line. Once a line is determined, the formula for calculating slope is:
m = (y2 – y1) / (x2 – x1)
m = slope
(x1, y1) = one point on the line
(x2, y2) = a second point on the line
Typically, when we plot student data, we end up looking at data points on a graph. Some commercially available systems provide a general line as a guide approximating where the student’s data points should fall. With just this information, there is no line from which we could calculate an accurate slope. Therefore, we have to create that line! It is the position of the authors of this site that linear regression is the best method for calculating an accurate line to determine rate of improvement.