By Joseph Kovaleski, Indiana University of Pennsylvania
I recently participated in a web-based forum on data-based decision making and RTI sponsored by the RTI Action Network. I presented with Lynn Fuchs from Vanderbilt University and John Carruth, an assistant superintendent from Vail, AZ. It was a great pleasure to work with Lynn, who has contributed so much to the fields of special and general education, and with John, who has provided exemplary leadership in implementing RTI in his school district. In 90 minutes, I think we provided a good overview of the use of assessment within a three-tier model, focusing on screening/benchmark assessment, progress monitoring, and diagnostic assessment. You can access the forum at www.connectlive.com/events/rtinetwork043009/.
On the heels of the forum, I’d like to talk about assessment and data-based decision making. Let's start with screening. Regardless of whether they are actually using a full multi-tier model, most school districts these days seem to have adopted screening of all students in academic core subjects, at least at the elementary level. It is common for districts to screen students three times per year, typically in September, January, and March or April. I believe screening instruments should have the following features:
- brief and easily administered
- research-based
- highly correlated to skills assessed
- benchmarks that are predictive of future performance
- high reliability and validity
- sensitive to small increments of change
- readily and efficiently warehoused
- capable of producing user-friendly summary documents
Basically, these benchmark measures should be capable of reliably predicting students performance on high-stakes assessment (e.g., state tests) and, more importantly, provide teachers with useful data regarding where all their students are functioning.
Historically, schools have used instruments based on curriculum-based measurement (CBM) such as DIBELS and AIMSweb. As is well known, both instruments assess early literacy skills, and AIMSweb also taps early numeracy skills. In Pennsylvania, we have also been using 4Sight, a measure of reading comprehension developed by the Success for All project at Johns Hopkins University. 4Sight has given our teams an added dimension that is a nice supplement to oral reading fluency data. My colleague Ed Shapiro has done a study that found that using DIBELS and 4Sight together predicted better than either assessment alone.
Relatively new on universal screening horizon are the assessment products that have been developed by Renaissance Learning, including Star Reading, Star Early Literacy, and Star Math. These instruments are particularly promising because they are computer-based and require little time for administration, which should be particularly attractive to middle and high school applications of RTI. I had the opportunity last month to observe an elementary data-analysis team using these measures with their students at the Brown International School in Denver. The team did a great job in identifying students’ needs and planning instruction using these data.
Schools that are looking for the most effective universal screening measures should consider accessing Web sites that provide a critical review of these measures, such as the National Center on RTI. All of the aforementioned measures, with the exception of 4Sight, are reviewed there.
Next up: some thoughts on progress monitoring.
Comments