Last blog,
I wrote about data-mining but I wasn't specific. In 2002, when I took a course
in differentiated instruction from Carol Ann Tomlinson, one of the tenets to
“getting it right” was to let your choices be data driven. A decade ago, my
data was tainted because I was using only my own assessments and observation. I
was using information like individual student learning styles, IEPs, and 504
considerations. We did not have the advantage of web-based assessment engines
like studyisland.com or PVAS at the time.
We are more
than half-way through the first marking period and that is part of my
uneasiness with my new endeavor. It could not be helped, but I wish I was
starting sooner. I wasn't going to attempt to develop individual improvement
plans, alternative lessons, or flexible groupings based upon my (shrinking)
gut. (Guess who is reversing his
middle-aged spread. --- Fodder for another blog. Down 15# and counting!) So,
for my initial plan, I used my students’ first quarter benchmark scores from
study island and my observations of the writing samples I had collected, so far, from journal entries and short responses to prompts.
I wanted to
know a few details to start. The first question: “Who passed and who failed?”
While gathering my answer, I discovered, as I mentioned in an earlier blog,
that my students were all over the map. There wasn't even a clear trend among
the advanced, proficient, basic or below basic scores. Strengths and weaknesses
fluctuated between individuals and across class grouping. With that distinction
or inconsistency noted, I developed a new question. “What are my students’ strengths
and weaknesses?”
Study
Island separated its questions into four domains and students were rated in
each by their scores: Language, Writing, Reading, and Informational texts. A
few of my students showed proficiency and even mastery in two or more domains,
yet still they scored “basic” because one domain score was significantly low
enough to drop them into a failure overall.
I admit
that, based upon past eighth grade performances, I was really looking for the
data to validate my assumptions about this cohort of students. I expected to
see that everyone was weak with reading informational texts. Far more students
not only were proficient in informational texts but they even scored perfectly
in that domain. However this area is still a concern area because this form of
reading is still a weakness for many of my students. So, those students were
going to need more time learning how to attach the genre.
The second
tenet of DI that I learned was to use the data to inform my decisions for
lessons, and groupings, rather than the behavior and interpersonal dynamics
among my students. As you may expect, some students had multiple weaknesses but
some of these weaknesses I have disregarded this month because some of the
benchmark was a pretest of information not yet rolled out, that will be
introduced later in the curriculum.
Our school
has already committed to remediation and enrichment for all students who need
it, regardless of IEP, 504, and other legally binding markers. The data
showed me that the advanced scorers
still needed remediation in their weak areas (some areas were under 60%.) The
2012-2013 PVAS data just went live this week in school. That was too late to
help me achieve my goals for first marking period, but the data may paint a
different picture than the results from our September testing. Since I want to
see all my students grow, I need to remediate all of their weaknesses. The
benchmark domain markers were a good place to start, and since they will be
tested each quarter, the data will allow me to track progress, quarter by quarter.
