Dr. Strangelove: Or How I Learned to Stop Worrying and Love
Effect Size
I like that title better.
I’ve been intrigued by the concept of effect size for
several years. I am not a quantitative
person, but I’m curious. I try to keep an open mind, but I still can’t shake a
lack of faith in numbers. I try to
believe, and sometimes a good quantitative person can move me in their
direction just a bit, but I’m still a qualitative guy at heart.
Two weeks ago, our school division hosted its annual “Making
Connections” conference and Dr. Matt Haas, assistant Superintendent offered a
session titled “You Can Calculate Effect Size.”
The fact that many teachers lack basic literacy in research and
statistical methods is a detriment to our profession. First, we fail to apply the results of research
in the classroom and second, we fail to adequately participate in the
conversations around educational research that drives decisions in our
divisions, states, and nation.
In a perfect world, education research would be carefully
vetted and practitioners could refer to current research from time to time in
order to refine their skills. In the
world as it is, research on education is often agenda-driven and practitioners
too often fall prey to ideas that merely sound good. (Anyone still encouraging
students to discover their Learning Styles?)
In the world of the classroom, it would do teachers well to
understand at least a little of the methods and language that researchers are
using to influence the national conversation on education. Influence that affects universally, such as
the movement to use value-added measurements to teacher evaluations. And,
influence that affects the classroom in the form of instructional methods
teachers are expected to use.
In the absence of any “authoritative body” to filter and
condense the growing body of educational research into something productive for
American education, teachers need to develop a better understanding for
themselves of how to interpret research.
Ready for your first lesson.
Effect Size= “Mean of Data Set Two minus Mean of Data Set
One divided by Standard Deviation of Data Set One.”
If you give a pre-test and a post-test, data set one is the
pre-test. Data set two is the post-test.
Sometime between pre-test and post-test you “apply a treatment.” In the case of
education, an instructional strategy.
The effect size measures how much difference the treatment made.
If like me, you’re not a number/stats person it’s easy to
stop here and pretend that it’s too confusing to waste your time on. This is too important for that, if you didn’t
get it read it again. An effect size
should tell you how much an instructional strategy facilitated or inhibited
student growth. Yes growth (or
value-added if you’d rather.)
Take this tool for what it’s worth. It’s the primary tool used by researchers
such as Marzano and other education “meta-analysts” to determine instructional
methods that work, the techniques have the greatest effect size on student
achievement.
Still, the greatest power in using effect size is
informative, not prescriptive. For example, Marzano’s well-known book
“Classroom Instruction that Works” presents strategies that have proven,
through meta-analysis, to have a higher than average effect size on student
learning. He does not imply (and even
directly states otherwise) that a given strategy WILL work on every student in
every situation.
That's likely the greatest flaw with this type of research. What should be informative for our educational practices becomes prescriptive through policies and evaluative methods. I imagine that across the country, more than a few
teachers have been evaluated on consistently applying the “strategies that
work” without regard to immediate evidence of whether the strategies are
working or not, leaving them skeptical and critical of the entire body of work
that attempts to isolate the most effective classroom strategies.
This is why all of us, from classroom teachers to
legislators enacting policy, should have a better understanding of educational
research.
you should talk about this a lot more, please.
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