Welcome to the Deep Dive. We sift through sources
to bring you the key insights, the important
stuff. And today, well, we're tackling something
many of us have strong opinions on, standardized
testing. But what if the whole idea was maybe
flawed right from the get -go? There's this question
Peter Green asked over at Forbes, is the big
standardized test a big standardized flop? In
our main source today, an article by Gary Ackerman
from back in September 2018 on hackscience .education,
it gives a pretty clear answer, a definite yes.
Now, lots of reasons have been thrown around
for why these tests haven't worked out as hoped,
but the source, it goes a bit deeper. It argues
it was actually doomed to fail from the very
beginning. Why? Because it was built on what
the author calls an untenable foundation. Okay,
let's unpack this. The basic problem, according
to Ackerman, seemed to be trying to shoehorn
a scientific lab experiment model onto, well,
messy, complex human education. The article kicks
off by looking at why standardized testing and
this whole accountability movement even started.
The basic argument was, you know, the public
should only pay for what works in schools. And
how do we know what works? Well, we measure it.
Seems simple enough, right? Especially if you've
got a science background. Oh, absolutely. That
approach feels very familiar if you've spent
time in, say, the natural sciences. Science often
uses this pretty straightforward method for finding
answers. You set up an experiment. You control
everything in the environment, keep it all constant,
except for just one single thing, one variable.
Then you change that one variable for a specific
group. That's your treatment group. After you
make the change, you measure. You look for any
growth or change you're interested in. And here's
the key. any change you see. You can confidently
say it was caused only by that one thing you
changed, because everything else was held steady.
The source gives a really good example, actually,
from Motney. Imagine a student, maybe an undergrad,
growing legumes, hydroponically, under grow lights,
very controlled. They'd manage everything meticulously,
the nutrient mix, the substrate they're growing
in, they'd even randomize the seeds, make sure
all the plants are right next to each other,
total control. Then, for just one group of those
plants, the treatment group, they add something
tiny. Let's say... trace amounts of heavy metals
to the nutrient water. Now, if they then observe
fewer nodules, those are the little root growths
that grab nitrogen from the air if they see fewer
nodules only on that group. Well, the conclusion
is pretty inestable. The heavy metals caused
it. Nothing else could have. And that really
gets to the heart of it. These experiments, they're
specifically designed to remove the environment
as a factor. You're stripping away all the complexity
to isolate one single cause and its effect. OK,
that makes total sense. In a lab. where you can
control light, water, nutrients, everything.
But taking that idea and applying it to education,
to kids in a classroom, that feels like a huge
leap. So here's where it gets really interesting,
or maybe really problematic. What happens when
you try to map that super controlled science
model onto a school? That is precisely the issue
Ackerman raises. It's the fundamental flaw. Students,
as the source puts it, they live in a rich and
variable environment. Rich and variable. Yeah,
that sounds about right. It's not just a small
detail you can tweak. It's basically an insurmountable
barrier for that specific experimental model.
You just cannot, and you wouldn't even want to
control all of the variables that affect how
they attend, engage with, and learn in school.
Great. Think about everything that affects a
student on any given day. Exactly. Their home
life, what resources they have access to, how
they're feeling emotionally, their health. Did
they sleep well? Are they interested? What did
they eat for breakfast? All these things, they're
huge variables, constantly changing. Impossible
to control. Totally impossible. And because we
can't possibly control or even account for all
those factors in a student's environment, well,
then we have no scientifically rigorous way,
using that model, to say that this specific teaching
method caused that specific change in test scores.
The link. that direct cause and effect, it just
gets completely lost in the noise. It's untraceable.
Wow. So the entire premise, the very foundation
of using standardized tests in this way for accountability
was shaky from day one. That's a pretty big claim.
It suggests it wasn't just about choosing the
wrong tests or bad implementation. It was the
core. concept itself that didn't fit the reality
of learning. Now, the source does mention, you
know, the other common criticisms people have,
things like, what are these tests really measuring?
Are the constructs even well -defined questions
about validity, reliability, how the data is
collected, ethical concerns, those all get a
nod. Right, the author acknowledges those are
out there. But the main thrust, the thing this
article really hammers home and what we're focusing
on, is that initial fundamental flaw, the misapplication
of the astermental design. Exactly. What's fascinating
here is the argument that you don't even need
to get bogged down in debating those other details.
The core idea, the attempt to treat education
like a controlled botany experiment, was flawed
from the start. The foundation was just untenable,
as the author says. Built on sand, essentially.
Pretty much. And the article touches on the human
side of this too, doesn't it? The cost. It makes
the point. It is unfortunate that a generation
of students suffered. while we pursued this approach
that was perhaps fundamentally mismatched to
the task. Yeah, that's a sobering thought. So
wrapping this up, the key takeaway for you listening
is this. According to this source, the big standardized
test didn't just stumble. It potentially failed
because its very premise was flawed. It was built
on that untenable foundation, trying to use a
scientific model designed for tightly controlled
labs and applying it to the messy, complex, wonderful,
rich, and variable world where actual humans
learn. Mm -hmm. And if we sort of connect this
to the bigger picture, really grasping this foundational
issue, it changes how you might think about evaluating
education entirely. It pushes you beyond just
critiquing a test, you know? It makes you question
the whole framework we use to decide what works
in such a complex system like learning. Which
definitely leaves us with a big question to chew
on, doesn't it? If that strict scientific experimental
model, the one described here, really can't be
neatly applied to measure what works in education,
and how do we genuinely understand and foster
better learning in this incredibly rich and variable
world we all live in? Something to think about.
Thanks for joining us for this deep dive.