Hi, Dr. Honora Wall here, welcoming you to the
What in the World is Dyscalculia? podcast. And
this podcast is supported by the educalclearning
.com company, where we have a lot of individual
services and help for people with dyscalculia
and quite a few research articles and information
for you. We also work quite a bit with the Dyscalculia
Training and Research Institute, and that is
a nonprofit based here in the US that works on
a larger scale with schools and school districts
and individuals. If you have any question, email
me at either one of those places. And our podcast
talks about the math learning disability, which
is called So in this episode, I'm actually going
to talk a little bit about research in general,
not necessarily a specific study on dyscalculia,
but I do want to talk a lot about research in
this season. So we're going to start with an
analogy that I think will help. us all understand
some of the limitations of being research -based,
research -informed, just talking about research
in general with other people, be them colleagues
in the education sphere or just other parents
or people who may or may not have had a lot of
exposure to published research. Because we do
want things to be research informed. We want
to know that someone has taken a good idea and
studied it and then they can tell us what they
found. But until you've really done some research
studies, it's hard to know what goes into that
and what you can therefore take from a research
study. Here's my analogy. This is what got me
off on this tangent. I was having a conversation
recently. with a friend and colleague who talked
about a friend and colleague who was using in
their AP psych class a research study that says
people who make their bed every morning make
more money. So this was our conversation. What
it kicked off in my head is first of all talking
to a friend about their friend is your trigger
to go find the original source. you've got to
go back to the actual article, not the referral
from a few steps removed, not the AI generated
lead -in, not the potential clickbait headline.
Go to Google Scholar, keep clicking back through
articles if that's your beginning method, find
the original source material. So that's part
one. And then part two, and I'm not picking on
the study. I want to make that clear. If you
like making your bed, make your bed. If you like
finding anything that will give you an edge to
be more financially successful, find that edge.
Try out different things that could help you
be more financially successful and see what works
for you. If you don't want to make your bed,
don't make your bed. I'm not concerned either
way. I'm really just talking about how we use
research in our conversations and how we use
studies in our conversation and what are some
best practices we really should be following
in that sphere. So the first thing that I thought
was, okay, this sounds like a really great idea.
Quick fix. If you do something simple at the
beginning of every day, it's going to be tied
directly to earning money later. So first I want
to point out a flaw in using that kind of thinking
to interpret studies and research because it's
something that we do quite a bit and just as
people we fall into this trap we all do myself
included and we just have to check ourselves
when it happens so here's the flaw thinking that
one study can be generalized to all situations
and in the same vein, thinking that any studies
determine an absolute cause and effect. That's
not how statistics work. We could say that we
looked into something and we found a statistically
significant difference. All things considered,
we expect to see this happen more often than
that. That's as close as we can come with statistics.
We don't have 100 % return on pretty much anything
except that living things die. That's pretty
much it. Everything else has some little bit
of ends that don't quite meet the middle. And
what we talk about in research studies is the
middle. It does give us the best bang for our
buck in most situations. That's why we use research
studies. And they are very important. but they're
not a direct cause and effect and they're not
always the only cause making an effect. So while
it may be true that people who make their bed
tend to make more money, it's also true that
plenty of people make their bed and don't make
very much money. It's also true that some people
who never make their bed also earn more money.
And then, of course, we have to ask, earn more
money than what? What is our standard? And that's
where our standard deviations come from. Here's
what we expect. Are we going further or behind?
What are we comparing it to? So that's an important
question. When you're looking at any research
study, what is the standard we're comparing against?
What is the change that we're trying to measure?
And then account for the situations where that
change does not make a difference. It also begs
the question, is that the only thing that has
an impact on future earnings? Are there any other
variables besides just making a bed that would
impact future earnings? Does it matter what time
this person made the bed? Could it have been
in the morning? Could it have been at night?
Could it have been every Saturday afternoon?
Does that have any impact? Maybe it's just the
consistency of doing something you don't like
because most people don't like making their bed,
making yourself do that uncomfortable thing early.
So you've broken the seal for the day and are
you then more likely to do more small things
that add up to big results? Are you then more
likely to do things you don't particularly enjoy
because of their perceived benefit? It could
have been any one of those things that were used
as a research question, as that hypothesis. So
we have to look at that as well when we're looking
at research -based practices or researched informed
ideas and getting them into practical strategies,
especially in the classroom. We also want to
be careful about bias. And this is something
that researchers will put in the beginning of
their studies. If they think they have a bias
or any kind of conflict, they state it so you
know upfront. And that could be anything from,
does this person who did the study really particularly
enjoy a clean, nicely made bet? Maybe they had
an inherent bias towards that. Does this person
who wrote the study really enjoy doing things
that feel uncomfortable. Maybe they have an internal
reward system that's tied to that. It also includes
the idea that everyone has a bet, that everyone
has a nice set of sheets, that everyone has the
time in the morning to make that bet. Could those
other environmental and societal factors influence
making more money. So we have to be careful looking
at all those variables and add bias. We also
want to be careful because sometimes things have
a moral bias within society and that can influence
a lot of our research studies. Again, a good
researcher is going to analyze that before they
conduct their study and they're going to put
it out there. So you can go find out. what their
frame of mind was when they started their study.
But here's the the moral implications. It sounds
really good to make your bed every day and your
room looks clean and nice. This is also a really
nice idea for most parents. They like to tell
their kids to go clean their room and make their
bed. So are we using any kind of propaganda throughout
our study or does the study reinforce propaganda
we enjoy? And therefore, we cite the study when
we talk to other people. Maybe yes, maybe no.
But it's a question that needs to be examined
when we're talking about research. Looking at
those different variables, there's another big
piece of research. How many things were tested
in the study? Did it only look at people who
made their bed versus people who did not? Did
they also look at economic background, family
background? levels of education, field that they
worked in, gender, age. I have no idea if any
of those things would necessarily impact lifetime
earnings. I can make my own assumptions and have
my own bias. And then I can go look at other
studies and see how they were conducted and see
what information that yields. So this is a lot
of what we really should be talking about in
our statistics classes. It's also a lot of what
we should be talking about in geometry. We've
got to get a lot of this algebra out of geometry.
Algebra has plenty enough of its own courses.
Algebra 1, Algebra 2, there's a ton of it in
PreCalc and Calc. Now we shove it into middle
and elementary school. Let's leave geometry for
critical thinking, logic statements, and proofs.
If you're going to say something, you had better
be able to justify it with a solid reason. And
those reasons come from very specific small places.
Definitions, postulates, theorems we've already
proven. But I digress. Going back to the idea
of this research study. So once I got onto this
track of how do we talk about research, where
does it come from? Are we really thinking cohesively
about everything that can impact a research study
and using that when we read them and then try
to apply them? The best thing you can do, as
I said in the beginning, is go to the original
source, which I would love to bring you, but
I couldn't find one. I'm sure there probably
is a research study in a peer -reviewed journal
that examines this idea. And if so, if you find
it, please send it to me, hanora, h -o -n -o
-r -a, at eduCalcLearning .com or hanora at thedtri
.org. If I get it, I'm happy to do another episode
where we examine it and talk about it. I couldn't
find it. I found a lot of articles and stories
and a few books and TV shows that talked about
a study that says, but I could not find a link
that went back to the study. I found quite a
few articles on Google Scholar that looked at
different things related to beds, usually involving
a sleep study that talked about how much sleep
a person got at night. whether or not they could
make up that sleep, how that sleep impacted the
way they felt during the days. I found some polls,
which are people's personal opinions, which is
valid in many places of research, especially
qualitative research. But that's different than
quantitative. So I'd like to know, is there a
study? How is it done? Was it qualitative or
quantitative? Was it both? Did they do a mixed
methods? I'm just not sure. But if I can't find
it on Google Scholar, and I can't find it through
other research avenues where I'm going to look
for the article, then I really question. I feel
like then any idea, not just making the bed,
any idea becomes part of our pop culture, part
of our storytelling vernacular. But if none of
us are going back to the original source, then
we have too many interpretations. It's a telephone
game. And we're not really looking at the bias,
the limitations. What was the statistical significance?
Were any other variables included? We're just
left with too many questions and not enough answers.
But that's really annoying and time consuming
and more than what a lot of people want to do.
They want to know a study said this, now I can
trust it and I can use it. But we want to be
really careful with that. Clearly I'm using this
as an analogy because most of us have a bed and
most of us have a preference on whether or not
we make that bed first thing in the morning.
Most of us would appreciate greater financial
lifetime earnings. So I'm using it as an analogy.
But I want you to apply these things to any research
-based program, research -based idea, research
-informed, anything at all. I want you to go
back to the original source, and I want you to
get comfortable reading about the limitations,
reading about the results. Even if you're uncomfortable
with the standard deviation and the p -hat and
the graphs, at least go to the summary. Look
at the methodology. section so you can see who
was included, who was excluded, and how the study
was presented, how it was designed. These are
things that are going to give you proof of concept
and the ability to trust in results, and then
you can analyze it through an application lens
and try things out in your classroom. And if
you're teaching upper -level math and science,
these are some really important questions to
generate in the classroom and get some class
discussion around. Statistics is not just figuring
out standard deviation or the z -score. Any computer
program can do that. Any calculator can do that.
You can do it by hand. It's really not even that
difficult. It's just time consuming. Understanding
what that means and the limitations around it
and the application, that is the really important
part of studying statistics and understanding
research. In geometry class, I want you to spend
a lot more time on logic statements and proofs
because having reasons that justify your statement,
that is the most important thing that we learn
in geometry because it changes the way you think
and it develops those critical thinking skills
that make us better at analyzing our world and
the information that we get. Big part of data
science too, understanding the information we're
given and questioning the information against
reliable methods. So that's the lens we're going
to use. Throughout this season, we are going
to do a lot more analysis of research studies
around dyscalculia and the DTRI is looking to
embark on a couple of exciting ones. So hopefully
we'll be adding to the knowledge base of published
research around the math learning disability.
And we are working on getting more of these posted
on the website so that you can go read the original
source material yourself. Don't take my word
for it either. Verify everything that anyone
tells you about dyscalculia, especially, but
in general, trust and verify. All right. I am
Dr. Hanora Wall. I'm really glad that you joined
us for this episode of what in the world is dyscalculia.
And if you have any questions, comments, or ideas
for future podcasts, or if you want to send me
the research study. tying making your bed to
future lifetime earnings, please send me an email.
I'm happy to hear your comments. Have a great
day.