Dive headfirst into the enlightening world of educational data with our special guest, Dr. Emily Davis! She's here to shatter the myth that data is just a series of intimidating numbers, revealing how it can become a teaching superpower. Together, we navigate through the nuances of quantitative and qualitative data, unlocking the stories and patterns that can transform your teaching methods and boost student outcomes.
Our journey with Emily takes us through the intricacies of educational data, examining how it can be a supportive ally rather than an overwhelming foe. We discuss the magic of self-reflection through video, the clarity that comes with goal setting, and the beauty of data in tailoring teaching strategies. These revelations pave the way for you to embrace data with confidence, ensuring that every student's learning experience is as effective and engaging as possible.
As the curtain falls on our captivating chat, we celebrate the joy of connecting with fellow data enthusiasts. Emily also spotlights the fantastic work of Teacher Development Network LLC in nurturing early career teachers. We wrap up, inviting you to continue your journey toward educational minimalism with us, Tammy and Christine, while the melodious tunes of Gaia Moretti play us out. Don't miss the chance to be part of this empowering narrative in our next episodes of the Minimalist Educator Podcast.
Dr. Davis is the founder of Teacher Development Network LLC, whose mission is to support educational organizations in developing and enhancing induction and mentoring programs for early career teachers. Dr. Davis is a sought-after consultant and professional developer on topics including mentoring, facilitation, and professional learning and is the author of numerous articles and blogs on those topics. She was also named an emerging leader in the field of education by Phi Delta Kappan and ASCD and was recently selected to be a Fulbright Specialist.
Website: www.teacherdevelopmentnetwork.com
LinkedIn: www.linkedin.com/in/dremilyldavis
This episode is sponsored by Teacher Development Network.
Collaborating to Create Customized Systems of Support for Early Career Teachers
Buy The Minimalist Teacher book from ASCD+ISTE.
Follow on Instagram @PlanZEducation and @minimalist_ed_podcast.
The Minimalist Educator Podcast is a Plan Z Education Services adventure.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:18):
Welcome to the Minimalist Educator Podcast, a
podcast about pairing down torefocus on the purpose and
priorities in our roles withco-hosts and co-authors of the
Minimalist Teacher Book, TammyMusiowsky-Borniman and Christine
Arnold.
Speaker 2 (00:35):
Today, emily speaks with us about all things data.
Far from something daunting,data can be utilized by teachers
to enhance all aspects of ourpractice.
Dr Emily Davis is the founderof Teacher Development Network
LLC, whose mission is to supporteducational organizations in
developing and enhancinginduction and mentoring programs
(00:56):
for early career teachers.
Dr Davis is a sought-afterconsultant and professional
developer on topics includingmentoring, facilitation and
professional learning, and isthe author of numerous articles
and blogs on those topics.
She was also named an emergingleader in the field of education
by Phi Delta, kappan and ASCDand was recently selected to be
(01:18):
a full, bright specialist.
Speaker 3 (01:21):
Hello everyone and welcome to today's episode of
the Minimalist Educator Podcast.
Today we are looking forward tohaving conversation with Dr
Emily Davis.
Speaker 4 (01:33):
Welcome, emily.
Hi Tammy, thanks so much forthe invitation.
I'm so excited to be here.
Speaker 3 (01:38):
We are excited to have you.
And how are you today,Christine?
I am doing well.
Speaker 2 (01:44):
How about the both of you?
Speaker 3 (01:45):
All good, here the birds are chirping.
Speaker 4 (01:49):
A little gray and rainy here in Pennsylvania, but
it's all right, it's holidayseason time.
Speaker 3 (01:54):
Awesome.
So I'm excited to talk to youtoday, emily, about one of your
specialty areas.
I mean, you are a master coachand mentor, but I remember a
session that you put on for ouremerging leader alumni affiliate
in the summer and it made methink about data slightly
(02:16):
different data and feedback, andso I'm excited to talk to you
about that today, which is funnybecause data can be a scary
word to teachers or a boringword to people who don't like
information, but the way youapproach data, it feels
(02:36):
different, it feels comfortableand easy to use.
So can you talk a little bitmaybe first about how you became
so interested in datacollection and using it in your
work?
Yeah, sure?
Speaker 4 (02:48):
Well, I'm so glad that's the way you feel about it
.
I mean, I think you write a lotof teachers dear data and it's
like this scary four-letter word, right, Like that we don't want
to spend time talking about inour work.
I think I've become a data geekI don't think I started out
that way, but I think that Ihave found that it is so
(03:09):
powerful in our work that wehave to spend time with it,
right, we have to really get inthere with it.
It's the one thing that we canlook at and play around in and
understand.
That really helps us to make adifference in our classrooms,
right?
So we have to figure out how tomake it our superpower instead
of the scary thing.
(03:30):
So I think that's where itstarted.
It started in my own work as aclassroom teacher and definitely
has become much more clear justhow important it is in my work
as a coach these days.
Speaker 3 (03:41):
When you mention lay around us data, can you talk a
little bit about?
Speaker 4 (03:46):
that, yeah, absolutely.
I mean okay.
So let's, let's start with some, some misconceptions, because I
feel like a lot of folks thinkabout data and they have all
these scary thoughts because Iknow I have them as well right,
like, oh, it's all numbers and Ihate math.
I'm bad at math, I'm not a mathperson, so I can't be a data
person.
I am not a math person eitherby training, you know, I learned
(04:10):
to be a math person through mywork and my doctoral program,
but it, it, it is.
It is a scary thing, I think,when people think about it that
way.
So it is not all math.
So I just want to say that, andit's not all numbers.
I think other people think, oh,it's too complicated, I I don't
know how to look at it, I don'tknow how to like do something
with it, so kind of throw up myhands because that's something
(04:30):
that, like people with you know,accounting degrees do not
something that I do, right?
I think some people go Well, itjust takes too long, like it
takes too long to look at.
I already know my kids.
Why should I spend time lookingat the data?
It's not gonna tell me anythingthat I don't already know,
right, but I think that's wherea lot of people go.
So I think the first thing thatit's helpful to think about
(04:52):
when we think about data is thatyou know it's anything that you
can collect that helps you tosee and understand emerging
patterns, and something that youcan do something with right.
So, yeah, sometimes it'snumbers and honestly, I love
quantitative data because itoften points us at something
right.
It tells us that there'ssomething going on there that's
(05:12):
worth our curiosity and our timeto look at a little more
closely.
But a lot of times it's other,more quantitative stuff like
engagement, pattern analysis orpacing or the types of questions
that get asked and answered inthe question, or that
interesting look at studentwriting or error analysis and
math, right.
It's all of these other thingsthat get our curiosity up and
(05:36):
help us to understand patternsthat are emerging when we have
an understanding about patternsand we can do something about
that, right.
So I think it's just importantto kind of like start there and
think about what it actually is,because I think once we unpack
that a little bit, it's a wholelot less scary, right, and then
it is something to play aroundin, right, we can look at those
(05:56):
pieces that we've pulled up likea puzzle.
I love puzzles, right, and thepuzzle pieces.
Once we start to put themtogether to help us to
understand more about what'sactually Happening in that speak
right.
And then again, that createsefficacy for us as teachers,
right?
If I know what's happening andI know where it's happening and
I know why it's happening, thenI can do something different
with that, right?
(06:17):
Yeah, I think also, I mean foreducators, data is super
important for a lot of otherreasons.
I mean we all know.
I mean, when I was a graduatestudent, our motto was know thy
students, right?
So data is one of those waysthat you do that.
You have to know your studentsto teach them that data.
What do you?
How do you know your gut?
I mean, that is an inherentlyunreliable way to do that.
(06:39):
We know.
I mean all the brain sciencewe've been looking at lately.
It tells us that our brains arepretty lazy.
They take shortcuts to savespace and so we make judgments
and then we continue to look fordata that confirms those
judgments.
That's confirmation bias, right?
So data pushes us to really look, to look at where kids are
right now, and we all know thekids change and they grow.
(07:01):
They're not always the same.
Some stuff is harder for themat some points and easier than
for them at other points, right.
And if we're just working fromthat unreliable guts base, we
tend to just keep doing the samething for students all of the
time, right?
John Hattie says that teacherestimates about student
achievement are the third mostinfluential on student outcomes.
(07:22):
So if we got it wrong, we'rereally doing students a major
disservice, right?
That gut, I think post COVID aswell.
When we're trying to figure outhow to help all the kids get
back up to speed Instructionallyand socially, data is the best
tool that we have, right tofigure out how to help make sure
they're always kind of workingin that zone Approximal
(07:42):
development or the only onesthat can do that, for the only
ones that can shape theinstruction in our classroom.
So if we're not actively usingdata to help us make better
choices, our kids are missingout.
Speaker 2 (07:51):
Right, yeah, for sure .
Before I ask this question, I'mgoing to add myself as also a
data geek as well.
I love the data.
Yeah, I just love thespreadsheets.
I love all of that.
But what would you say topeople who would come across the
argument of you know whenpeople?
This is a human enterprise thatwe're in, and it's not always
(08:15):
so easy to to quantify Humans inthat way or or measure humans
in that way.
What would you say to peoplewho are coming from that point
of view?
Speaker 4 (08:26):
I love that question.
That's a great question andbecause I work in coaching world
and my work is about people,right, I think the best kinds of
coaching is and we can talkmore about this is when really
smart people sit together andthink through things together.
That's why I got into coachingwork, is why I didn't become a
school leader or something elseI figured out.
When really smart people sitnext to each other, great things
(08:47):
can happen.
So when we think about datalike only as like a quantifiable
thing right, we do do that.
Like I said, I think sometimesthe numbers they point us at
something, right.
So when we look at standardizedtest scores or when we look at
benchmark assessment data, orthat you know exit ticket at the
end of your math class, thatthose numbers, like the six out
(09:11):
of 12 or whatever, do tell ussomething, but they don't give
us the whole story, right.
I think as educators, we haveto thoughtfully triangulate
across several sets of data toreally get at what's happening
here.
So that's one piece of data,it's a snapshot, it's a moment
in time and hopefully you get tohear curiosity and you begin to
(09:32):
ask questions like why is thatthe way it is?
What else do I know about thesituation?
What is happening here?
What factors might have causedthat to happen?
What else do I know about thisperson that might have led to
this thing today?
Right, and all of that stuff isqualitative stuff.
Right, it's deep, rich, thick,descriptive stuff that helps us
(09:53):
to kind of round out and informour work.
Right, it tells the storybehind those numbers and that
data, and for me, I mean I heck,I wrote a 400 page qualitative
dissertation, so I mean that isthe data that I love the most
and I'm happy for that data, andI think that's the data that
most educators are drawn to aswell.
Right, the stories about whythings are the way they are,
(10:15):
what's happening with kids weget into this because we love
kids and people.
Right, and that work.
So, yes, I think that is reallyimportant data.
So I don't want people to heardata and only think numbers.
I think that's just a verysmall part of this much bigger
story and we struggle ineducation with this.
Right, that's the only metricswe tend to want to like, look at
(10:36):
and publish, but I think allthese other metrics are the
places where we really get toget down in the work and figure
out what's going on and makechange.
Speaker 3 (10:46):
And I mean I love observing, right, it's fun to go
into a classroom and just likewatch the kids and you know
their interactions and listen towhat they say.
And it's hard to capture all ofthose things unless you're like
recording everything or likereally good at jotting notes and
things like that.
But I do get my phone out atschool a lot because I want to
(11:07):
capture some things that kidsare doing or things that they're
they're saying.
So I do record a lot of that.
And that data collectionprocess can be pretty
overwhelming, right, Becausethere's there's so much
happening all the time and youwant to capture as much as
possible.
And then because you know youhave to report that to parents
and you're writing up studentreports for to show their growth
(11:31):
over time or lack of growth.
So how do you work with yourteachers to kind of pick the
best data to use, maybe becausethere can be so much collected?
So how do you kind of reducethat overwhelm or help teachers
work through the overwhelm of somuch information?
Speaker 4 (11:50):
Yeah, that's a great question.
I think our goal is to avoidbeing data rich and information
poor, right?
So being really clear aboutwhat you're looking for and what
you want to spend time on isalways where we start when I'm
doing coaching work withteachers, right?
So we're going to ask thequestion like what's our goal,
like what's the thing that wewant to know more about, and
(12:11):
then let's just spend some timereally zeroing in on that thing,
put that set of glasses on thatlens on the space, right, and
see if we can kind of tune outsome other data at this point in
time.
So when I go to observe that'swhat we do, right we're going to
say we're super curious abouthow kids are interacting when
they work in small groups today.
So obviously, I'm not a machineand I'm not a camera, though
(12:33):
video is a phenomenal datacollection tool and I always
highly recommend it.
Even if you don't have a coachwith you, you can always record
your own class and watch it back.
Once you get past the liketerribleness of seeing and
hearing your own cell phone film, you learn so much about what's
happening in your classroom,right, even without anybody else
there to help you.
But if it's me and I'm able togo in and get to sit in with
(12:54):
kids.
Even then, we know we can't seeand hear everything, right.
So we'll work together.
Is there a group of kids thatwe have lots of questions about?
Maybe I'm only going to sitwith that group of kids and
gather some data today.
Right, it's a snapshot.
It's a small sample, smallscale sample of what's happening
in the class as a whole, but itmight tell us, it might
(13:15):
illuminate some patterns for us,right?
Or help us to unpack a littlebit more, to triangulate with
some other data that we'vealready got right About what's
happening in that space.
Or I might sit with one kidright For a while who we have a
lot of questions about.
Or I might sit back and justsee what we can notice about
broader patterns, because we'retrying to figure out what's
happening, you know.
So I think, like scale and lenshelps us to know, but we have to
(13:39):
base it on something likewhat's our goal, right?
What's the thing we want toknow more about?
I think expert teachers do this, naturally, right.
I'm taught middle school artfor 40 years and every year she
would call me and say, like thisis the year that I'm going to
work on this thing in mypractice, right, and then when I
run out of stuff to worry about, then I'll probably be ready
for me to stop teaching.
So I think this is what we do.
(14:00):
So when we worry about our, whenwe come up with our own goals,
when we think about our owngoals, we think about what data
we might collect that will helpus to get closer to answering
those questions or meeting ourgoals.
That's efficacy for us asteachers also, right, we're also
teaching our kids a reallyimportant skill, right, but we
want kids to be able to beinformed practitioners as well,
(14:23):
right, informed about their ownwork.
So when we do this work forourselves and we teach kids how
to do the same work forthemselves, to look at their own
assessment data or whateverdata they have about their work
and make some decisions aboutwhat it means and figure out how
to grow their their selves,they have efficacy as well, and
we know that that makes a hugedifference.
So, again, I think I thinkabout this work like a coach,
(14:45):
right?
So the stuff that I do withteachers is the stuff that I
hope they're doing with theirkids, right, all of this is best
practice work at any level.
Speaker 2 (14:54):
Yeah, I was going to ask that about any strategies or
thoughts on how to share thedata with our students, but also
with the parents as well.
What are some really good waysthat we can provide that
measurement for parents in a waythat's helpful and
understandable for them?
Speaker 4 (15:12):
Yeah, great question.
A lot of schools are moving tolike student run conferences at
this point and I think that's areally great strategy,
especially if they're wellorganized and well set up.
So I taught middle schoolhumanities before I became a
coach, and so for me, mystudents used to do things like
keep portfolios of their workright, of the work, their
(15:35):
writing work that they weredoing or other work that they
were doing in class.
Over time they always bring afew things to fruition, but they
had all the other stuff thatthey had been making and writing
and doing, and so when we getto parent-teacher conferences,
it gave them an opportunity tolike pull a few things and to be
able to talk about their growthand progress.
Right, to be able to say, likethis is where I was at the
(15:56):
beginning of the quarter.
Right, and these are the thingsthat I realized, you know, when
we looked at my writing that Ireally needed to work on and
spend time on.
So these are been my goals overthe course of the quarter, and
now this is the last piece ofwriting that I've done and you
can kind of see evidence of howI've been growing in my work.
Right, and these are the thingsthat I did that helped me to
(16:17):
get from point A to point B.
And then I think that abilityto kind of be metacognitive
about your own work at a youngage really sets you up for
success.
As a parent now sitting on theother side of the table, when I
get to hear my kids talk abouttheir work in that way, that's
also incredibly powerful, right,because they are owning their
learning.
It's not about whether they gotan A in English class or math
(16:40):
class or science class.
Do they understand thattransferable skill of how to
learn?
And I think data is a huge partof that.
Can I?
Am I data literate?
Can I look at the feedback thatI've been given or the
information that I haveavailable to me?
Can I understand it and unpackit?
Can I make a plan about how todo something different as a
(17:01):
result of that feedback?
As a lifelong skill?
And we know that people need itat any field, right, and I
think that that transcends theindividual class and I think
teachers and kids and parentswill really appreciate that
Everything that you're saying isvery magical, because I'm a
proponent of a person who's likewe must teach skills, right,
(17:24):
like the content is somewhatirrelevant.
Speaker 3 (17:28):
They need, students need and we need skills to that
transfer across whatever we'redoing.
So looking at data andanalyzing it, talking about it,
sharing it is one of thoseskills.
So how do we collectively, Iguess, break through some of
(17:49):
those barriers of thinking aboutI don't have time to show my
kids too much, I write thefeedback on their paper, or you
know, I have a quick conferenceand then that's it.
Like we don't do anything elsewith the data I've given to them
because they don't have time.
There's like all this contentto teach.
So how do you work through that?
Because we know that, likethese are essential skills.
Speaker 4 (18:12):
Yeah, great question, I think, for teachers.
We have to realize that this isabout.
This is a working, smarter, notharder, activity, right, taking
a few minutes to look at datain a reasonable way, and it
really doesn't have to take thatmuch time.
I mean, you can do something assimple as make a like a little
three column chart.
When you look at an exit ticketright, kids names on the left,
(18:35):
like areas of strength in themiddle, misconceptions or areas
for growth on the right put yourgoals and success criteria at
the top, like what are youlooking for?
And just as you're gradingthose exit tickets, just write
like a couple of bullets foreach kid right.
And then when you get to theend, you can just take a look at
that and say, like whatpatterns have emerged?
(18:56):
What do I see about my kids as awhole, as subgroup of kids, as
individuals?
What am I missing in this data?
Right?
Like I don't know about you.
Like when I look at data, italways more curiosity comes up.
I have new and more questions.
I think that's like terriblecycle of data, right?
So how do I build on that?
Like?
What do I do tomorrow?
That's going to make sure I'mmuch more likely to hit kids
(19:17):
where they need me to be thanjust planning broadly, right.
I could spend myself in circlesplanning generic lessons for a
whole year, right.
So I can plan a whole lot morewisely.
If I spend a couple of minuteslooking at that data and making
a decision about what I'm goingto alter tomorrow.
That's more likely to get kidswhere they are today and what
(19:39):
they actually need.
So I would start there.
I mean that is being an informedpractitioner, right.
The data helps us to betteranticipate the outcomes of our
actions and increase thelikelihood that students are
going to succeed.
That's what it does, right.
If you're a coach, I mean yougot to.
I can't do my work as a coachwithout data about the teacher,
(20:02):
about the kids, about thecontent, about the classroom,
about the environment as a whole.
So model this in your work.
If you're a coach, right.
Support teachers in buildingthose habits by doing it with
them.
Right.
Working around data when you'rea coach does so many good things
for you.
It builds ownership, it buildsrelevance, it builds autonomy,
(20:24):
it builds immediate application.
All of those are things that weknow adult learners really,
really need.
It builds trust, right, thisthoughtful, transparent use of
data and it also keeps you fromhaving to have the feedback
conversation that like, let metell you about what I saw and
what I think happened here, whatmy opinion of it is.
I love it at you across thefence and hope you do something
(20:47):
with it, and instead it helps usmove to a coaching conversation
, right?
The data becomes a third pointthat the two of us can sit next
to each other together and lookat and say what does this mean?
What might we do as a result ofwhat we're seeing here?
How can I help you?
What would you want to do?
(21:08):
What could you imagine doingnext that could help you be even
better tomorrow for these kids,now that you've seen this data?
That's a totally different kindof conversation and that's what
I think you were alluding toearlier, tammy, when we were
talking about this differencebetween feedback and coaching
and why I think this is so very,very important.
It is central, the success of acoaching relationship in that
(21:29):
way, like I said, it does allthose other good things right.
Each teacher's had to do thiswork and helps teachers figure
out how to help kids do thiswork, and I think that's a game
changer for our system as awhole.
If we're ready to go there anddo it.
It's way more simple too, right, and a lot of the other things
that we see.
So if for a minimalist educatorpodcast, I think this is a
perfect topic.
Speaker 2 (21:48):
I hope this question is not going to be too
controversial.
I know we're risking going overtime as well, but I am so
curious as this thoughts allabout data and like effectively
using data for our students andfor our own practice.
What is your opinion aboutgrades, about this practice that
we have in schools of assigninggrades?
(22:11):
What are your thoughts on that?
Speaker 4 (22:15):
Yeah, grades are hard right.
Like again, grades are a datapoint, but in absence of clear
criteria for their provision,they don't really mean anything,
right?
So if a grade was accompaniedby a clear set of a clear rubric
, clear matrix, clear set ofcriteria and we see this
(22:37):
happening in some places thismastery grading strategy that's
coming online, it makes moresense, right?
I think parents kind of needyour reaction as well.
I understand a grade An A meansthat they did great and an F
means that they did bad but wedon't really know what that
means.
We don't know any of thetransferable skills that went
behind that.
We can't understand any of thenew learning that actually took
(23:00):
place in that space.
We also know I mean, I work inuniversity settings we also know
that A in one place and an A inanother place are not
necessarily synonymous, right?
So they don't do much, honestly, in terms of conveying solid
information for us at thisparticular point in time.
So, yeah, I guess I would sayI'm a proponent of mastery
(23:22):
grading.
After having this conversationwith you, christine, I think
it's much more helpful, but it'sa lot harder for teachers.
We have to learn how to do allthese other things that we've
been talking about.
It has to be built into thearchitecture of our work from
the beginning.
We can't kind of randomlyassign mastery learning grades
at the end.
It has to be in all the timebeauty of work.
(23:42):
But maybe that's not the worstthing in the world, right?
It helps us to actually seekids and the way that we've been
talking about today and that'svery powerful and help kids see
themselves in the way that wehope that we're talking about
today, so that they haveownership and efficacy in this
work as well.
Speaker 3 (23:58):
Yeah, absolutely.
Thank you for answering whatcan be a controversial question.
So thank you.
And it's at this point I mean Ilove talk.
Yes, ok, third data geek in thegroup yes, yes, we come
together and start talking aboutthese things, and we could go
on and on, but we're at thepoint in the show because we
(24:20):
want to stay true to ourminimalism principles, like keep
it short and bite-size forpeople.
We ask our guests for aparedown pointer at the end of
the show, and that might besomething you mentioned in the
show.
It could be something that youdo personally as a coach.
Anything, just a quick tip thatyou want to share as we wrap up
the show.
Speaker 4 (24:41):
Yeah, I think I would probably say that quick data
analysis tool that we weretalking about, that little
protocol, is probably the tipthat I would offer most.
Before you sit down to look atanything that students have put
forward, just think what are myexpectations for success here?
What am I looking for?
And then make a little chart ofyour kid.
What can they do inrelationship to your goals?
(25:02):
What would be the next step forthem?
Where is their misconception?
And then just look at that.
What can you gather from that?
What are your trends?
What patterns do you see?
What does everybody need?
What do some folks need?
What does this one kid need?
What am I going to do aboutthat tomorrow?
I might add one more questionis how did looking at this data
impact my thinking?
We talked about lazy brainbefore, so what biases got
(25:27):
debunked when I looked at thisdata today, and how's that going
to impact the way I work withand look at that kid or that
group of kids tomorrow?
Speaker 3 (25:36):
Yeah, Excellent.
Thank you, Emily.
So much for today's episode andconversation.
It was a happy place to talkabout data.
Thanks, Emily.
Speaker 4 (25:47):
Thank you both so much.
What a pleasure to talk withyou.
Have fun.
Data geeks of the world.
Data geeks tonight.
Speaker 2 (25:54):
Today's episode was brought to you by Teacher
Development Network LLC,collaborating to create
customized systems of supportfor early career teachers.
Find out more atteacherdevelopmentnetworkcom.
Speaker 1 (26:08):
Be sure to join Tammy and Christine and guests for
more episodes of the MinimalistEducator Podcast.
They would love to hear aboutyour journey with minimalism.
Connect with them at PlanZPLSon Twitter or Instagram.
The music for the podcast hasbeen written and performed by
Gaia Moretti уляzos during조금omer days.
Welcome to the Minimalist Educator Podcast, a
podcast about pairing down torefocus on the purpose and
priorities in our roles withco-hosts and co-authors of the
Minimalist Teacher Book, TammyMusiowsky-Borniman and Christine
Arnold.
Speaker 2 (00:35):
Today, emily speaks with us about all things data.
Far from something daunting,data can be utilized by teachers
to enhance all aspects of ourpractice.
Dr Emily Davis is the founderof Teacher Development Network
LLC, whose mission is to supporteducational organizations in
developing and enhancinginduction and mentoring programs
(00:56):
for early career teachers.
Dr Davis is a sought-afterconsultant and professional
developer on topics includingmentoring, facilitation and
professional learning, and isthe author of numerous articles
and blogs on those topics.
She was also named an emergingleader in the field of education
by Phi Delta, kappan and ASCDand was recently selected to be
(01:18):
a full, bright specialist.
Speaker 3 (01:21):
Hello everyone and welcome to today's episode of
the Minimalist Educator Podcast.
Today we are looking forward tohaving conversation with Dr
Emily Davis.
Speaker 4 (01:33):
Welcome, emily.
Hi Tammy, thanks so much forthe invitation.
I'm so excited to be here.
Speaker 3 (01:38):
We are excited to have you.
And how are you today,Christine?
I am doing well.
Speaker 2 (01:44):
How about the both of you?
Speaker 3 (01:45):
All good, here the birds are chirping.
Speaker 4 (01:49):
A little gray and rainy here in Pennsylvania, but
it's all right, it's holidayseason time.
Speaker 3 (01:54):
Awesome.
So I'm excited to talk to youtoday, emily, about one of your
specialty areas.
I mean, you are a master coachand mentor, but I remember a
session that you put on for ouremerging leader alumni affiliate
in the summer and it made methink about data slightly
(02:16):
different data and feedback, andso I'm excited to talk to you
about that today, which is funnybecause data can be a scary
word to teachers or a boringword to people who don't like
information, but the way youapproach data, it feels
(02:36):
different, it feels comfortableand easy to use.
So can you talk a little bitmaybe first about how you became
so interested in datacollection and using it in your
work?
Yeah, sure?
Speaker 4 (02:48):
Well, I'm so glad that's the way you feel about it
.
I mean, I think you write a lotof teachers dear data and it's
like this scary four-letter word, right, Like that we don't want
to spend time talking about inour work.
I think I've become a data geekI don't think I started out
that way, but I think that Ihave found that it is so
(03:09):
powerful in our work that wehave to spend time with it,
right, we have to really get inthere with it.
It's the one thing that we canlook at and play around in and
understand.
That really helps us to make adifference in our classrooms,
right?
So we have to figure out how tomake it our superpower instead
of the scary thing.
(03:30):
So I think that's where itstarted.
It started in my own work as aclassroom teacher and definitely
has become much more clear justhow important it is in my work
as a coach these days.
Speaker 3 (03:41):
When you mention lay around us data, can you talk a
little bit about?
Speaker 4 (03:46):
that, yeah, absolutely.
I mean okay.
So let's, let's start with some, some misconceptions, because I
feel like a lot of folks thinkabout data and they have all
these scary thoughts because Iknow I have them as well right,
like, oh, it's all numbers and Ihate math.
I'm bad at math, I'm not a mathperson, so I can't be a data
person.
I am not a math person eitherby training, you know, I learned
(04:10):
to be a math person through mywork and my doctoral program,
but it, it, it is.
It is a scary thing, I think,when people think about it that
way.
So it is not all math.
So I just want to say that, andit's not all numbers.
I think other people think, oh,it's too complicated, I I don't
know how to look at it, I don'tknow how to like do something
with it, so kind of throw up myhands because that's something
(04:30):
that, like people with you know,accounting degrees do not
something that I do, right?
I think some people go Well, itjust takes too long, like it
takes too long to look at.
I already know my kids.
Why should I spend time lookingat the data?
It's not gonna tell me anythingthat I don't already know,
right, but I think that's wherea lot of people go.
So I think the first thing thatit's helpful to think about
(04:52):
when we think about data is thatyou know it's anything that you
can collect that helps you tosee and understand emerging
patterns, and something that youcan do something with right.
So, yeah, sometimes it'snumbers and honestly, I love
quantitative data because itoften points us at something
right.
It tells us that there'ssomething going on there that's
(05:12):
worth our curiosity and our timeto look at a little more
closely.
But a lot of times it's other,more quantitative stuff like
engagement, pattern analysis orpacing or the types of questions
that get asked and answered inthe question, or that
interesting look at studentwriting or error analysis and
math, right.
It's all of these other thingsthat get our curiosity up and
(05:36):
help us to understand patternsthat are emerging when we have
an understanding about patternsand we can do something about
that, right.
So I think it's just importantto kind of like start there and
think about what it actually is,because I think once we unpack
that a little bit, it's a wholelot less scary, right, and then
it is something to play aroundin, right, we can look at those
(05:56):
pieces that we've pulled up likea puzzle.
I love puzzles, right, and thepuzzle pieces.
Once we start to put themtogether to help us to
understand more about what'sactually Happening in that speak
right.
And then again, that createsefficacy for us as teachers,
right?
If I know what's happening andI know where it's happening and
I know why it's happening, thenI can do something different
with that, right?
(06:17):
Yeah, I think also, I mean foreducators, data is super
important for a lot of otherreasons.
I mean we all know.
I mean, when I was a graduatestudent, our motto was know thy
students, right?
So data is one of those waysthat you do that.
You have to know your studentsto teach them that data.
What do you?
How do you know your gut?
I mean, that is an inherentlyunreliable way to do that.
(06:39):
We know.
I mean all the brain sciencewe've been looking at lately.
It tells us that our brains arepretty lazy.
They take shortcuts to savespace and so we make judgments
and then we continue to look fordata that confirms those
judgments.
That's confirmation bias, right?
So data pushes us to really look, to look at where kids are
right now, and we all know thekids change and they grow.
(07:01):
They're not always the same.
Some stuff is harder for themat some points and easier than
for them at other points, right.
And if we're just working fromthat unreliable guts base, we
tend to just keep doing the samething for students all of the
time, right?
John Hattie says that teacherestimates about student
achievement are the third mostinfluential on student outcomes.
(07:22):
So if we got it wrong, we'rereally doing students a major
disservice, right?
That gut, I think post COVID aswell.
When we're trying to figure outhow to help all the kids get
back up to speed Instructionallyand socially, data is the best
tool that we have, right tofigure out how to help make sure
they're always kind of workingin that zone Approximal
(07:42):
development or the only onesthat can do that, for the only
ones that can shape theinstruction in our classroom.
So if we're not actively usingdata to help us make better
choices, our kids are missingout.
Speaker 2 (07:51):
Right, yeah, for sure .
Before I ask this question, I'mgoing to add myself as also a
data geek as well.
I love the data.
Yeah, I just love thespreadsheets.
I love all of that.
But what would you say topeople who would come across the
argument of you know whenpeople?
This is a human enterprise thatwe're in, and it's not always
(08:15):
so easy to to quantify Humans inthat way or or measure humans
in that way.
What would you say to peoplewho are coming from that point
of view?
Speaker 4 (08:26):
I love that question.
That's a great question andbecause I work in coaching world
and my work is about people,right, I think the best kinds of
coaching is and we can talkmore about this is when really
smart people sit together andthink through things together.
That's why I got into coachingwork, is why I didn't become a
school leader or something elseI figured out.
When really smart people sitnext to each other, great things
(08:47):
can happen.
So when we think about datalike only as like a quantifiable
thing right, we do do that.
Like I said, I think sometimesthe numbers they point us at
something, right.
So when we look at standardizedtest scores or when we look at
benchmark assessment data, orthat you know exit ticket at the
end of your math class, thatthose numbers, like the six out
(09:11):
of 12 or whatever, do tell ussomething, but they don't give
us the whole story, right.
I think as educators, we haveto thoughtfully triangulate
across several sets of data toreally get at what's happening
here.
So that's one piece of data,it's a snapshot, it's a moment
in time and hopefully you get tohear curiosity and you begin to
(09:32):
ask questions like why is thatthe way it is?
What else do I know about thesituation?
What is happening here?
What factors might have causedthat to happen?
What else do I know about thisperson that might have led to
this thing today?
Right, and all of that stuff isqualitative stuff.
Right, it's deep, rich, thick,descriptive stuff that helps us
(09:53):
to kind of round out and informour work.
Right, it tells the storybehind those numbers and that
data, and for me, I mean I heck,I wrote a 400 page qualitative
dissertation, so I mean that isthe data that I love the most
and I'm happy for that data, andI think that's the data that
most educators are drawn to aswell.
Right, the stories about whythings are the way they are,
(10:15):
what's happening with kids weget into this because we love
kids and people.
Right, and that work.
So, yes, I think that is reallyimportant data.
So I don't want people to heardata and only think numbers.
I think that's just a verysmall part of this much bigger
story and we struggle ineducation with this.
Right, that's the only metricswe tend to want to like, look at
(10:36):
and publish, but I think allthese other metrics are the
places where we really get toget down in the work and figure
out what's going on and makechange.
Speaker 3 (10:46):
And I mean I love observing, right, it's fun to go
into a classroom and just likewatch the kids and you know
their interactions and listen towhat they say.
And it's hard to capture all ofthose things unless you're like
recording everything or likereally good at jotting notes and
things like that.
But I do get my phone out atschool a lot because I want to
(11:07):
capture some things that kidsare doing or things that they're
they're saying.
So I do record a lot of that.
And that data collectionprocess can be pretty
overwhelming, right, Becausethere's there's so much
happening all the time and youwant to capture as much as
possible.
And then because you know youhave to report that to parents
and you're writing up studentreports for to show their growth
(11:31):
over time or lack of growth.
So how do you work with yourteachers to kind of pick the
best data to use, maybe becausethere can be so much collected?
So how do you kind of reducethat overwhelm or help teachers
work through the overwhelm of somuch information?
Speaker 4 (11:50):
Yeah, that's a great question.
I think our goal is to avoidbeing data rich and information
poor, right?
So being really clear aboutwhat you're looking for and what
you want to spend time on isalways where we start when I'm
doing coaching work withteachers, right?
So we're going to ask thequestion like what's our goal,
like what's the thing that wewant to know more about, and
(12:11):
then let's just spend some timereally zeroing in on that thing,
put that set of glasses on thatlens on the space, right, and
see if we can kind of tune outsome other data at this point in
time.
So when I go to observe that'swhat we do, right we're going to
say we're super curious abouthow kids are interacting when
they work in small groups today.
So obviously, I'm not a machineand I'm not a camera, though
(12:33):
video is a phenomenal datacollection tool and I always
highly recommend it.
Even if you don't have a coachwith you, you can always record
your own class and watch it back.
Once you get past the liketerribleness of seeing and
hearing your own cell phone film, you learn so much about what's
happening in your classroom,right, even without anybody else
there to help you.
But if it's me and I'm able togo in and get to sit in with
(12:54):
kids.
Even then, we know we can't seeand hear everything, right.
So we'll work together.
Is there a group of kids thatwe have lots of questions about?
Maybe I'm only going to sitwith that group of kids and
gather some data today.
Right, it's a snapshot.
It's a small sample, smallscale sample of what's happening
in the class as a whole, but itmight tell us, it might
(13:15):
illuminate some patterns for us,right?
Or help us to unpack a littlebit more, to triangulate with
some other data that we'vealready got right About what's
happening in that space.
Or I might sit with one kidright For a while who we have a
lot of questions about.
Or I might sit back and justsee what we can notice about
broader patterns, because we'retrying to figure out what's
happening, you know.
So I think, like scale and lenshelps us to know, but we have to
(13:39):
base it on something likewhat's our goal, right?
What's the thing we want toknow more about?
I think expert teachers do this, naturally, right.
I'm taught middle school artfor 40 years and every year she
would call me and say, like thisis the year that I'm going to
work on this thing in mypractice, right, and then when I
run out of stuff to worry about, then I'll probably be ready
for me to stop teaching.
So I think this is what we do.
(14:00):
So when we worry about our, whenwe come up with our own goals,
when we think about our owngoals, we think about what data
we might collect that will helpus to get closer to answering
those questions or meeting ourgoals.
That's efficacy for us asteachers also, right, we're also
teaching our kids a reallyimportant skill, right, but we
want kids to be able to beinformed practitioners as well,
(14:23):
right, informed about their ownwork.
So when we do this work forourselves and we teach kids how
to do the same work forthemselves, to look at their own
assessment data or whateverdata they have about their work
and make some decisions aboutwhat it means and figure out how
to grow their their selves,they have efficacy as well, and
we know that that makes a hugedifference.
So, again, I think I thinkabout this work like a coach,
(14:45):
right?
So the stuff that I do withteachers is the stuff that I
hope they're doing with theirkids, right, all of this is best
practice work at any level.
Speaker 2 (14:54):
Yeah, I was going to ask that about any strategies or
thoughts on how to share thedata with our students, but also
with the parents as well.
What are some really good waysthat we can provide that
measurement for parents in a waythat's helpful and
understandable for them?
Speaker 4 (15:12):
Yeah, great question.
A lot of schools are moving tolike student run conferences at
this point and I think that's areally great strategy,
especially if they're wellorganized and well set up.
So I taught middle schoolhumanities before I became a
coach, and so for me, mystudents used to do things like
keep portfolios of their workright, of the work, their
(15:35):
writing work that they weredoing or other work that they
were doing in class.
Over time they always bring afew things to fruition, but they
had all the other stuff thatthey had been making and writing
and doing, and so when we getto parent-teacher conferences,
it gave them an opportunity tolike pull a few things and to be
able to talk about their growthand progress.
Right, to be able to say, likethis is where I was at the
(15:56):
beginning of the quarter.
Right, and these are the thingsthat I realized, you know, when
we looked at my writing that Ireally needed to work on and
spend time on.
So these are been my goals overthe course of the quarter, and
now this is the last piece ofwriting that I've done and you
can kind of see evidence of howI've been growing in my work.
Right, and these are the thingsthat I did that helped me to
(16:17):
get from point A to point B.
And then I think that abilityto kind of be metacognitive
about your own work at a youngage really sets you up for
success.
As a parent now sitting on theother side of the table, when I
get to hear my kids talk abouttheir work in that way, that's
also incredibly powerful, right,because they are owning their
learning.
It's not about whether they gotan A in English class or math
(16:40):
class or science class.
Do they understand thattransferable skill of how to
learn?
And I think data is a huge partof that.
Can I?
Am I data literate?
Can I look at the feedback thatI've been given or the
information that I haveavailable to me?
Can I understand it and unpackit?
Can I make a plan about how todo something different as a
(17:01):
result of that feedback?
As a lifelong skill?
And we know that people need itat any field, right, and I
think that that transcends theindividual class and I think
teachers and kids and parentswill really appreciate that
Everything that you're saying isvery magical, because I'm a
proponent of a person who's likewe must teach skills, right,
(17:24):
like the content is somewhatirrelevant.
Speaker 3 (17:28):
They need, students need and we need skills to that
transfer across whatever we'redoing.
So looking at data andanalyzing it, talking about it,
sharing it is one of thoseskills.
So how do we collectively, Iguess, break through some of
(17:49):
those barriers of thinking aboutI don't have time to show my
kids too much, I write thefeedback on their paper, or you
know, I have a quick conferenceand then that's it.
Like we don't do anything elsewith the data I've given to them
because they don't have time.
There's like all this contentto teach.
So how do you work through that?
Because we know that, likethese are essential skills.
Speaker 4 (18:12):
Yeah, great question, I think, for teachers.
We have to realize that this isabout.
This is a working, smarter, notharder, activity, right, taking
a few minutes to look at datain a reasonable way, and it
really doesn't have to take thatmuch time.
I mean, you can do something assimple as make a like a little
three column chart.
When you look at an exit ticketright, kids names on the left,
(18:35):
like areas of strength in themiddle, misconceptions or areas
for growth on the right put yourgoals and success criteria at
the top, like what are youlooking for?
And just as you're gradingthose exit tickets, just write
like a couple of bullets foreach kid right.
And then when you get to theend, you can just take a look at
that and say, like whatpatterns have emerged?
(18:56):
What do I see about my kids as awhole, as subgroup of kids, as
individuals?
What am I missing in this data?
Right?
Like I don't know about you.
Like when I look at data, italways more curiosity comes up.
I have new and more questions.
I think that's like terriblecycle of data, right?
So how do I build on that?
Like?
What do I do tomorrow?
That's going to make sure I'mmuch more likely to hit kids
(19:17):
where they need me to be thanjust planning broadly, right.
I could spend myself in circlesplanning generic lessons for a
whole year, right.
So I can plan a whole lot morewisely.
If I spend a couple of minuteslooking at that data and making
a decision about what I'm goingto alter tomorrow.
That's more likely to get kidswhere they are today and what
(19:39):
they actually need.
So I would start there.
I mean that is being an informedpractitioner, right.
The data helps us to betteranticipate the outcomes of our
actions and increase thelikelihood that students are
going to succeed.
That's what it does, right.
If you're a coach, I mean yougot to.
I can't do my work as a coachwithout data about the teacher,
(20:02):
about the kids, about thecontent, about the classroom,
about the environment as a whole.
So model this in your work.
If you're a coach, right.
Support teachers in buildingthose habits by doing it with
them.
Right.
Working around data when you'rea coach does so many good things
for you.
It builds ownership, it buildsrelevance, it builds autonomy,
(20:24):
it builds immediate application.
All of those are things that weknow adult learners really,
really need.
It builds trust, right, thisthoughtful, transparent use of
data and it also keeps you fromhaving to have the feedback
conversation that like, let metell you about what I saw and
what I think happened here, whatmy opinion of it is.
I love it at you across thefence and hope you do something
(20:47):
with it, and instead it helps usmove to a coaching conversation
, right?
The data becomes a third pointthat the two of us can sit next
to each other together and lookat and say what does this mean?
What might we do as a result ofwhat we're seeing here?
How can I help you?
What would you want to do?
(21:08):
What could you imagine doingnext that could help you be even
better tomorrow for these kids,now that you've seen this data?
That's a totally different kindof conversation and that's what
I think you were alluding toearlier, tammy, when we were
talking about this differencebetween feedback and coaching
and why I think this is so very,very important.
It is central, the success of acoaching relationship in that
(21:29):
way, like I said, it does allthose other good things right.
Each teacher's had to do thiswork and helps teachers figure
out how to help kids do thiswork, and I think that's a game
changer for our system as awhole.
If we're ready to go there anddo it.
It's way more simple too, right, and a lot of the other things
that we see.
So if for a minimalist educatorpodcast, I think this is a
perfect topic.
Speaker 2 (21:48):
I hope this question is not going to be too
controversial.
I know we're risking going overtime as well, but I am so
curious as this thoughts allabout data and like effectively
using data for our students andfor our own practice.
What is your opinion aboutgrades, about this practice that
we have in schools of assigninggrades?
(22:11):
What are your thoughts on that?
Speaker 4 (22:15):
Yeah, grades are hard right.
Like again, grades are a datapoint, but in absence of clear
criteria for their provision,they don't really mean anything,
right?
So if a grade was accompaniedby a clear set of a clear rubric
, clear matrix, clear set ofcriteria and we see this
(22:37):
happening in some places thismastery grading strategy that's
coming online, it makes moresense, right?
I think parents kind of needyour reaction as well.
I understand a grade An A meansthat they did great and an F
means that they did bad but wedon't really know what that
means.
We don't know any of thetransferable skills that went
behind that.
We can't understand any of thenew learning that actually took
(23:00):
place in that space.
We also know I mean, I work inuniversity settings we also know
that A in one place and an A inanother place are not
necessarily synonymous, right?
So they don't do much, honestly, in terms of conveying solid
information for us at thisparticular point in time.
So, yeah, I guess I would sayI'm a proponent of mastery
(23:22):
grading.
After having this conversationwith you, christine, I think
it's much more helpful, but it'sa lot harder for teachers.
We have to learn how to do allthese other things that we've
been talking about.
It has to be built into thearchitecture of our work from
the beginning.
We can't kind of randomlyassign mastery learning grades
at the end.
It has to be in all the timebeauty of work.
(23:42):
But maybe that's not the worstthing in the world, right?
It helps us to actually seekids and the way that we've been
talking about today and that'svery powerful and help kids see
themselves in the way that wehope that we're talking about
today, so that they haveownership and efficacy in this
work as well.
Speaker 3 (23:58):
Yeah, absolutely.
Thank you for answering whatcan be a controversial question.
So thank you.
And it's at this point I mean Ilove talk.
Yes, ok, third data geek in thegroup yes, yes, we come
together and start talking aboutthese things, and we could go
on and on, but we're at thepoint in the show because we
(24:20):
want to stay true to ourminimalism principles, like keep
it short and bite-size forpeople.
We ask our guests for aparedown pointer at the end of
the show, and that might besomething you mentioned in the
show.
It could be something that youdo personally as a coach.
Anything, just a quick tip thatyou want to share as we wrap up
the show.
Speaker 4 (24:41):
Yeah, I think I would probably say that quick data
analysis tool that we weretalking about, that little
protocol, is probably the tipthat I would offer most.
Before you sit down to look atanything that students have put
forward, just think what are myexpectations for success here?
What am I looking for?
And then make a little chart ofyour kid.
What can they do inrelationship to your goals?
(25:02):
What would be the next step forthem?
Where is their misconception?
And then just look at that.
What can you gather from that?
What are your trends?
What patterns do you see?
What does everybody need?
What do some folks need?
What does this one kid need?
What am I going to do aboutthat tomorrow?
I might add one more questionis how did looking at this data
impact my thinking?
We talked about lazy brainbefore, so what biases got
(25:27):
debunked when I looked at thisdata today, and how's that going
to impact the way I work withand look at that kid or that
group of kids tomorrow?
Speaker 3 (25:36):
Yeah, Excellent.
Thank you, Emily.
So much for today's episode andconversation.
It was a happy place to talkabout data.
Thanks, Emily.
Speaker 4 (25:47):
Thank you both so much.
What a pleasure to talk withyou.
Have fun.
Data geeks of the world.
Data geeks tonight.
Speaker 2 (25:54):
Today's episode was brought to you by Teacher
Development Network LLC,collaborating to create
customized systems of supportfor early career teachers.
Find out more atteacherdevelopmentnetworkcom.
Speaker 1 (26:08):
Be sure to join Tammy and Christine and guests for
more episodes of the MinimalistEducator Podcast.
They would love to hear aboutyour journey with minimalism.
Connect with them at PlanZPLSon Twitter or Instagram.
The music for the podcast hasbeen written and performed by
Gaia Moretti уляzos during조금omer days.
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