Make Sports Coed Redux

A few months ago I made the argument that schools should move towards a coed model of sports.  The logic behind those arguments can be found here, and I stand behind the basic concept.

I was surprised to find, during August inservice, that a former student was denied a place on the high school field hockey team because he was male.   Our high school is pretty progressive, and our state’s sport governing body, starts its bylaws with the rules around the rights and responsibilities of transgender athletic participation.  Under Title IX I knew women could join traditionally male sports if there was no female equivilent, and I had assumed that went both ways.  A dinosaur of an athletic director at fault, I figured, and sought clarification.

Nope.  It was the state’s governing body, the Vermont Principals’ Association (VPA).

My first take-away is that it is important to get the facts and go to the source before you jump to conclusions and begin writing letters to the school board.  The local AD was quick to respond and detailed.  My second lessons is that organizations fear lawsuits.  The VPA lawyers prohibited males from participating in female sports because being male gives them an unfair advantage.

In my previous article on coed sports, I took that question to task.  You can decide if it holds up.  Researching the issue, I found letting boys play field hockey is controversial in Pennsylvania and Massachusetts because, when they do play, they tend to be pretty dominant.  That may be self-selection–only the most adroit males and if more join it may even out.

Here is why I am revisiting it: What is the goal?  Title IX was drafted because women got the short end of the stick.  Since Title IX women’s participation in sports has growth, and women’s participation in other areas has grown along with it.  It is not necessarily about allowing girls to play baseball, but getting everyone in the game.

When I wrote my original article, I was more thinking about my female students who wanted to be on the typically more competitive male teams.  Some could do it, and were underserved by the female equivalent.  Separate was not equal.

But, what happens when boys enter the traditional domain of girls?

If, say, ten boys went out for field hockey (assume they were good), would they change the dynamic of the team?  Of play?  Would girls get pushed out over time?  Ten is not enough to create a separate male team, and they would have few people to play.  Still, ten females would not be playing sports.  How does this affect the goals of Title IX?

With popular sports that have both male and female teams, it seems logical that, if you have enough B, C, D teams then everyone can play.  I made that argument earlier.  With one team, not so much.  This might not matter–perhaps everyone just wants the best players?  At some point, though, the sport stops being empowering for women and begins to be another place they have to fight for a toe hold.  I look at the WNBA as an example of how men can participate in coaching, but women coaches, regardless of success, are not welcome in the male NBA.  Men ruin everything (ha, ha).

I’m not sure what the solution is.  A prep school in my youth just had endless teams, from Varsity to JV to JV VI.  That sixth level of JV was not even a good intramural team, and they rarely played other schools, but they learned and participated.  If sports went genderless, that might be the solution–as I argued in my basketball example.  Even then, I’m not sure when the free market gets involved.  The discussion is still open.

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Activity to Get Faculty to Engage in Data

Getting people to care about data, engage in data and use data to drive instruction is difficult, but this exercise can serve the dual goal of data engagement and team building.

Too many teachers are stuck on current practices.  We teach as we were taught.  We hold biases.  When data confirms what we know, it feels a waste of time.  When it contradicts our assumptions, we make excuses as to why that might be so.  The hustle and bustle of the profession provides an easy excuse to pass over important data about our students instead of having meaningful engagement.

Here’s an exercise–a kind of data jigsaw–to cut through that.

  1. Data.  You will need to break your data down into smaller bits.  Say, Math scores for the 4th grade.  And, Reading scores for the 7th.  More and more.  Take the data you have already, and slice and dice it until you have as many bits as faculty and staff present.  You can use graphs, too.
  2. Each person in the room has one part of a table or a graph, which you prepared in the last step.
  3. Looking at their data, people should think about what next piece of data they need to create context (so, if I had 4th grade Math data, I might want to know how the supervisory union did. Or how these same students did in 3rd).  You could have them write the question on a sticky note (this makes it concrete) or not (which allows mental flexibility).  With the former, they can track their own thought pathway, too.
  4. People then find whomever who is holding that table or graph with the information they seek.  They chat.
  5. Together, they come to conclusions (and write them on their sticky note).  They then decide together if they need another piece of data, or their next question.  Or, they might decide each needs different data or has different questions and separate.
  6. Repeat.  The exercise ends when each individual has “next steps” for what students need based on a clear picture of where they are.

A lot of graphs and broken up data tables are needed for that!  I recommend any facilitator play this game amongst other admins or even alone to get an idea if a) would it actually work, b) what pieces are wanted and needed–with data, what makes sense in YOUR head is not always clear to others.

Big Picture, Little Picture Data

My admins have begun to ask good questions that require data to form the answer, and as a result have given me access to vast amounts of data to explore with.  After answering their initial questions, one admin began to talk about using data in a Response to Intervention (RtI) type model.  A big believer in RtI, I find I have little interest in playing with data around it because it seems pretty straightforward and not particularly interesting from an analysis standpoint–no real toys to play with; you just see something, respond and remeasure.

It did make me wonder about micro vs. macro uses of data.  In this EdX course I am taking (Data, Analytics and Learning) they touch on Learning Analytics vs. Academic Analytics; that is, looking at a set of students and the teacher in a classroom, as opposed to the administrative and larger organization level.  Often, because conversations about data are so rudimentary, we blur the two.  At our school, we slap the NCLB numbers on the whole school in one bubble and then look at individuals in another bubble (if we look at data at all).  If we could, many would use a single number and call it analysis.

I find there are three types of people who look at data:

  • Micro data users: These are RtI folks, but also anyone who looks at individual students and assignments and uses that data to help that student, the class or general, personal instruction.  Many elementary teachers fall into this.  In fact, they are very good at this–pioneers!
  • Macro data users: We are interested in systems, starting with the classroom, but then scaling up results to schools and beyond.  If you can change the system for the better, there exists a higher, more solid foundation for the micro folks to build on.  Few teachers are here (unfortunately, few admins are here).
  • Non data users: These are the folks who know what they know (or think they do). From their point of view, when the data does not confirm, it’s flawed and useless.  When it does confirm, it’s a redundant waste of time.  I’m throwing half of all teachers and admins, and many secondary teachers, into this lot.

Of course, I have no actual data to support these conclusions (ha, ha).  It did, though, make me wonder which focused efforts–macro or micro–show best results.

In looking at the data that was given to me, I was able to track how cohorts did compared to other schools in our district.  I find it helpful to think in terms of sports: If a cohort beats the district average we “won” and if we did not, we “lost”.  Looking at six cohorts over three years, two cohorts clearly had something going on–they had “winning” records.

When I looked at teachers, only two seemed to have “winning” records.  One was me.  The other had those winning cohorts two of their three years, so it is hard to discern if they are a good teacher or just got good kids–the results of that third year indicates the former.

Beyond tooting my own horn, it has made me think about my program.  A big picture person, I tend to avoid the trivialities of my subject–spelling, grammar, historical dates and the like–and focus on large trends, like being coherent, doing analysis and having the reader understand the content.  It has been a struggle.  Besides a raft of coordinators demanding spelling programs, I want to do right by my students.  Cultural currency is important–our ideas will not be judged if the reader dismisses your work due to spelling errors.  I find, though, that the resources allocated to such things is better spent elsewhere–the kids who can’t spell can’t do plenty, while the others don’t need the spelling program.

Instead, I look at long timelines.  Until last year, I taught multi-age.  I had a two year timeline; students often came back from the summer seemingly smarter, and tested great before leaving me for good.  Success!  Success?

At this point, I am struggling with the balance.  Before you respond “both” to the question of micro or macro, know that choices have consequences–what you choose is also you not choosing something.  Imagine a spectrum where, on one end, we did 100% spelling.  Now, slide away form that so you can include grammar, then writing and then perhaps a little reading.  As you add, you approach zero spelling.

Question: Is there a point where you do so little spelling that it really isn’t worth it to do any?  That’s where I am (I don’t do any).

Question: What, then, is the point of diminishing returns where input and output are maximized?

Question: In plotting out the returns of all areas needed to be covered, which has the “most bang for the buck”?

In economics, this is called the “opportunity cost” of choices–what do you lose when you make a choice, and is that loss less than the choice you went with?

All a good struggle to have.

Mapping Data with Google Sheets (on a Map!)

I have long wondered if student success is tied to where the student lives.  (Why?  Read in this post.)

With between 50 and 120 students at a time, sitting down with a map, charting out each student’s location and then linking their assessment results to that pin has seemed a bit arduous.  Google Maps has made finding the location a bit easier, but never could I figure out how to look up more than a single location at a time (and without having to manually input that, to boot).

After trying out Tableau for a EdX online course (the excellent Data, Analytics and Learning MOOC offered by UTArlingtonX–free and still informative three years after it closed) I was intrigued by its mapping promise.  Below is my journey, as I could not figure out how to get Tableau to do it.

Assessment Map Sheet

My original data table

To work, Tableau needed latitude and longitude data (it probably did it for me, but…)  I had street addresses, with each element in a different column (number, street, town, etc.).  Here is a sample data table.

I got an add-on from Awesome Table.  The program seems to do a whole lot, but I only wanted the latitude and longitude.  On this screenshot note two things.  First, that I was able to create a single address from multiple columns.  That’s what you see happening in the middle.

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pasted image 0 (1)Second, once I had that column it created my latitude and longitude.  You can see that column here (yes, it’s all blurry because I can’t figure out an efficient way to drop screenshots in WordPress, so blur).

Note that in the box on the right it offers you to create a map.  It will, indeed, drop pins on a map.  While I could figure out how to put my data in the pin, I could not figure out how to color code my pins.  That’s what I wanted–to have a range of colored pins so I could see the clusters effortlessly–and then click on individual pins for details.

Then I found Claire Miller, a data journalist who was looking to provide a map of clinics in Wales that still took NHS and those that did not.  You can find her informative blog here.  She tipped me off to Google Tables.  As Claire wrote in 2012, Google Tables was in beta and I hadn’t remember seeing it in years (I assumed it was folded into Google Sheets, because they always struck me as close, mainly because I don’t really know what Google Tables does).  Now called “Fusion Tables” I had to add it to my Drive.

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I’ll save you the boring steps of linking your spreadsheet and get to the map.  Table will open to Rows 1, so click on “Map of Latitude”.

Ironically, the “Location” choice (on the left) was set for latitude–and it didn’t work after all of that Awesome Table stuff!  When I chose “Full Address” from my Awesome Table merge a few steps ago it did.  Great.  Pins.

pasted image 0 (3)Here is the fun part.  Click on “Feature Styles” (left) and this box comes up.  Claire created a column in her spreadsheet with a command of what pin to place (middle tab) as her’s was a yes-no binary.  I used “Buckets” on the right for a range.  A second benefit is that as I update data I don’t have to update those commands–Buckets reads the new data.  As my scale was a 1-4, that became the range.  Be sure to choose the column you are taking data from (I forgot in doing it here and was flummoxed for a moment as it mapped zip codes).

pasted image 0 (4)Not done.  Click on “Change Info Window” (left) and this box of info will come up.  Here, you choose what data is useful to you or the user.  For example, I unchecked our state, town, zip and such because all of the students live in the same town.  All I really care about is name, specific street address and score.  (You can move the order of the codes manually if info order matters to you).

pasted image 0 (5)And here is the map.

With eight data points, it is not very exciting.  I chose small pins because I usually map a while grade level.  But, I click on that one pin and Nancy’s relevant data comes up.

This data is not very telling (it is random demo data), but the maps for my class are a bit more telling.

Again, you can read about what you might do with this here:  Read in this post.

Why Mapping Data Matters

I am going to post on how to use Google Tables to map student data, but I wanted to explain why you might want to do it separately.  You, I am sure, can find a dozen uses for mapping data.  Here are a few of mine:

Knowing the Community: I do not live where I teach, and rarely leave the building (I go a few hundred meters to the market for lunch, and drive the main street on my way elsewhere).  Mapping out my students helps me understand where people live.  It seems like a small thing, but clicking about on clusters and rural areas helps me understand my community–the trailer parks, housing developments, rural farms and deep woods.  I can see divisions and lifestyles just from geography, as it blends with what they talk about in class.

Resources: It also helps me understand who has resources and who does not.  Some of our most needy students do not have easy access to the library, stores (for supplies) and rely on the late bus if they want to participate in anything after school (and I can see who will be on it for an hour because of how far away they live).  From this I know for whom basketball is a sacrifice, and who can stay after to finish up a project before zipping across the street to their home.

Clusters: It is common for adults to make assumptions about where people live.  It’s a social class bias.  As many teachers are middle class, from middle class backgrounds, they just don’t know.  The local trailer parks get a lot of abuse based on those biases.

In The Tipping Point, Malcolm Gladwell makes hay about studies showing community matters more than family in shaping children and their values (the more intellectual among you probably read the actual studies).  That doesn’t stop us from blaming the family for student results, but it also calls into question where students live–is the neighborhood a problem, and can the school counter-act that influence?

This is where my interest in maps started.  I cannot help but think this stems from my own biases, and I’m unsure how helpful this line of questioning is.

Focused Interventions: Ten years ago our old principal wanted to reach out to families and make the school a bigger part of the community.  We wound up having an ice cream social the day before school started.  cache_240_240_0_100_100_16777215_new-framework-cover-golden-lampGreat, except that Ruby Payne’s A Framework for Understanding Poverty makes clear how adults who were unsuccessful in school are reluctant to come for such events (or parent conferences, etc.).  As non-threatening as it is, our ice cream social tends to be mostly middle and upper class parents of successful students.

In reading about the Civil Rights movement, I noticed how they organized where people lived.  They didn’t ask people to come, but went to them.  They used churches, meeting halls and the living rooms of trusted members of THAT community.  I wonder, for example, if tutoring and summer school might be off campus–in the heart of these low scoring clusters?  Perhaps the administrator might hold a parent group meeting somewhere other than the school?  Do those far flung places have churches or halls in which we can hold classes?  Perhaps rent an apartment or trailer for a summer month?  When you see that half of the students in need live with a kilometer from each other, but ten kilometers from the school, you have to wonder if the mountain needs to go to Mohammad.

Note: Know Your Students: Of course, knowing more about your students adds to this.  For example, one of my students lives with a grandmother who does not drive in a rural home–she relies on the bus a lot.  To keep her after school is a big thing.  But to keep her in for recess denies her the one chance she has to be social and make connections.  I try and find alternative times to support her.  This is very different from the girl who lives in the development with five other classmates, a short walk from school.  Awareness matters.  By combining this map with my personal knowledge I craft my responses to their needs.

Check out my post on mapping data here.

Unknown Known

There are the known knowns; there are things we know we know.  We also know there are known unknowns; that is to say we know there are some things we do not know.  But there are also unknown unknowns–there are things we do not know we don’t know. –Donald Rumsfeld, Secretary of Defense under George W. Bush

Donald Rumsfeld made these comments in response to the possibility of weapons of mass destruction in Iraq.  He got a lot of flack and mockery for it (the flip-floppery of the words and their utter ridiculousness on the surface seemed to encapsulate the Bush White House response on everything, even if the core idea was valid) from an American people that were post 9/11 afraid, sitting on the cusp of a new, violent world.  As Iraq proved, there were plenty that we did not know we did not know.

9780143125082

Nate Silver, the founder of the great sports, politics, and economics data site FiveThirtyEight, also wrote a pretty good (a bit long) book The Signal and the Noise.  It’s worth the read as it will make you think about data in new ways, and really question the assessments we do (and the assumptions we can and cannot make).  In the chapter “What You Don’t Know Can Hurt You” he looks at intelligence failures, including 9/11 and Iraq, and delves into the idea of the “knowns”.  The breakdown is interesting and important:

Known Knowns: You know the problem and have the answer.  You know you need enough chairs for your class to sit.  Thanks to a class list, you know how many kids will be in your class.

Known Unknown: You know the problem but do not have the answer.  This is the first day of class.  You know the material you have to cover.  Unknown are the skills students bring into the classroom: Can they even read the text you are counting on?  Unknown are the personalities: Do they like to learn or are their “issues”?  These questions x 1,000.  Schools combat this unknown with assessments and data; a good administration will give teachers access to databases or just include basic data in your class list (my first job included DRP scores and IEP designations with the list).  Elementary schools spend a lot of time crafting classroom balance when moving kids grades, and reporting on each child before the new teacher takes over.  High schools have more informal information exchanges, in the teachers’ room over coffee or, later, in a bar over drinks.  Schools recognize this problem and use data to solve it as much as they can (caffeine and alcohol are mere balms).

Unknown Unknown: “A contingency that we have not even considered,” writes Silver.  “We have some kind of mental block against it, or our experience is inadequate to image it; it’s as though it doesn’t even exist.” (421)  There is a reason we pay experienced teachers more.  If you’ve had a student teacher recently, or mentored a new one, you can see they have no idea what lies ahead.  Not only do new teachers not realize it can take fifteen minutes for a student to find a pencil, they have NO idea what the home life of many are and how unimportant Poe’s “The Murders in the Rue Morgue” is at that moment in time.  Who knew?  There is a reason so many teachers quit in the first three years.

* If we could get parents, school board members and others to teach for a month the entire tone around teacher negotiations would change.  There is nothing more frustrating (I would argue a microagression) than a non-teacher suggesting a lesson.  “If you would just….”  Thanks, no.

Unknown Known: As veteran and studied educators, we know the results but not the problems (we do make judgments, though–I used to blame middle school teachers for what my 9th graders couldn’t do, until I became a middle school teacher (I try not to blame the elementary teachers)).  I remember a few yeas ago, I got data showing that nearly 25% of my incoming students were illiterate.  Easily, one-third are below grade level.  That state is known.  The problem is not.

Silver does not talk about this–and I have no doubt I’m getting the binary wrong and this state of mental organization doesn’t even exist–but for me the “unknown known” seems to be the blind spot in education.  Instead of looking at a known problem (kids can’t read) and the unknown solution (Why?  How can we fix it?) we should be looking at how we got here.

The Difference and How It Helps

In our district, we are pushed to look at where the student is and solve the problem.  A student can’t read (known) we teach them how (unknown how, but solve it over 180 days).  That’s the school year in a nutshell.  Next year, repeat.

The problem is that it is reactive.  Ten (more?) years ago our district went full RtI (Response to Intervention).  For at least two school years (a lot time for many initiatives to last) we talked about using data (then, a new idea) to drive instruction (an even newer idea).  If Johnny did not know his alphabet, someone would take him aside and drill it; then he’d be with the class and ready to push on as an equal.  It is a great idea.  It reminds me of herding stray sheep to keep the whole alive.  We even got these great laminated folders that detailed much of the philosophy and protocol (I kept mine–it is so clear–while I’ve dumped my share of other such initiatives and supporting materials).  Unfortunately, RtI got watered down by the differentiation push that followed it.  Plus, because PBL (Performance Based Learning) had not yet happened, those teachers in the upper grades complained that their content was too complexly woven together to do a simple intervention (PBL and targets takes some of that argument away–just teach a focused Evidence group, for example, if that’s their weak spot).

The unknown known is not about the student in front of you.  It is about the path that brought them to this moment.  You know the result: one-third of my class struggled with literacy.   I don’t know the problem: For some reason, a large number of students could arrive at middle school without being able to read, but I don’t know why.  We have good teachers in the younger grades.  We have resources.  It is unknown how we got here.

In putting the unknown first (unknown known) we focus on the system, not the individual.  In this instance, I am not looking at my students but those who are coming up.  In theory, if I can know that unknown those coming into my class in future years will not have this issue–they will be able to read, and I can focus on bringing them up even higher.

The Power (and Blind Spots) of Linear Thinking

Semantics?  Perhaps.  But there is a lot to be said about linear thinking.  Our school is dogged by linear thinkers that cannot see the complex interconnectedness that is life (and teaching).  They often hold back discussions and real change because they cannot see how fixing C before B helps get to M–and we all get bogged down.  But linear also clarifies.  In thinking about what lead up to this moment, our solutions look to the future.

The question to ask is simple: How did we get here?  It is one we rarely have time to address because, teaching.  Those one-third in my classroom right now need me.  Those two-thirds need me, too.  Someone, though, needs to be thinking about how we got here.

But we know the unknown unknown (confused or just meta?).  Ten years ago, I sat in a Literacy Committee meeting and heard from the kindergarten about this group.  The next year, the first grade told us about them.  By the time the third grade teacher reported out about “this group” I asked what we were doing about it.  Nothing.  Blank stares.  Crickets.  Then, we threw extra resources at it.  They got better.  To the fourth grade teacher, this was problem: solution.  For me, though, that group was known but I had no idea why.  When they got to me, I knew plenty.

Root out those linear thinkers who bog down every other discussion and put them to work.  One a wall in a conference room put two lists: Cause and Effect.  The latter is what we know (literacy).  Charge them with solving the cause.

No Hats in School: The Data Supports It

Fifteen years ago, when I began at my current school, the rules were clear.  We had a dress code: Shorts and skirts could be no longer than your knuckles when arms hung by your side; tops had to have straps two fingers wide; no underwear could be showing.  And, of course, NO HATS.

Much of this has gone by the wayside.  The short shorts and skirt issues, plus ones around cleavage, were disproportionally enforced on girls with curves (the first graders had crazy short shorts, but their teachers wagged their fingers at my middle schoolers).  There was also some body shaming going on.  Our focus has shifted to clothing disrupting the learning process (profane or offensive, or really shiny) and being unable to participate in activities (dumb shoes).

Except for hats.

We have debated hats on a number of issues–many surrounding learning social norms and cultural currency.  The fact is that if you don’t wear a hat no one cares, but if you do some people will hold it against you.  Not everyone is convinced that it matters, and, as a result, enforcement is lax.  A rule that is not enforced is not worth having.  Still, I fight the battle.

But I am a person of data.  Is there, I wondered, a reason for banning hats that is supported with data?  When I thought about my own dislike of students wearing hats (against the rules) it came down to a gut reaction–students who wore hats (and were constantly flaunting the rule) always seemed to be in trouble in some other way.

Was this true or was it just an impression?

Method: After a year with a grade level, I broke students into several groups: Behavior problems, No behavior problems, and Recent behavior problems.  Then, I tagged those who generally wore hats (against the rules) and those who did not.  Here are the results:

hats pie graph

Behavior Issues; Wears Hat: 20.6%
Behavior Issues: Does Not Wear Hat: 17.5%
Recent Behavior Issues; Recently Began Wearing a Hat: 7.9%
No Behavior Issues; Wear Hat: 3.2%
No Behavior Issues; Does Not Wear Hat: 50.%

Conclusion: Not all students with behavior issues wear hats, but nearly all kids who wear hats have behavior issues.

Why?  I see the wearing of the hat as the canary in the coal mine.  If a kid cannot come in and follow that basic rule, why would we expect them to follow other rules?  Those with recent behavior issues are the most interesting because their wearing hats coincided with the change.  Perhaps the baseball season is a poor influence (ha, ha)?

Besides wearing hats being anachronistic, the argument I hear is that we have other battles to fight.  My response is that if a student will not adhere to this basic rule, why do we think they will respond to others?  It has been argued that, “if they get their work done, what does it matter?”  By that measure, students who get work done don’t have to follow any rules.  There are students who don’t even need to come to school and they’d be fine!  It is extreme (I’ve been told), but how many rules are arbitrary when measured with production?  Hats are arbitrary (beyond cultural norms), but they are also a useful nod to being part of a larger community.

Bonus: Paul Young is a music teacher who wrote a nice post on hats and music performance etiquette.  Here, he measures a hat-ratio.  Check out “The No Hat Rule” here.

And try your own experiment as I did.  Were the results the same?  I’m curious about classroom and schools that have no hat policy–do the results hold even when hat wearing breaks no rules?