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.


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.

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.


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.

Aggregate Not Facilitate

I remember the interview well: “So, you’re a facilitator, more than a teacher.”

This was in response to my description of the student-centered model I had presented. I have always struggled with letting go of control, having once believed that a good lecturer was the key element to a transformative class. Now, I aspire to be a Nancie Atwell, although I cannot give up my podium completely.

Still, in 2002, putting desks in a circle instead of rows qualified as transformative.

Currently, I am “taking” an archived course on data through EdX and the University of Texas Austin. I put “taking” in quotes because I’m really just rummaging through their archived material, missing out on the most important element–the interaction with others in the course. It’s all explained in their video How DALMOOC Works, which I recommend for helping you see another way a class can be structured. (DALMOOC stands for Data Analytics and Learning MOOC, or Massive Open Online Course)

To boil it down, the primary learning in the class comes from students doing stuff in the world, integrating and talking with the world, and then bringing all of those discussions back to the class. Students talk with experts, go on forums, tweet, blog, chat, talk, explore and create and then get together (online) with the class to share out.

Notice how this is different than most online courses and their required posts and word counts. Yes, that’s there, but this is about the student and the power of sharing.

What is the teacher doing? Facilitating, sure. They set the whole thing up and keep it going. They are the expert and guide.

But then the aggregate. The most interesting thing is that they monitor and share the most interesting, insightful and important learning that happened that day. It goes in an email. Instead of monitoring words and posts for participation, these instructors promote ideas and work that moves the group forward. This is a community.

Now, I know we can leave no child behind. That quiet kid falls between the cracks. Most important, the MOOG is a volunteer course with no fee which starts with thousands and ends with far fewer completions. But prodding is a different philosophy than inspiring. I am wondering how this model of agregation could become a meaningful, transformative next step.

Make Sports Co-ed

Two years ago our administration told us not to use gender in our classroom. It had come up when students were asked to pack-up the room for the day–boys putting away materials, girls stacking chairs. It was one of many daily sorts we do, and students self-designated their gender and responsibility, but one student who was questioning their gender felt stuck. We were asked to look at other data when we make groups, be it classroom chores or placement in classes. It was a solid decision that moves us forward in a number of issues–read my post about “the boy problem” here.

When told that gender was no longer being used for groupings, I asked if this was going to be true for sports, too.

It is a complicated issue, but it gets at the heart of problem with using gender as a designation–it offers no path to a solution, except if the problem is gender discrimination.

For the sake of argument, let’s use the stereotype that “boys are physically bigger and stronger than girls” because this has a basis in data.  We line up everyone who wants to play basketball and find that for 80% of boys that is true.  If a co-ed team was created, 80% of the A-team players would be boys.  What, then, to do about the other 20%?

If we stick to gender, we are going to fill the team with sub-par specimens instead of the best players–period–filling up those roster spots.  From a tactical standpoint, the coach would want that 20% of stronger girls.  A co-ed team.

Let’s add some complexity–skills.  Teams have smaller, quicker players with skills that trump size and strength.  If the roster was filled with the best players–if the coach was able to evaluate without taking gender into consideration–the team would probably be a diverse group, physically.  From a tactical standpoint, a good coach would want the best fifteen players on their squad–size and strength being only one factor.

Note that in that last scenario, other than a concern about discrimination, gender has moved to the side.

What, then, is the issue?  Let us take plain bias in evaluating talent off the table–it is a huge one, but this will allow us to look at other, overlooked issues.

The first is equity.  Our school has four basketball teams–Boys A, Boys B, Girls A, Girls B.  If we went co-ed we could simply have A, B, C and D.  Extending the above, let’s assume Team A has an 80:20 split of boys: girls.  Let us further assume that Team B has a more equitable ratio, if not the former Girls A 80% taking up the majority of the Team B spots.

Does Team A being mostly boys and Team B being mostly girls create inequity?  Typically, our Team A goes to more tournaments, gets the new uniforms, and has a more committed coach.  Team B is more developmental–and I would assume Team C and Team D would be more so.  As the majority of girls are on the lower teams (even on Team B), the majority of girls would get less.  At least with a Boys A and a Girls A schools can easily count dollars spent, games played and the like.

The real issue here is the purpose of the sports program in the first place: The eternal debate–winning vs. participation.  For those hoping to be the best, they need to play the best.  On the court, you want the best players regardless of gender.  Those who are not in the top fifteen need development.

Equity means respecting development.  Players on Team B should be striving to earn a spot on Team A.  Instead of focusing on winning games, though, that program needs to focus on development of the player.  This requires participation and good instruction.  Equity falls away when players are no longer pushed.  Team C and Team D should be the same, even as they are even more elementary in terms of skills and development.

When players are on the team where they are, the system is equitable.

Bias.  Of course, this is only possible when bias in evaluation is taken off the table.  But parents get ugly when it comes to sports.  When teams are by gender, parent after parent still finds a reason their kid is being held back, not on Team A or riding the bench too often.  One coach a town over, after a win, was confronted by a spreadsheet wielding parent, recording time played by each player and a quibble over a two minute variance (the coach scheduled roles and times prior to the game, except the fourth quarter so he’d have flexibility if the game was close).  He moved to absolute equity the next game, lost, but no parents complained (the players were not as happy).  Whoa the burden coach’s kid actually being good, but constantly being told they got their spot because of bias.

Add gender and the result is explosive.

In the data world they call this issue “the signal in the noise.” 9780143125082The signal is the problem–finding the best players and playing them to win–while biases are the noise. We identify gender as an easy way to categorize people. We notice it. Evolutionary, we are built to recognize patterns as a means of survival. But our intuition can cause us to fall to, create and reinforce stereotypes. We create more noise, and lose the signal. Every stereotype has some truth at its core, but it ultimately binds the person it is being done to–we put the person in a box. And, it makes others blind to the real problem and its solution.

In the case of those 20% of boys who do not get spots on Team A because there are girls who are better, gender now becomes a factor.  A battle to be fought.  This is where cries of political correctness and reverse discrimination become issues, not what is best for the players.

The issue, then, is dealing with this bias.  Notice how, over several paragraphs, we have moved away from the stereotype of boys being more physically able than girls and are now talking about bias and equity.  Dealing with equity is hard.  It requires education and community support.  It requires a commitment, so that it becomes, over time, the norm.  “You are on Team B because you need to develop skills X, Y and Z.”

That we shy from implementing this tells us something about our values as a school and community.  Schools need to set the standard against bias in all forms.  They cannot do this when their institution underscores this in the group representing them to the larger community–wearing uniforms with the logo across their chest and being photographed for the paper.

The way forward.  There are plenty of obstacles to move forward.  Looking at basketball, girls use a different ball.  But people adapt.  Until seventh grade girls playing recreational lacrosse did so with boys, with full contact rules.  When they were segregated, playing by girls’ limited contact rules, most felt it was a step back.  These girls were ready to hit.

One step is to desegregate those sports without such conflicts.  There is no reason I know to have separate cross country races for boys and girls.  Wrestling, golf and typically single-gender sports (football, field hockey) should be gender-free, too.

It should be noted that, through most of schooling, the physical size and natural abilities waxes and wanes.  A small kid one year comes back from summer break having grown half a foot.  The kid with no balance suddenly catches up.  As educators, we should be embracing a growth mindset.  If only K-8 schools embrace a gender-free athletic process it will create a foundation for growth.  There is no reason not to.

Finally, schools should focus on both winning and development, but the second part is key.  Having a Team A, with the understanding that it is competitive, is important in giving an aspirational goal for all.  Those on the team need to accept that, in being on that team, they might sit.  But practices should be developmental.  And Teams B, C and D should be levels of development.  There is room for both those who compete and those who just want to play.  The emphasis is on work and commitment, and from that comes growth and joy.

The Boy Problem: Noise Obfuscation of True Problems

While a bunch of us were chatting, our administrator noted how all of the discipline cases he is dealing with are boys.  He then noted how most of our failing students are also boys, and that most of our top students are girls.  Not alone in this observation, he pondered what is perennially proposed: A different program for boys than girls.

Bad idea.

The problem of using gender to model programs is that it offers no path to a solution, except if the problem is gender discrimination.

In the data world they call this issue “the signal in the noise.”  9780143125082The signal is the problem–behavior and academic achievement–while classifications (gender, race, age) are the noise.  We identify the boy problem because gender is an easy way to categorize people.  We notice it.  Evolutionary, we are built to recognize patterns as a means of survival.  But our intuition can cause us to fall to, create and reinforce stereotypes.  We create more noise, and lose the signal.  Every stereotype has some truth at its core, but it ultimately binds the person it is being done to–we put the person in a box.  And, it makes others blind to the real problem and its solution.

To say that our school does not serve boys is to say that there is only one way to be a boy.  It’s a box we put people in.  For the sake of argument, let’s use the stereotype that “boys need movement.”  And let’s say that 80% of boys need movement.  That leaves us missing 20%.  And if the needs are reversed for girls–only 20% need movement–that leaves that group missing out, too   Everyone is in a box.

Instead, we might build a program around students needing movement, and another program(s) around something else.  Now, those student who need it (half) get movement.  That 20% of non-movement boys are now free to pursue their needs, along with 80% of the girls.  Win-win.

We track gender, race, SES and the like for two reasons.  First, some elements of an identified group we can address–SES kids, by definition, need to be fed. But that use is limited. Second, we identify groups because some have been discriminated against, historically.  That was the reason NCLB required those designations.  When a group comes up short, this provides a place for schools to start the conversation–is the cause discrimination?

After that has been answered in the negative (hopefully) the use of such designations should then move to characteristics of the individual students in question and their needs.  Why are these students getting into trouble?  How large an issue is that, and how can it be addressed?  In looking back at NCLB the one area that using the data made a big difference was with SES students.  Interestingly, the solution was like the 80:20 above–many needed something the school was not providing (but not all), and some non-SES students benefited from those same programs.  Win-win.  It was not because of discrimination, but in starting there schools took a fresh look at a problem and identified the true root cause.  Focusing on gender instead places the needs of some on the larger demographic while excluding others–it is not an efficient solution and can create new problems.

So what is our school’s problem?  We are too indulgent.  In our desire to provide to students what they need to succeed we have failed to hold them accountable.  We take off limits but do not demand responsibility as part of the bargain.  For example, I allowed music last fall because students benefited as it canceled out distracting noise.  Now, it is the distraction.  And music has creeped into other activities and classrooms.  Snacks have become meals.  Fidgets have become toys.  Water and bathroom breaks are a right.  In the end, I should have a product.  Not always.  In opening the barn door first I have now set up my enforcement of academics as conflict, not an inspired goal.  Too often, the work reflects this shift in tone from support to scold.  The exception is the rule.  We indulge.

We have reached the tipping point: As we approach 20% of students being an exception, the exception becomes the rule.  When music left the classroom, using during essay writing only, it became an exception.  As 20% of classrooms had exceptions (hats, music, no lines, snacks) it becomes harder to hold to the rule.

There are two fixes for this.  The first is to hold the rule.  No hats.  No music.  Lines.  The second is to add responsibility and accountability to the privilege.  Currently, we ask nothing in return for privilege.  Why?  Because monitoring it is difficult and it sets up conflict.  But that’s exactly how we creep towards the tipping point–we let those with the least amount of respect for others redefine the rule.  When those 20% change expectations the number of rules pushed grow and the number of students breaking them grows, too.

Those kids are defending by packs of adults, all justifying why they need it and apologizing for transgressions.  It’s not the exception that is the problem, but the transgression and accountability.  We are starting with an assumption that this thing bestowed–music, gum, movement–is a right to be taken away, not a privilege to be earned.  This is the exact opposite of how the adult world works–the most responsible gets the privileges while those lacking control either get few rewards or confinement.  And we excuse them in academics, too, for the same reasons.  We are doing these kids a disservice.

All of this is hard.  You can’t penalize a kid for the lack of structure provided up until the moment they cross a line.  The Responsive and Developmental Design programs offer those systems and protocols, but they require time and commitment from the group.

I would argue that it appears boys are the problem because success involves awareness and impulse control.  Boys seem to have more of a problem with this, but they are not alone.  Because society excuses much of it based on stereotypes (“boys will be boys” and “you can’t expect a boy to sit for an hour”) they hear that and internalize it.  When we lean on punishment, though, we are teaching students not to be caught.  Our data does not account for those who appear to follow rules but who skate the line constantly–take a census of how many are not where most of their peers are, or doing outlier behaviors, and you’ll find “they have permission.”  Plus, we have behaviors that are more personal, and do not affect others.  Even with academics, Tier II is filled with those who flail openly and dramatically.  When we stop looking at the major behavior data, but instead account for minor behaviors and any deviations from the rule, a true picture of our ailments become clear.  The solution is not movement but accountability to norms and earned privilege.

This Wall Street Journal article is a nice summing-up of the balance between challenge and aspiration.