Post 17: Geoff Colvin "Talent is Overrated" Part 2

     In the last post, I wrote about Colvin’s “Talent is Overrated” and how deliberate practice is the secret to success.   But, Colvin points out, all of this is moot if you do not create a culture of innovation in your school first.  Teachers must feel free to try new things, experiment, and take risks.  In a risk-averse culture, teachers will just continue with the status quo instead of practicing what is important and coaching each other to improvement.

     In a sentence, Colvin says that the very first step in creating a culture of innovation is to tell people exactly what is needed and then give them the freedom to do it.  This is reminiscent of two other books that I’ve read, “How Did that Happen” and “Drive.”  The authors of “How Did That Happen?” point out that when people don’t meet the leader’s expectations, it is often because the leader did not explain their expectations well enough.  In “Drive,” Daniel Pink says that the three keys to motivation are autonomy, mastery, and purpose.  So, it makes sense that if a leader explains the expectations well and then gives teachers the autonomy to accomplish those expectations, then magic can happen.
     Many times, I see principals approach change this way, “Our graduation rate is low, I’d like to raise it to 90%, and here’s how we’re going to do it.  Now is everyone on board?”  Of course they’re not on board because the leader decided the focus, determined the goal, and set out the plan for how to reach the goal.  That’s the opposite of Colvin’s idea of how to motivate innovation.  I read somewhere and cannot remember where that this is an example of shared leadership under the definition, “I make the decision and then share it with all of you.”
     Instead, a plan that looks more like one that Colvin, Connors & Smith, and Pink would recommend would be:

1) Distribute graduation data and have groups of teachers point out data that concerns them most
2) Have teachers discuss why a focus on that data point would benefit students
3) Have teachers determine what a reasonable stretch goal would be for that area
4) Brainstorm ideas for how that goal might be reached
5) Have teachers who are passionate about one or more of the ideas recruit their own teams to create a plan and implement them
6) Provide feedback, coaching, and support as the teachers implement their plans
7) Study the data to see how the movement is working
     This plan allows teachers to determine what to focus on within a range (graduation), what a reasonable goal will be, and how to focus on it.  They are then given autonomy to go out and use their best ideas to try to address the goal.  Teachers would work 100 times harder on this project than the one that the leader developed and set in their laps.

How do you set clear expectations and give autonomy to meet them?  Add your stories in the comments section below.

Post 16: Motivational School Leadership: Geoff Colvin "Talent is Overrated" Part 1

                This blog has always been about taking the research and literature on motivation, influence, and improvement and applying it to principals and their schools.  The more I read about this subject, the more I realize that these authors all read the same research and put their own twists on it in their books.  The book covered in this post is no different.  It’s a great combination of Outliers and Mindset.  The book is “Talent is Overrated: What really separates World-Class Performers from Everyone Else” by Geoff Colvin.

                The overriding theme of the book is that there is no such thing as talent, there are those who have deliberately practiced for a sufficient amount of time and there are those who have not.  Once people realize this, they see that high performance isn’t born, it is borne out of deliberate practice.  The first idea, that sufficient deliberate practice is necessary to be great is similar to the 10,000 hours idea in Outliers.  Colvin uses 10 years as his time period, which at 20 hours per week would add up to 10,000 hours.  The second idea, that some people think that performance is born and others think it’s developed, is very similar to Dweck’s Fixed and Growth mindsets (blogged about here, here, and here).

                In this post, I’ll write about Colvin’s “Seven Principles of Great Performers.”  Here’s the list:

1) Well-designed practice activities

2) Coaching

3) Repetition

4) Feedback

5) Self-regulation

6) Building knowledge

7) Mental models

                Much of the book is about the well-designed practice activities.  My first a-ha was that just doing the activity over and over is not deliberate practice.  Basketball players do not just play pickup games every day to practice basketball.  They break the game into tiny skills and deliberately practice those individual skills over and over and over with coaching and feedback from an expert.  Musicians don’t just play songs over and over.  They play scales, do breathing exercises, and play portions of songs many times over with an expert coach providing immediate and focused feedback.

                The most difficult part for the principal trying to apply this book to their school is that most of the examples are in sports and music.  Deliberately practicing lesson delivery, classroom management, or parent phone calls isn’t as straight forward as practicing a tennis serve.  BUT IT IS POSSIBLE!

                After I read “Talent is Overrated,” I asked my colleagues in my office, “How do we deliberately practice what we do?”  At a county office, we coach, provide professional development, evaluate data, support collaboration amongst teachers, etc.  I also asked, “In the limited amount of time that we have in our lives, which of the things that we do are important enough to dedicate time to deliberate practice?”  Some of my colleagues pointed out books that address these questions more focused on schools and, of course, I’ll blog about them in the future.  FYI, the books are “Practice Perfect: 42 Rules for Getting Better at Getting Better” and “Mastery: the Keys to Success and Long-Term Fulfillment.” 

                In the next post, I’ll talk about how Colvin suggests that leaders can set up a culture of innovation in their organizations.  Turns out that it’s very similar to Daniel Pink’s “Drive” combined with Connors and Smith’s “How did That Happen?”

                How do you set up a climate where teachers deliberately practice their craft?  Please give examples in the comments section.

Interview of Geoff Colvin on Youtube:

Response to E.O. Wilson's "Great Scientists Don't Need Math"

                In the Wall Street Journal, E.O Wilson wrote an article entitled “Great Scientist ≠ Good at Math.” (here)   There were so many logical fallacies in this article, that I decided that it needed more than a few paragraphs in the comments section, it required an entire response.

                The gist of Wilson’s point is that not all scientists need high levels of math.  He claims that most scientists just hire someone to do the math for them and others don’t need math at all. 

                Wilson states that, “Pioneers in science only rarely make discoveries by extracting ideas from pure mathematics.”  That’s beside the point and the point should not be limited to pioneers of science (who mostly worked before calculus had even been developed), but instead it should be about the vast majority of modern scientists.  Wilson follows up this statement with the idea that if something new is discovered, the scientist can just hire a mathematician to analyze the data.  Science is so tied to instrumentation, data collection and analysis, how would the scientist know (s)he had discovered something new until the data was analyzed?  If the scientist is not good at math, how would (s)he even know what to ask the mathematician to look for, what equipment to use, or what methodology to follow?  This would be like saying that a General Medical Practitioner doesn’t need to know anything about cancer because there are oncologists out there.  But how will the GP even know to refer the patient to the oncologist?  The more the doctor knows about cancer, the better (s)he will be at referring patients.  Similarly, the more a scientist knows about math, the better able they’ll be to make new discoveries.

                Wilson then states what he calls Wilson’s Principal No. 1, “It is far easier for scientists to acquire needed collaboration from mathematicians and statisticians than it is for mathematicians and statisticians to find scientists able to make use of their equations.”  Whether it’s easier for a scientist to find a mathematician or a mathematician to find a scientist has nothing to say about whether the scientist needs to be good at math.  What it really says is that mathematicians should be better at science.  Wilson’s Principal No. 1 is a not applicable to this discussion.

                Wilson then argues, “The annals of theoretical biology are clogged with mathematical models that either can be safely ignored or, when tested, fail.”  The same could be said of non-mathematical theoretical sciences!  This has nothing to do with the math; it’s just how science works.  Many hypotheses are tested and most of them fail.  Think ether, flat world, geocentric model of the universe, indivisibility of atoms.  They’re all false and none of them involved any mathematics.

                Wilson follows this up by saying that if a scientist’s mathematical skills are weak, they should try to improve them, but otherwise should avoid the highly mathematical sciences, “These include most of physics and chemistry, as well as a few specialties in molecular biology.”  What?  Much of biology, all of chemistry, and all of physics?  Isn’t that pretty much the vast majority of the sciences?  That’s like saying, “Buy any computer operating system you want unless it’s Windows, MacOS, or Linux.”  Additionally, the social sciences are highly grounded in statistics, earth science (hydrology, petrology, seismology) are highly mathematical as well.  The space sciences are a mixture of observational science and mathematical analyses.

                Wilson gives Darwin as an example when he says, “Darwin had little or no mathematical ability, but with the masses of information he had accumulated, he was able to conceive a process to which mathematics was later applied.”  But for every Darwin, there are thousands of scientists at CERN, NASA, NOAA, DOE, and military research labs who apply advanced mathematics to their data every day.

                Then Wilson describes his Principal No. 2, “For every scientist, there exists a discipline for which his or her level of mathematical competence is enough to achieve excellence.”  Although literally true, this is highly deceiving.  The relationship between level of mathematical ability and the number of jobs available to a scientist is like an upside down pyramid.  Sure, if your math skills are weak, there’s a job out there that matches that ability, you just cannot get it because there’s so much competition and so few jobs at that level.  This would be the same as saying that journalists don’t really need to be good writers and “For every journalist, there exists a newspaper for which his or her level of writing competence is enough to achieve excellence.”  Sure, that’s probably true, but the better their writing skills, the better their chance of finding a job.

                I should confess that my degree is in physics, so I might be biased on the mathematical side, but it is clear that E.O. Wilson’s life science bent has biased him in the opposite direction.  Somewhere in between no math at all and 8 semesters of calculus is probably reasonable.