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I Couldn’t Finish My Book, So I Enlisted a Sports Psychologist

I recently came across a TED talk by Mihaly Csikszentmihalyi from Claremont Graduate University. I learned of Prof. Csikszentmihalyi’s work a few years ago, when I was struggling to finish my second book. It was part of a formative professional experience that influenced both my work and my career advising. I spoke about the experience in an episode of The Annex with Clayton Childress from the University of Toronto:

Here’s the story:

I was working on my 2017 book and hit a writer’s block that needed overcoming if I were going to finish it. There are times when you are in the zone and can produce page after page of great writing. Then there are others where your writing is garbage, and it is hard to get out a paragraph.

I reasoned that my situation was very similar to an athlete who has a hot hand versus one who is in a slump, and went to a sports psychiatrist to ask how he would treat me if, say, I were a pitcher who couldn’t hit the strike zone or a basketball player who freezes when he makes a free throw.

He told me that he often refers patients to the work of Csikszentmihalyi’s (1990) Flow: The Psychology of Optimal Experience. For me, the big take-away was this: Were I a pitcher, Csikszentmihalyi’s approach would advise me to enjoy the experience of the pitch, and to concentrate on each thrown ball, and to block out the batter, the inning, and all that. Being in the zone is a form of immersion into an activity where your mindset becomes focused on and develops a rhythm to the most basic elements of the activity. Throwing a baseball in pitching. Writing paragraphs in writing.

Here’s the TED talk for more:

This experience was formative for me in both my approach to work and my advising of students. It is very important to enjoy the immediate experience of the tasks involved with one’s job, and one can lead a pleasurable life if one is happy to jump into the day-to-day of their job on a regular basis. For me personally, it encouraged me to shed projects that I didn’t like and didn’t feel were rewarding, and to invest in things that may not be conventionally valued but were things that I did well, loved, cared about, and enjoyed.

For students who come to me seeking career advice, I tell them to spend their twenties and early thirties finding a place in the world that suits their natural dispositions and involves tasks that they enjoy doing. I strongly believe that it is possible to enjoy a comfortable, rewarding livelihood in any line of work, so long as you are really good at it. And you can’t get really good at something unless you are doing it day in and day out. And you can’t do something day in and day out if you don’t like doing it.

Photo Credit. Bain News Service, Publisher. Eric Erickson, pitcher, Detroit AL baseball. , 1917. Photograph. https://www.loc.gov/item/2014701275/.

Avoid Starting Out by Chasing the Latest Hot Thing

I’m passing along an excellent post by Terence Shin that I caught on the data analysis blog KDnuggets. Mr. Shin’s post speaks to those of you who have a great enthusiasm for the latest hot thing in data analysis — the skills or tools that are being discussed on the blogs and in the press. Currently, one of these hot things is machine learning. There is always something.

Read the post yourself. It is very well done. Its key points are: (1) Machine learning (or any hot thing in data analysis) is only one part of the toolkit that you will have to wield to solve real-world problems, and (2) A proper engagement of machine learning (or any advanced skill) requires an understanding of foundational skills.

To my mind, learning data analysis is similar to learning any occupational skill. It is not altogether different from learning to be a craftsperson, like an electrician or carpenter. One group of trainees learns how to wire a house, and another learns to translate raw data into information to support decision-making. It is possible to write and execute scripts to perform highly-complicated statistical operations using documentation and web searches, much like I could perform a do-it-yourself rewiring of my home by watching YouTube videos. However, as you gain practical experience in this field, you will find that there is much more to the job than knowing how to wield the most complicated piece of equipment.

This kind of learning strategy seems likely to hinder students’ overall development as data analysts. Start by mastering learning basic tools to solve simple problems, and work your way up to more complex problems and more sophisticated tools. This strategy puts you in the position of a problem-solver and question-answerer, and something more than a programming tech. I think such a strategy is more likely to result in you being a competent entry-level analyst upon graduation.

That being said, I do not want to discourage students from experimenting with stuff while they are learning. That passion will keep you pushing your boundaries and learning over your career, because there is plenty to learn over a lifetime (I’m still learning). Do not extinguish that passion. Just make sure that you don’t become over-focused on this or that method to the detriment of becoming a solid analyst with a good grasp of their toolkit.

Photo Credit. Johnson, Paula J, and Michael Crummett. Wheelwrights and cartwrights Dale Thibault and Harvey Howes, Miles City, Montana. United States Miles City Montana, 1979. Miles City, Montana. Photograph. https://www.loc.gov/item/afc1981005_01_22928/.

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