Interviews with Personal Trainers

Email:

Hi ____,

{sentence about how I know you}. I'm a data science educator and one day I realized that I might have a lot to learn from a personal trainer (beyond the obvious of how to exercise). If you could spare 20 minutes of your time, I'd love to talk to you more about some challenges I think we might have in common such as:

• How you remind clients that their goals are attainable
• What you do to be more approachable and less intimidating to beginners
• Your approach to correcting "bad form" without demotivating clients

Let me know if you'd be interested in chatting and I can send you some available times.

Questions

1. How would you describe your job? What motivates you to do it?
2. I worry sometimes that the people that I'm mentoring might feel intimidated by my ability (which I got through many years of practice). I definitely feel intimidated by gyms and the very fit people at them. What do you do to make clients more comfortable?
3. Sometimes I notice a more intermediate learner doing something maybe equivalent to having "bad form" and I worry that pointing it out will feel like nit-picking or that it will derail the lesson and will be demotivating. Have you encountered a situation like that with your clients? How do you approach it?
4. What do you find clients need most—motivation or instruction? How do you balance these?
5. I imagine often when a client comes to you, you see a lot of potential areas for improvement. How do you decide what to focus on first? [Maybe add another question: how do you avoid feeling overwhelmed?]
6. What is your approach when a client's stated goal (e.g. run an 8 minute mile) is something they could do unsustainably once without much learning, but that in order to in a healthy/sustainable way they would need to invest a lot of time in learning good form?

June 24 Christine Morita-McVey

What do you do when a learner has more problems than just what they asked for help with?

A: Give a succinct answer to their question, but ask more about the other things. Where did you learn about this? Why do you do it this way? Then, try to add value by providing evidence-based sources and modeling how to find good information. With something like bad form, break their goal into smaller pieces. Remind learners about their progress, and always incorporate something they're good at or enjoy into practice.

Translation to Data Science

If bad coding practices are really getting in the way of their learning goals, ask questions about where they learned them. Answers might include "Chat GPT told me to do it this way", outdated advice or misinterpretations of adivce, or "well, I was trying to do x, but I don't really know what I'm doing". Discover their motivation for doing things the way they do and suggest alternatives. Follow up with resources where they can learn more, but focus on the question at hand as much as possible.

How to deal with learners who might feel intimidated?

A: Don't speak badly about anyone else's fitness routines—this is not a good bonding strategy. Ask open ended questions, be a good listener. Ask the learner "how did that feel?" rather than jumping to conclusions based on observation and saying "Wow, so much better th is time!".

Translation to Data Science

Similarly, don't speak poorly about anyone's code, coding styles, or programming languges or conventions (i.e. base R vs tidyverse, python vs R). After guiding a learner through refactoring code, ask if they like it better or can understand it better—just because it looks good to you doesn't mean it makes them more comfortable with their code.

How to balance motivation vs. instruction?

A: most clients don't get a lot from cheerleading. Work to connect to the client values, which might take work to discover. E.g. if you think of yourself as a person who goes to the gym 4 times a week, then that's motivation to go to the gym. Refrain from criticism—when clients haven't kept up with exercise, ask why, don't criticise. "Habit stacking"—finding ways to attach fitness to other habits. Easier to do things together (e.g. put vitamin bottle in front of coffee grinder to force the habit of taking vitamins with morning coffee).

Translation to Data Science

Remind learner of or demonstrate the benefits of putting effort into reproducibility and coding best practices. Rather than generic positive reinforcment, get learner to reflect on practical benefits of implementing what they've learned. Regarding "habit stacking"—encourage learners to set up research compendia with all the best practices from the beginning. E.g. create a new github repo, clone it as an RStudio project, create their folder structure and a README.md, and activate renv (mayhbe) before adding data. If all of that stuff is part of the setup, it may be easier to remember to do it. Also, encourage learners to document as they go to make a habit of continually updating documentation and metadata as their project evolves.