Bootcamp business models, How to tell if you'd like programming, and a conversation with a long-time Bootcamp Instructor
2/24/20 Newsletter
I spent a few days building out a Jupyter notebook exploring the bootcamp business model. I’m excited to share it and describe what I learned in building it.
I’ll also share a story of my own from this week about helping a high schooler decide whether coding is right for them, a link to a nice scrollytelling feature investigating free college, and a great conversation about coding education.
I cut a section on the recent Lambda School news and twitter fight. This post was getting too long, so I’m moving that section to its own post, which should come out tomorrow.
The Bootcamp Business Model
I used Google’s Colaboratory (hosted Jupyter notebooks) and Will Larson’s systems library to model the flow of students (and money) through a hypothetical bootcamp. Better than reading my commentary on it, check out the notebook here.
As I mention in the intro to the notebook itself, you’ll learn more (and have more fun) if you play with the model, instead of just reading. If you model something interesting, send it my way!
Generating insights
I’ve been in and around the bootcamp space for a few years, and have put together a few different unit economics before, in a spreadsheets or notebooks like this. This one has a lot of variables. That provides a lot of interesting ground for experiments, but also means there are ways to make it generate wacky results. Set tuition to one million dollars (doctor_evil_pinky_curl.gif), and see the money roll in!
Having so many variables also opens up many of the gears and levers available to folks designing or running a bootcamp. What business choices do bootcamps get to make? Note that this is a different set than the curriculum or teaching choices - not what language do we teach, but what do we pay for space?
For anyone who is currently working in the bootcamp space or interested in how a bootcamp works as a business, I encourage you to play with the model and the numbers. The bootcamp modeled in the notebook is imaginary, but you can adjust it to the actual or guessed numbers for a bootcamp and use the notebook to make inferences about expenses and revenue, along with a host of other factors.
A few of my insights from working through this model:
The costs at earlier lifecycle stages get multiplied by the drop-off at later stages. For example, the $40 that the model bootcamp spends to interview each applicant turns into $86 per student who ends up graduating and getting placed in a job. Bootcamp unit economics is weird this way.
Given some time between students starting and paying back their tuition, bootcamps take a long time to become cash-positive.
The job placement rate of graduates — the one bootcamps tend to advertise — is different from the “prospective success rate”. Prospective students should count in their chances of graduating. In the bootcamp model, 85% of enrolled students graduate, and 85% of graduates get placed in a job. For a prospective student, this translates to a forward-looking 72% prospective success rate - the average expectation that they will graduate and get placed.
This last point has particularly tricky implications for bootcamp design.
Bootcamps can choose different points in the student journey to place barriers - admissions, gating assessments, graduation requirements, or job-placement eligibility rules. If these barriers filter out students who are less likely to get a job, then a higher percentage of ‘eligible’ students will end up placed in a job. From the student perspective though, getting “filtered” at any stage can be crushing.
Assessments are hard to design well. One reason, hinted at by the business model exploration, is that everyone involved in a bootcamp has a stake in the outcome.
Check out the notebook, and let me know what you find (or if it’s got bugs!)
I’ll continue to refer back to this notebook in future posts, since it should provide a baseline for exploring different bootcamp ideas.
Scrollytelling Free College
The Urban Institute published a cool scrollytelling piece exploring Who Would Get Free College. I _love_ scrollytelling features, especially when they’re well-done like this (this despite a general aversion to scrolljacking, the usability nightmare).
The feature tries to fill in some of the details and implications for some of the public policy options on the table for ‘free college’ - I scare quote because different people mean different things by the phrase.
Takeaways:
There are students who are getting something like ‘free college’ now, and we can base some of our expectations about the future on the experiences of those students
Depending on the details of the policies, different pools of students would shift in number and composition.
Students at public and private colleges have very different financial experiences. These differences would grow under ‘free college’ plans that include 2-year and 4-year public schools, but not for-profit universities.
It’s weirdly important whether students are claimed as dependent on their parents taxes, for determining their eligibility for a ton of existing programs and scholarships. Tax policy things like this always strike me as deeply weird.
It’s hard to tell what students would actually do if a plan like this was enacted - would a lot of students switch from a private to a public school? Would those students transfer to schools that were free to them? Would their credits apply? These kinds of questions might only matter in the transition period, but it’d affect a lot of students.
How to tell if you’d like programming
Last week, my mom called me on the phone for some computer advice. Now, this wasn’t the kind of mom-computer-troubleshooting you might expect. She had two friends whose high-school-age children were wondering about how they’d know if they have the ‘aptitude’ for computer science. In particular, could I recommend any online tools that would help them figure out if this is something they might, potentially, be good at.
Here’s my email response (I sent it to be forwarded, after we hung up on the phone):
Interest is more important than aptitude. The question can be "do I like this?" instead of "am I good at this?". Like other skills, you'll like it more if you're good at it, and you'll get good at it if you like it. There's a virtuous cycle.
Resources:
For trying out coding: https://www.codecademy.com/
For exploring and playing with examples: https://glitch.com/, especially https://glitch.com/@glitch/glitch-team-faves
More exploring and examples: https://repl.it/talk/share?order=votes
Resources for making stuff right away:
For making phone apps from a spreadsheet: https://www.glideapps.com/
For making websites: https://www.squarespace.com/ or https://webflow.com/ or https://wordpress.com/
Making an app or a website is super fun, impressive, and surprisingly easy (with these tools). It can be a hook that gets you curious about the rest of the software world, which in turn will keep you interested and learning.
For a narrative example of what the learning journey might look like, you should read Tania Rascia's post about her learning journey.
More tips and thoughts:
Coders are not different than other people. Coding is not different from other skills. Getting good takes time, attention, and practice, like anything else.
Like most things, coding is more fun with friends. Learning with other people is easier than learning alone.
Unless you're getting paid, coding should be fun. It's sometimes confusing, frustrating, or overwhelming, which is less fun - but very normal, so don't give up on yourself if you hit a dead end. Build things you are excited or curious about!
Feel free to forward this, and feel free to reach out to me over email - rob@cs-ed.com. I love to talk about this stuff, and I'm happy to answer questions or point towards other resources!
Interest beats aptitude. In the words of John Ousterhout, (related to me by Andrew Kortina)
A little bit of slope makes up for a lot of y-intercept
Still, as mentioned in last newsletter’s segment on Learning in Public and the prior posts’ section about Learning Roadmaps, the content out there is overwhelming. Bootstrapping knowledge of the roadmap is hard, because it takes specialized understanding to see how the different pieces add up or fit together.
If you’ve got other resources I can send to my mom (or parents in her friends’ position), send me a note!
And a conversation with a long-time Bootcamp instructor
Kyle Coberly, Flatiron Instructor, formerly of Dev Bootcamp (RIP) and Galvanize, speaking to the Denver Node.js Meetup.
I really like the format - lots of topics, each time-boxed, which means that Kyle got to cover lots of interesting ground about bootcamps, code teaching, code learning, and education in general.
Kyle focuses on ‘Getting Wins’ and ‘Hooks into further learning’, which are key. To stay engaged, students need emotional - not just cognitive - connection. In coding education, that translates to building something they’re excited about and sharing the experience with a community.
Tomorrow, I’ll have a post about the recent Lambda school news, and then we should be back to regularly scheduled newsletters.
Thanks for reading!