Edit: It's too late to edit my comment, but I noticed an error we have sold ISAs with minimal recourse not at enrollment, but at the point of _graduation_; we would sell half at an extreme discount at graduation (based on likelihood of being hired) and keep half on our books.
If I am interpreting the parent's comment correctly, he's referring to TAs (we called them "team leads") not instructors. Based on the context of the comment I'm assuming that this was a time when we had a TA for every 8 students on top of a layering of instructors for each cohort, and indeed the TAs would do a lot of the 1:1 interaction. There has never been a time we didn't have qualified instructors, though I would readily admit the quality of our instructors has improved over time as we got better at instructional design and hiring.
I love the idea of CIRR but it is largely a failed institution. Their measures have changed dramatically over the years (the last CIRR event anyone at BloomTech attended resulted in the notion that anyone who adds anything new on LinkedIn could be considered "hired," even if it was a portfolio project or self-employment), and are used very differently from school to school, resulting in every major school I know of stopping to work with them.
For example, we used them for our first outcomes report and paid extra to have them "verify" our outcomes report, but they literally never opened the Google Drive file we sent them.
I think it was a great idea set up by well meaning people, but the self-governing aspect and comparisons created ended up in weird incentives that resulted in it falling apart.
The review sites are perhaps marginally better, but the positivity of reviews are almost 100% correlated with how hard schools work to farm for positive reviews, and their business model is selling leads to the schools, so the incentive isn't for objectivity there either.
Honestly the best way, though it requires more work, is to find a handful of recent grads on LinkedIn and ask them about their experience.
We should do a better job of getting more granular on that piece, because it really does matter, but the above isn't the right way to do that math to answer the question prospective students have, and is misleading in the opposite direction. The outcomes report is directed at prospective students who want to understand what will happen to them if they attend the school and look for a job.
You have to remember that (for this outcomes report) nearly every student uses an ISA under which no one is required to pay us unless/until they get a job using the skills they learned. There are a number of people who attend never intending to switch careers, a (large) number who ghost us the day after graduation, and a (large) number who get a job but don't tell us until we get tax returns (so we learn they were hired only after this outcomes report).
Our team works their asses off to work with these students, and is doing everything they possibly can. Slacks, calls, texts, emails, some of which are auto-generated from me personally, and in some cases even physical mail, to try to get them to work with us. If they respond _in any way at all_ with anything other than something that equates to, "I don't want a tech job" they are job-seeking in the outcomes report. We have built tooling to make applying to jobs easier, we find jobs that you should apply to for you, have an outreach generator where our team will write emails to hiring managers for you, and more recently even what we call "job search takeover" where we work with students on resume/portfolio/job criteria in advance, and we will actually do all of the work to fill up your calendar with interviews.
Students who look for a job in any way whatsoever get hired at a very high rate. In my view, if you're a prospective student, that's the information you actually want to understand. The fact that there are a number of students students (most of whom are using ISAs) who never intend to look for a job or don't look for a job is a fair indictment of our business model, but not a fair indictment of the quality of the school or the likelihood of getting hired.
So how should we treat that in an outcomes report? If you're a prospective learner do you want to know about the hiring rate of the people who ghost us or don't intend to look for a job, or do you want to know the hiring rate of people who map to the profile of what you expect to do?
If anyone has ideas of a better way to slice that data to convey the best information to a prospective learner, I would love to hear it.
Hmm, it is interesting to me that sometimes when clear evidence conflicts with an existing mental model it’s easier to create imaginary evidence than to adjust the mental model.
I was not cheering, and my opinion is consistent; as money becomes much tighter companies have to rightsize themselves to the amount of revenue coming in. This is true across Silicon Valley and it is true of us.
"deep learning vs. crypto is a clear divide of math people vs creative people."
> the former offends theorycel aesthetic sensibilities but empirically works to produce absurd miracles
deep learning doesn't seem like it should work to people who are entrenched in theory, but somehow it produces great results.
> the latter is an insane series of nerd traps and sky high abstraction ladders yet mostly scams
crypto is full of interesting technical challenges but mostly produces scams.