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Great stuff Ammon and team! Can you discuss how you might test for bootcamps overfitting their curriculums to interviews? They definitely would seem financiall

by dtran 10y ago

Great stuff Ammon and team! Can you discuss how you might test for bootcamps overfitting their curriculums to interviews? They definitely would seem financially incentivized to do just that. From a personal anecdote, someone I interviewed was able to code a solution for a problem, but then couldn't discuss how or why they did it that way at all, or solve a closely related problem, which made me strongly suspect that they just memorized an answer. How would you test for this? I would also be curious to see if there was any way to breakdown bootcamp grads with previous programming experience vs. without and by what they studied in undergrad if they went to undergrad.

ammon 10y ago
Interesting questions. Bootcamps are clearly incentivized to do this. However, they do not seem to be particularly good at it. Algorithms are over represented in interviews relative to most jobs, and yet (as our data shows) bootcamps are not very good at teaching this. Now, we are measuring algorithmic skill by asking candidates to actually implement non-trivial algorithms. We've observed that a lot of interviews involve what is essentially trivia about algorithms, and it's possible that the bootcamps are better at preparing students for this (we don't measure this skill so I am not sure). I think that this gets at the answer. If you make your interview go deep, it gets increasingly hard to specifically prepare for it, to that point where preparing is actually becoming a better programmer. Rather than a 30-minute question that covers knowledge of sorting algorithms (easily learnable), have your candidate spend an hour building a collision detection systems using a axis-sorted list of rectangles, and reason about maintaining this sort as objects move around. That's the theory. In practice there will always be some noise.

by dtran 10y ago

ammon 10y ago

Interesting questions. Bootcamps are clearly incentivized to do this. However, they do not seem to be particularly good at it. Algorithms are over represented in interviews relative to most jobs, and yet (as our data shows) bootcamps are not very good at teaching this. Now, we are measuring algorithmic skill by asking candidates to actually implement non-trivial algorithms. We've observed that a lot of interviews involve what is essentially trivia about algorithms, and it's possible that the bootcamps are better at preparing students for this (we don't measure this skill so I am not sure). I think that this gets at the answer. If you make your interview go deep, it gets increasingly hard to specifically prepare for it, to that point where preparing is actually becoming a better programmer. Rather than a 30-minute question that covers knowledge of sorting algorithms (easily learnable), have your candidate spend an hour building a collision detection systems using a axis-sorted list of rectangles, and reason about maintaining this sort as objects move around. That's the theory. In practice there will always be some noise.