Lambda School run into the realities of education economics.
As a society, we decided to subsidize high performers so they can actually focus on building/researching things and securitize everyone else.
The fact of the matter is educating high performers is cheaper short term( they teach themselves and process information better) and exponentially more valuable long term (they get good jobs, go into business or lead lucrative fields)
If we sort out people based on similar ratings as applied to bonds, Lambda school works with Cs. It doesn't mean that everyone is bad, it just means on average the level of people is bad. All A people are picked by good unis via scholarships. B people can't get a scholarship but have good enough grades to get into B schools and pay via a loan or via relatives.
Lambda School is focusing on everyone else, but hopefully, there is a lot of everyone else.
The model should have been on looking at Cs and separating good Cs from bad Cs. A good C is normally a student that didn't have opportunities or environment to become A, but have innate ability to do so, given the opportunity and resources.
If you don't really have the tools to distinguished good Cs from bad Cs, you can enroll as many people as possible and hopefully RNG your way to success. The problem with that strategy is that a lot of bad Cs will be unhappy with job outcomes, struggle with courses, generate bad press impacting recruitment, and more importantly be a massive drain on teaching resources.
I still think Lambda School is onto something but trying to do this via hypergrowth focused VC funding is a challenge.
On another topic, the hack I use in recruiting people who didn't have the opportunity to learn CS is to ask them to do CS50 in their own time. About 90% of people never come back, about 5% start but never finish or take too long to finish, and about 5% knock it out of the park. Those 5% generally were always worth my time advising and if we were lucky working with them. It doesn't mean they will become rockstar programmers, but it means they have learning ability and with enough time and resources will become a net positive to the company in a variety of engineering and engineering adjacent roles.
As a society, we decided to subsidize high performers so they can actually focus on building/researching things and securitize everyone else.
The fact of the matter is educating high performers is cheaper short term( they teach themselves and process information better) and exponentially more valuable long term (they get good jobs, go into business or lead lucrative fields) If we sort out people based on similar ratings as applied to bonds, Lambda school works with Cs. It doesn't mean that everyone is bad, it just means on average the level of people is bad. All A people are picked by good unis via scholarships. B people can't get a scholarship but have good enough grades to get into B schools and pay via a loan or via relatives.
Lambda School is focusing on everyone else, but hopefully, there is a lot of everyone else. The model should have been on looking at Cs and separating good Cs from bad Cs. A good C is normally a student that didn't have opportunities or environment to become A, but have innate ability to do so, given the opportunity and resources.
If you don't really have the tools to distinguished good Cs from bad Cs, you can enroll as many people as possible and hopefully RNG your way to success. The problem with that strategy is that a lot of bad Cs will be unhappy with job outcomes, struggle with courses, generate bad press impacting recruitment, and more importantly be a massive drain on teaching resources.
I still think Lambda School is onto something but trying to do this via hypergrowth focused VC funding is a challenge.
On another topic, the hack I use in recruiting people who didn't have the opportunity to learn CS is to ask them to do CS50 in their own time. About 90% of people never come back, about 5% start but never finish or take too long to finish, and about 5% knock it out of the park. Those 5% generally were always worth my time advising and if we were lucky working with them. It doesn't mean they will become rockstar programmers, but it means they have learning ability and with enough time and resources will become a net positive to the company in a variety of engineering and engineering adjacent roles.