How brain-dead are they?
It takes 10,000 hours to master something. At least that's the claim by Malcolm Gladwell in his book Outliers. There, he states that, 'the key to achieving world-class expertise in any skill, is, to a large extent, a matter of practicing the correct way, for a total of around 10,000 hours'. Before you quickly hit the reply or unsubscribe button, you can watch a conversation with Mr. Gladwell explaining himself and providing context for what he meant. Also, you can watch a video where Mr. Bill Gates reflects on the same.
And if you want to read more, here is a study that questions this 10,000-hours theory. The 10,000-hours rule tries to, in simple terms, illustrate that to be good at something, you have to work hard for a long time. After you’ve gone through the links I just shared, you’ll also learn that it helps to have talent, good teachers, imagination, and motivation.
This 10,000-hours rule flashed through my mind when I came across an article, 'AI helps students skip right to the good stuff in this intro programming course,’authored by Leo Porter, University of California, and by Daniel Zingaro, University of Toronto.
Let me provide you with a few examples from this article about this “ground-breaking” new way of learning:
What prompted the idea for the course? Generative AI is really good at computer programming – to the point where the way we teach and assess students who are learning to program must change. We used to give students dozens or hundreds of small targeted programming tasks, drilling each aspect of the syntax – the words and symbols – of programming. That worked well as a starting point, except now generative AI tools can solve all of these problems.
What does the course explore? The more students struggle with finicky syntax details, the less time and energy they have to accomplish their programming-related goals like starting a business, writing apps for social good, or contributing to projects that are meaningful to them.
Why is this course relevant now? Professional programmers in droves have already adopted generative AI tools and are using them to be more efficient in their daily work. If the goal is to prepare students for these jobs, teachers need to train them in how to use these new tools.
What will the course prepare students to do? The majority of students in the course, though, are studying other disciplines like sociology, psychology, business, engineering, and science. The course prepares those students to use generative AI to boost their careers through programming.
Reading the above, brought another quote to my mind. This time from George Bernard Shaw, 'Those who can, do; those who can’t, teach.'
The level of misinformation and trivialization is breathtaking. Let's start with the first bullet point. The claim that AI is really good at computer programming, as referenced in this study from McKinsey. However, when you read the study, it’s clear that they are cherry picking the data. While the researchers admit there are some developers who can save time on common tasks, they clarify later that these time savings vary significantly based on the complexity of the task and the individual developer’s experience. In fact, in some cases, junior developers would take 7 to 10 percent longer with these AI tools than without them.
The next statement asserts that learning the finicky aspects of the syntax of a program (you know, all the words and symbols), takes time away from finishing their glorious goals. This suggests that learning the basics about anything is a waste of time which prevents us from doing social good. It also nicely translates to other professions. Doctors, musicians, and athletes – to name a few – can all benefit from this approach. Why would you need to know every bone or every note? Let AI handle the details and you can just focus on the brain surgery. You focus on the big picture – winning.
Next, the premise that professional programmers have already adopted generative AI tools to be more efficient is presumptuous. Since the authors of this article never worked as 'professional programmers', perhaps only reading about them, it suggests that they used another study to confirm their narrative. Using ChatGPT to fill out forms and create documentation, perhaps. Here is a review from a real professional programmer about an AI tool with a conclusion, 'Copilot can be a crutch if you rely on it too much. It is important to remember that Copilot is not a replacement for your own programming skills.' He also says, 'Emphasizing hands-on learning and practice is still crucial for a comprehensive understanding of programming concepts and languages.'
The way this course is presented only provides the students with misplaced optimism that they will learn anything about programming, when really they won’t. When put it on their resume, it will lead to embarrassing moments during an interview. If you really want to learn about programming and the concepts without the 'finicky syntax details', get Raspberry Pi and learn Scratch.
There is nothing wrong with exposing students to the latest and greatest humanity can offer; new tools help ignite the imagination and provide possibilities on how to apply them to make things better. Creating shortcuts with courses like that will only enforce the delusion that we can replace teachers with AI. A recurrent pattern which is a concept Messrs. Porter and Zingaro might find it difficult to accept.