Philip Guo

Philip Guo is an assistant professor of computer science at the University of Rochester. His main research interests are in human-computer interaction (HCI), with a focus on interfaces for online learning. He is also interested in studying how to better train software engineers and data scientists. In 2010, he created a free web-based tool for learning programming called Online Python Tutor, which has been used by more than 1.2 million people in more than 165 countries. In 2012, Guo wrote a popular free e-book called The Ph.D. Grind, which is the first known detailed account of an entire Ph.D. experience. Visit www.pgbovine.net to learn more.

Learning programming at scale

Bringing some of the benefits of face-to-face learning to millions of people without access to an in-person tutor.

Millions of people around the world — from aspiring software engineers to data scientists — now want to learn programming. One of the best ways to learn is by working side-by-side with a personal tutor. A good tutor can watch you as you code, help you debug, explain tricky concepts on demand, and provide encouragement to keep you motivated. However, very few of us are lucky enough to have a tutor by our side. If we take a class, there might be 25 to 50 students for every teacher. If we take a MOOC (Massive Open Online Course), there might be 1,000 to 10,000 students for every professor or TA. And if we’re learning on our own from books or online tutorials, there’s no tutor or even fellow learners in sight. Given this reality, how can computer-based tools potentially bring some of the benefits of face-to-face learning to millions of people around the world who do not have access to an in-person tutor?

I’ve begun to address this question by building open-source tools to help people overcome a fundamental barrier to learning programming: understanding what happens as the computer runs each line of a program’s source code. Without this basic skill, it is impossible to start becoming fluent in any programming language. For example, if you’re learning Python, it might be hard to understand why running the code below produces the following three lines of output:

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A tutor can explain why this code prints what it does by drawing the variables, data structures, and pointers at each execution step. However, what if you don’t have a personal tutor?

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Code Carabiners: Essential Protection Tools for Safe Programming

Assertions, regression tests, and version control

Programming any non-trivial piece of software feels like rock climbing up the side of a mountain. The larger and more complex the software, the higher the peak.

You can’t make it to the top in one fell swoop, so you need to take careful steps, anchor your harnesses for safety, and set up camp to rest. Each time you start coding on your project, your sole goal is to make some progress up that mountain. You might struggle a bit to get set up at first, but once you get going, progress will be fast as you get the basic cases working. That’s the fun part; you’re in flow and slinging out dozens of lines of code at a time, climbing up that mountain step by steady step. You feel energized.

However, as you keep climbing, it will get harder and harder to write each subsequent line. When you run your program on larger data sets or with real user inputs, errors arise from rare edge cases that you didn’t plan for, and soon enough, that conceptually elegant design in your head gives way to a tangled mess of patches and bug fixes. Your software starts getting brittle and collapsing under its own weight.

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