The Problem With Most Coding Learning Platforms
I’ve watched developers try to level up their skills using everything from algorithm grinding sites to video courses that promise mastery in 30 days. Most of these platforms treat programming like a multiple choice test where you memorize syntax patterns and hope for the best. The feedback loop is either non-existent or automated to the point of uselessness. You submit code, get a green checkmark, and learn absolutely nothing about whether your solution is maintainable, readable, or something that wouldn’t make your future teammates plot your demise.
Exercism does something different in coding education. It mixes small, focused exercises with actual human mentorship at scale. Think code review for learners, except the reviewers actually want to help you improve rather than just catch bugs before deployment. After contributing to the platform for two years and mentoring hundreds of developers, I think this is how we should have been teaching programming all along.
What Makes Exercism Different
The main idea behind Exercism is pretty simple. Real programming skill comes from writing code, getting feedback from experienced developers, and trying again. Not from watching someone else solve problems or memorizing algorithm patterns. Each exercise follows the same pattern: solve a small problem, submit your solution, get detailed feedback from a mentor, improve your code, and repeat until both you and your mentor are satisfied.
The exercises themselves are well thought out. Take the “Two Fer” problem, which asks you to create a function that returns “One for X, one for me” where X is a name, defaulting to “you” if no name is provided. Sounds trivial, right? But this simple exercise reveals how you handle default parameters, string interpolation, and edge cases. A mentor might point out that using string concatenation instead of template literals makes your code harder to read, or suggest extracting magic strings into constants.
What sets this apart from automated feedback is the human element. Mentors don’t just tell you if your code works. They help you understand why one approach might be more maintainable than another, when to prioritize readability over performance, and how to think about edge cases you missed. It’s like having a senior developer sit next to you and explain their thought process, except it scales to thousands of learners.
Getting Started: Your First Contribution
Contributing to Exercism is straightforward, especially if you’re new to open source. The project needs three main types of contributions: exercises, test suites, and tooling. For beginners, I recommend starting with improving existing exercises rather than creating new ones. This gives you a feel for the platform’s standards and philosophy without having to design problems from scratch.
Start by picking a language track you’re comfortable with and working through a few exercises as a student. This isn’t busy work. You need to understand the learner experience before you can improve it. Pay attention to which instructions confused you, where the tests could be clearer, or what additional test cases might help catch common mistakes.
Once you’ve completed 5-10 exercises, look for issues labeled “good first issue” in the track’s repository. These often involve updating test files to match newer standards, fixing typos in exercise descriptions, or adding missing test cases. The maintainers are really welcoming to newcomers, and the code review process is educational in itself. I’ve seen developers submit their first pull request fixing a typo and end up becoming track maintainers within six months.
Building Exercises That Actually Teach
Creating good exercises is harder than it looks. The best ones feel like puzzles with multiple valid solutions, each revealing different aspects of the language or programming concepts. When I wrote the “Protein Translation” exercise for the JavaScript track, I wanted students to practice working with dictionaries, string manipulation, and error handling, but in a context that felt realistic rather than contrived.
The key is progressive complexity. Early exercises should focus on language fundamentals: variables, conditionals, loops, and basic data structures. Middle-tier exercises introduce concepts like error handling, regular expressions, or working with dates. Advanced exercises might involve algorithm optimization, complex data transformations, or architectural decisions. Each exercise should feel like a natural stepping stone to the next level of complexity.
Test-driven development is built into every exercise. Students get a failing test suite and must implement code to make the tests pass. But the tests themselves are part of the teaching. Good tests work as documentation, showing exactly what behavior is expected and often hinting at edge cases the student should consider. Writing tests that are comprehensive yet readable is an art form, and contributing test improvements is one of the most valuable ways to help the project.
The Mentoring Experience: Teaching at Scale
Mentoring on Exercism taught me more about code quality than years of production debugging. When you have to explain why one solution is better than another to someone learning the language, you have to put into words principles you might take for granted. You can’t just say “this feels wrong” or point to team conventions. You need to explain the reasoning behind it.
The platform has excellent tooling for mentors. You can see the student’s code, their testing results, and their iteration history. The discussion interface encourages detailed feedback rather than quick approvals. Most importantly, there’s no time pressure. Unlike code review in production environments where shipping is the priority, mentoring focuses entirely on learning and improvement.
If you’re considering becoming a mentor, start small. Pick a language you know well and commit to reviewing just a few solutions per week. The time investment is manageable, usually 10-15 minutes per review, and the impact on learners is real. I still get messages from developers who mention that feedback from an Exercism mentor changed how they think about code quality.
Exercism is open source at its best: a project that solves a real problem, welcomes contributors of all skill levels, and creates genuine value for its community. Whether you contribute exercises, mentor students, or improve the platform infrastructure, you’re helping build something that makes programming education more effective and more human. The codebase is well-documented, the community is supportive, and your contributions will directly impact thousands of developers learning to code. Plus, you’ll probably learn something new about your favorite programming language in the process.
