Over the last semester, I explored how automation can improve the way we track and evaluate student projects, especially in structured programming courses like OOP.
The challenge: Manually reviewing dozens of GitHub repositories, tracking submission dates, verifying file structures, and organizing feedback across multiple classes.
The solution: I built a workflow with n8n, the open-source automation tool, that:
Pulls data from student GitHub repos (via API)
Analyzes key project files and folder structure
Flags missing components (e.g. missing class implementations)
Automatically labels each repo by topic focus (e.g. inheritance, polymorphism)
Generates a summary report in Google Sheets or Notion
Notifies me when new pushes are made after deadline 🚨
🧠 Why it worked so well for OOP:
The automation helped highlight how students applied principles like encapsulation and modular design. I could spot which projects followed proper class hierarchies — and which ones turned into spaghetti 😅
Bonus: I had real-time visibility into class-wide patterns (e.g. 65% didn’t implement abstract classes correctly) — which helped adjust lectures and review materials.
Tools used:
n8n (self-hosted)
GitHub API
CoderByte
Google Sheets
This was just a prototype — but it sparked real excitement about using workflow automation in education.
If you're managing technical coursework — or just curious about automating code review workflows — I highly recommend giving n8n a try.
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