My Best Study Strategy by Anthony

My Best Study Strategy by Anthony - September 2026 Scholarship Essay

My best study strategy is to treat every assignment like a small production system: define the goal, break it into shippable pieces, and verify each piece before moving on. In Computer Science at Colgate, that means reading the problem until I can restate the constraints in my own words, writing a tiny example by hand, then coding only after the example works. When I get stuck, I isolate one failure instead of rewriting everything. That habit saves hours and keeps me from confusing activity with progress.

The method came from scarce time. As a first-generation QuestBridge student balancing coursework, founding Raider Marketplace, and software engineering internships at BMO and Octave/Hexagon, I could not afford long unstructured study. Short focused blocks beat marathon cramming. I write down what failed, why I think it failed, and the next test that would prove a fix. If I cannot explain the next test, I do not understand the bug yet. Teaching a concept back to myself, or to a teammate, is the final check that the idea is solid enough to use under pressure.

I use the same loop for systems courses and for personal projects. For data structures and algorithms, I start with a clear input and output example before I touch an editor. For computer systems, I trace one failure path instead of guessing at the whole stack. On Raider Marketplace, we shipped React and iOS clients to more than 100 active users by iterating in small releases: listen to what students needed, ship a thin version, measure what broke, then fix that one thing. Study and building use the same muscle.

Studying abroad at Yonsei University this fall with a Gilman STEM scholarship uses the same approach in a new environment. New language context, new professors, and new tools make it tempting to feel behind. The strategy keeps me oriented: prepare early, ask precise questions, and ship daily progress I can point to. Higher education works best for me when learning is treated like engineering: honest debugging, clear requirements, and delivery that another person could follow.