N.S.’s small language project revealed questions worth pursuing.
N.S. had strong coding credentials, but his interest in language barely appeared. We helped him turn relatives’ feedback on a pronunciation tool into a more personal account of how he learns.
The starting point
A CBSE student in India applying internationally for the first time
Academic interests
Computer science, linguistics, and human-computer interaction
An anonymized student journey, shared with initials.
AI-generated illustration, not a photograph of N.S.
His technical record left out the people behind the project.
N.S. built a simple pronunciation tool for younger cousins. His application emphasized grades and coding while barely mentioning the family experiences behind his interest in language.
HOW WE HELPED
We connected his technical work to a specific question: how software responds when real people speak, hesitate, and switch languages.
Family life gave his language interests a beginning.
Translation and conversations at home helped explain why linguistics belonged beside computer science, rather than appearing as a new application theme.
A small project gave him real feedback.
Fewer than thirty people had used the tool. Their responses gave him useful design questions even without a large audience.
His family wanted a recognizable path after graduation.
His parents were considering a substantial international expense and wanted to understand how his interests related to a computer-science education.
INSIDE THE PROJECT
User confusion became more revealing than the user count.
Testing with relatives showed N.S. a gap between instructions that seemed obvious to him and the way people actually used his tool.
THE EXPECTATION
He thought the prompt was easy to follow.
The tool offered pronunciation practice in two languages, but his own understanding of the instructions did not predict everyone else’s.
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THE FEEDBACK
Relatives responded in ways he had not expected.
Some ignored prompts. Accents challenged the model, and certain corrections felt discouraging rather than helpful to the people using it.
→
THE LEARNING
He began asking better questions about usability.
The essays explored listening, language, and the weaknesses those interactions exposed, making his technical interest more understandable and personal.
LETRADO’S ROLE
We helped him develop those testing scenes and describe the tool’s capabilities accurately. N.S. kept control of the code, examples, and writing.
HOW WE WORKED TOGETHER
Specific evidence connected his interests without narrowing them.
The project, essays, and school research needed to tell the same story. Family discussions also needed space for practical concerns about studying abroad.
The project became clearer at its real scale.
We helped him document what the tool could do, name its limitations, and use the feedback that exposed weaknesses in his design.
Describing the work accurately
The application replaced broad platform language with the actual user count and functionality. Claims of demonstrated learning impact were removed because the tool had not been formally evaluated.
His essays connected coding with curiosity about people.
We developed scenes from testing with relatives, showing how language and usability questions emerged from work he had actually done.
Finding a personal academic connection
The application asked how software handles speech, hesitation, and switching languages. That connection made his interest in linguistics concrete rather than a last-minute label.
Degree research made the family discussion more useful.
N.S. compared computer science, linguistics, independent work, and breadth requirements, while addressing his parents’ questions about degree structures and career paths.
Comparing possible routes
His parents received a clear comparison of academic structures. N.S. made the final preference order, and the family discussed possible admissions outcomes before decisions arrived.
Princeton gave him room for computing, language, and independent work.
N.S. compared three offers with his academic interests in view. He chose a combination of computer science, access to linguistics, and independent study.
Computing and language could stay connected.Access to linguistics alongside computer science matched the questions that had grown out of his work with relatives.
Independent academic work mattered to him.He wanted room to pursue questions of his own, making Princeton’s independent work part of the final comparison.
A small project can lead to substantial questions.
Start with what you observed, not how impressive the project sounds. Real feedback can help you explain both your interests and how you respond when something surprises you.
What did someone do that you did not expect?
Describe a real interaction with your work. Explain what it revealed about the user, your assumptions, or the problem itself.
What can you show your project actually does?
Use concrete capabilities and honest scope. A small, well-explained project can tell a reader more than an ambitious label.
Where could your interests develop together?
Compare courses, independent work, and the freedom to cross departments. Explain the connection through your experience rather than a borrowed academic phrase.
Bring the questions you are still working through.
Meet your proposed mentor in a free 45-minute introduction. We’ll talk about what would help and send a personalized plan by email afterward.
