What Not To Do
12 Things Fatima Hassan Should Avoid in Her College Application Process
Fatima, your strong academic record and clear interest in Linguistics and Computational Linguistics already position you well. However, the most selective programs—especially at institutions like MIT—expect precision, context, and depth. Below are twelve pitfalls that could weaken your application if not carefully avoided. Each reflects patterns the committee flagged as potential risks for students with similar academic profiles.
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Do not rely on GPA alone to demonstrate rigor.
Your 3.92 GPA is excellent, but admissions officers will look beyond the number to evaluate the difficulty of your coursework. If you do not specify whether you’ve taken honors, AP, IB, or dual-enrollment classes, they may assume a lighter course load. Be explicit about advanced courses in math, computer science, or linguistics-related subjects. Avoid leaving the reader to guess what your GPA represents in context.
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Do not describe research in generalities.
If you’ve engaged in any linguistic or computational projects, avoid phrases like “I did research on language models” without explaining what you actually produced. Committees want to see measurable outcomes—datasets analyzed, algorithms tested, or papers drafted. Without tangible evidence, even genuine research can appear superficial. If you have not yet undertaken research, acknowledge that gap rather than implying experience you cannot substantiate.
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Do not skip technical specifics in your narrative.
For a computational linguistics applicant, omitting technical detail is a major red flag. Avoid statements like “I enjoy programming” without naming languages, frameworks, or problems you’ve tackled. The committee needs to see readiness for quantitative and computational coursework. Lack of specificity can make your interest seem theoretical rather than applied.
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Do not assume your SAT score speaks for itself.
Your 1520 is strong, but for technical programs, committees still examine section breakdowns and evidence of math fluency. Avoid presenting the score without context or reflection. If you plan to retake or submit additional standardized tests (e.g., AP or IB exams), clarify that in your materials to show continued academic engagement.
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Do not leave extracurricular or project information blank.
You have not provided your activities list yet. Leaving this section incomplete signals disengagement beyond academics. Even if your focus has been academic, note any relevant independent learning, language study, or coding work. Avoid the impression that your interests exist only in the classroom.
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Do not use filler language in essays.
In essays, avoid phrases like “I’ve always loved language” or “Since I was young.” These clichés dilute authenticity. Instead, focus on specific turning points or challenges. Committees can detect generic writing quickly, and it can overshadow your intellectual precision—especially important for a linguistics applicant.
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Do not overlook the computational side of your intended major.
For Computational Linguistics, failing to show comfort with data, algorithms, or coding will raise concerns. Avoid presenting yourself solely as a humanities student. Without technical context, even strong linguistic analysis may seem incomplete. Show balance—linguistic theory paired with computational methodology.
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Do not let recommendations speak only to general traits.
Letters that focus on being “hardworking” or “curious” without referencing analytical or technical ability won’t help much at schools like MIT. Avoid choosing recommenders who cannot speak specifically to your quantitative or linguistic strengths. Encourage them (politely) to include examples of your problem-solving or data analysis work.
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Do not delay clarifying your course context.
If your transcript or school profile doesn’t clearly show course rigor, committees might underestimate your preparation. Avoid assuming that the admissions reader knows your school’s grading scale or course options. Provide context in your additional information section if necessary—especially for advanced math, computer science, or language courses.
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Do not let your writing sample or portfolio lack structure.
If you plan to include a writing or coding sample, avoid submitting something that lacks annotation or explanation. Committees need to see both your analytical reasoning and your ability to communicate results. A technically sound but poorly explained project can undermine your strengths in linguistics, where clarity of argument matters.
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Do not ignore school-specific application nuances.
Each of your target schools—MIT, West Chester University of Pennsylvania, and the University of Minnesota–Twin Cities—has different expectations for supplemental materials. Avoid reusing the same essay or assuming one format fits all. For instance, MIT’s short-answer prompts emphasize initiative and problem-solving, while Minnesota may focus more on academic fit. Overgeneralizing your responses can make your application appear recycled.
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Do not postpone documentation of your progress.
Waiting until senior fall to gather transcripts, recommendation details, or project summaries can lead to rushed or incomplete submissions. Avoid assuming you’ll “fill in the details later.” Begin organizing your materials now, even if some sections (like research outputs) are still in progress. Incomplete documentation often signals lack of follow-through—something committees notice quickly.
Common Patterns to Watch For
Across these twelve areas, three recurring risks stand out:
- Insufficient context: Numbers (GPA, SAT) without narrative or course detail weaken perceived rigor.
- Vagueness in technical or research claims: Avoid general statements that lack verifiable outcomes or data.
- Underdeveloped computational dimension: For a linguistics applicant with computational focus, missing evidence of coding or quantitative preparation can misalign your profile with your intended major.
Mini Calendar: Avoidance Checkpoints (Next 6 Months)
| Month | Key “Don’t” to Watch | Action to Prevent It |
|---|---|---|
| March | Don’t rely on GPA alone. | Gather course descriptions or counselor notes showing rigor. |
| April | Don’t describe research vaguely. | Outline any ongoing projects; note measurable outputs or data sources. |
| May | Don’t omit technical details. | List programming languages, analytical tools, or coursework relevant to computational linguistics. |
| June | Don’t leave activities blank. | Compile all extracurriculars, even informal or self-directed learning. |
| July | Don’t use generic essay language. | Begin drafting essays with specific turning points; see §06 Essay Strategy for approach. |
| August | Don’t postpone documentation. | Finalize transcripts, recommendations, and project evidence before senior year starts. |
Final Perspective
Fatima, avoiding these twelve pitfalls will help your application communicate precision, depth, and academic authenticity. The committee’s main concern isn’t your ability—it’s whether your materials will reflect the full scope of your preparation. By steering clear of vagueness, unsupported claims, and missing context, you’ll ensure that your 3.92 GPA and 1520 SAT translate into a compelling, evidence-based narrative of readiness for linguistics and computational study.