From choices to better questions.

STEP 1

Uncover a student preference profile

The quiz presents 30 concrete situations and meaningful tradeoffs rather than asking students to name abstract preferences. Options contribute positive or negative evidence across 15 dimensions, including intellectual culture, faculty closeness, collaboration, curricular freedom, experiential learning, community closeness, social energy, urban and outdoor access, support structure, and career orientation.

Scores are normalized to a five-point scale. Dimensions supported by stronger or more distinctive answers receive more weight later. “None of these” responses can be preserved in the downloaded report but do not force the student into an unrelated category.

STEP 2

Discover fitting college environments

Each school has a structured profile across the same dimensions. The strongest school-specific claims are grounded in reviewed institutional evidence; records that remain incomplete after bounded research retain an explicitly quarantined legacy fallback rather than being presented as newly validated. The model calculates distance between the student and school on every dimension, giving more weight to the preferences that are furthest from neutral. Academic-interest signals can add a small bonus when they overlap with programs represented in the corpus.

The resulting fit score is used only to order possibilities within this student’s result. It is not an objective rating, national percentile, probability, or measurement to compare across students.

EVIDENCE STANDARD

Look for structures students can actually experience

Community closeness, faculty closeness, and support structure receive a stricter evidence treatment because reputation, enrollment size, and the mere existence of a program can be misleading. Community closeness asks whether durable, bounded peer communities exist and how broadly they reach. Faculty closeness looks for recurring, meaningful faculty contact - not ratios alone. Support structure examines the breadth, coordination, proactive intervention, and demonstrated reach of student services.

Official institutional pages are converted into controlled claims about mechanism, reach, duration, recurrence, and engagement. Plausible candidates advance to independent blind review, where the reviewer evaluates the supplied context rather than trusting a machine label. Missing evidence never becomes a low score, and a one-time event, award announcement, ordinary course, or generic promise does not establish a durable environment.

STEP 3

Add planning context without redefining fit

A separate section asks about GPA band, course rigor, testing, activity depth, residency, and aid priorities. These answers never alter the preference profile. They only help organize otherwise strong fits into broad research categories.

When reliable data are available, the assessment considers institutional selectivity, federal admissions references, testing policy, and residency effects. These labels are context - not admission probabilities. Exceptionally selective schools remain High Reach even for students with exceptional academic context. Unknown scores are not treated as low scores.

STEP 4

Construct a balanced research report

Recommendations are divided into Best Fits, Aspirational Fits, Great Value, and Hidden Gems. A school can appear only once. Great Value requires applicant-relevant aid context. A Hidden Gem is a less-obvious college with an unusually strong fit for this student’s preferences - not a claim that it is universally underrated. Minimum-fit rules prevent groups from being filled with weak possibilities.

For clearly developing academic profiles, the report may include at most one exceptionally selective school, only as an unusually strong Aspirational fit. This preserves room for ambition without crowding out attainable research options.

Each school includes an explanation grounded in the student’s preference signals, a possible tradeoff when one is evident, and links to the institution and its Niche profile for further exploration.

DATA & LIMITATIONS

Sources, freshness, and appropriate use

The 1,000-school corpus combines curated institutional profiles, federal College Scorecard data, and bounded official-source research. Federal references include admission rates, test ranges, test requirements, net price, costs, and other public fields where available. Direct institutional sources are preferred for policies and student-experience structures that cannot be responsibly inferred from aggregate data. Review the corpus coverage and remaining gaps.

College data change. Programs close, testing policies shift, costs rise, and financial-aid practices evolve. The application records provenance and review status where available, but students must verify current information directly with colleges.

• The model does not calculate admission probabilities.
• Fit scores should not be compared between different students.
• Financial-aid notes do not estimate an individual award or net price.
• Some dimension records retain quarantined legacy fallbacks because current official evidence was incomplete or unreachable.
• The corpus is intentionally broad but is not every college in the United States.
• Human priorities - including disability support, family needs, identity, safety, and lived experience - may require research beyond the current quiz.

The recommendation system is covered by deterministic regression and simulation tests. These tests check category integrity, repeated-school concentration, unusually selective recommendations, missing explanations, and stability across profile changes. Testing reduces obvious anomalies; it does not turn subjective fit into an objective fact.