Methodology

How UIChicago works

This page explains what the product is built from, how rankings and summaries should be read, and where students should still verify details for themselves.

Student-builtUnofficialTransparent about signals and limits

What UIChicago is built from

UIChicago combines imported course history, professor review signals, course-to-professor mapping, campus knowledge content, and student workspace tools inside one product. It is student-built and unofficial, so transparency matters more here than pretending to be an official university source.

  • UIC course and grade history used in course pages and rankings
  • Professor review and matching data used in professor pages
  • Campus knowledge content used for planning and Sparky answers
  • Public or imported source material transformed into student-friendly views

How to read course pages

Course pages are designed to help students compare difficulty, GPA patterns, withdrawal patterns, and instructor outcomes without guessing. Metrics are based on stored grade distributions and related registration history where available.

  • Average GPA is calculated from available letter-grade outcomes for the course
  • Pass rate and withdrawal rate are shown from the visible distribution on the page
  • Instructor comparisons are filtered to rows with enough outcomes to be worth showing
  • Course explorer filters help narrow majors, Gen Eds, and requirement types faster

How to read professor pages

Professor rankings use more than a raw star score. The product weighs rating quality, review depth, and available course context so profiles with tiny samples do not look identical to profiles with stronger signals.

  • Review count matters alongside the rating itself
  • Department rank and course rank help add local context
  • Course matching is used so students can jump between professor and class decisions
  • AI summaries are interpretive and should be read as guidance, not as a transcript of every review

How to use Sparky well

Sparky is the synthesis layer. It is best when you want the product to connect courses, professors, campus life, housing, costs, and planning into one answer. It should speed up exploration, not replace judgment for high-stakes decisions.

  • Use Sparky when you want a fast recommendation or summary
  • Open linked course or professor pages when you want deeper evidence
  • Treat time-sensitive, policy, and money decisions with extra caution
  • For official deadlines, bills, and requirements, confirm against official UIC sources

Limits and tradeoffs

No student platform can perfectly represent every class, every instructor, or every student experience. Some courses have richer data than others. Some professors have strong review signals while others are lightly sampled or unmatched.

  • Missing or sparse data can happen on newer or lower-volume courses
  • Professor matches are strong but not perfect in edge cases
  • AI summaries can compress nuance
  • The platform is unofficial and should complement, not replace, official advising or university policy pages