UIUC RHET 105: Writing and Research
RHET 105 is UIUC's principal Composition I course: academic writing and research built around a semester-long arc of drafting, peer review, and revision, culminating in a sustained research project. Nearly every undergraduate without exemption credit passes through it in the first year.
Fennie is independent and not affiliated with University of Illinois Urbana-Champaign. This is an unofficial study guide.
What makes it hard
The grade rides on process: drafts, peer reviews, conferences, and revision milestones that can't be reconstructed in a deadline sprint, which is precisely the approach STEM-heavy schedules tempt. The research project also demands real source work (finding, evaluating, and integrating scholarship) that compounds if deferred.
What you'll cover
- • Academic argument and rhetorical awareness
- • The writing process: drafting and revision
- • Research methods and source evaluation
- • Integrating and citing sources
- • Peer review and feedback
The RHET 105 study guide
How to study for UIUC RHET 105, step by step.
- 1
Treat every process deadline as load-bearing
Drafts, peer reviews, and conferences carry grade weight that no final-draft brilliance recovers. Hitting each small milestone is the most reliable strategy the course offers.
- 2
Start the research before the writing needs it
Source-finding and evaluation compound badly when deferred; the research project's real work is upstream of the prose. Build your source base early so drafting draws on it rather than waiting for it.
- 3
Revise to the feedback, specifically
Instructor and peer feedback on drafts is the clearest spec for the final version. Address it point by point; visible, substantive revision is exactly what process grading rewards.
- 4
Master the citation mechanics once, early
Source integration and citation format are steady points lost to carelessness. Learn the required style in the first weeks and template it, so the mechanics never compete with the thinking.
Today
Today's RHET 105 plan
What a Fennie Daily Plan looks like for RHET 105. Yours is built from your own syllabus and adapts every day to your deadlines and progress.
First plan free, no card required. Fennie is independent and unaffiliated with your school.
FAQ
Is RHET 105 hard at UIUC?
Not conceptually; the risk is structural. Process grading rewards steady engagement with drafts and revisions, which a deadline-sprint approach can't reconstruct. Students who hit the small milestones reliably report it as a dependable grade.
Can I test out of RHET 105?
Qualifying AP or other credit can satisfy the Composition I requirement; check UIUC's current placement and credit policies. Most students without exemption credit take RHET 105 or an equivalent sequence in the first year.
How do I do well in RHET 105?
Hit every process deadline, start the research early so sources are ready when drafting needs them, and revise visibly to the feedback you receive. The course grades the process, so steady engagement is the grade.
More UIUC courses
CS 124: Introduction to Computer Science I
CS 124 is UIUC's first programming course for CS majors, taught in Java or Kotlin (students choose), covering programming fundamentals through basic data structures and even Android development. It replaced the old CS 125 and is known for its polished homework infrastructure with daily small assignments.
CS 128: Introduction to Computer Science II
CS 128 is the second course in UIUC's CS sequence, moving students into C++ with memory management, object-oriented design, and an introduction to data structures and software engineering practice. It bridges CS 124 and the heavyweight CS 225.
CS 173: Discrete Structures
CS 173 is UIUC's discrete math course, covering logic, proofs, induction, sets, functions, graphs, and counting. It's the theory foundation for CS 225 and the algorithms coursework beyond. For most students it's their first proof-based mathematics.
CS 225: Data Structures
CS 225 is UIUC's famous data structures course in C++, covering lists, trees, AVL and B-trees, hashing, heaps, disjoint sets, and graph algorithms, delivered through MPs (machine problems) and weekly labs. It's the make-or-break course of the CS major and the one alumni still talk about.