Work
Course Pilot
TL;DR
Exploring how AI could make course planning less overwhelming for students. Prototyped Course Pilot, an AI supported course planning assistant that helps students consolidate course information, understand peer insights, and connect classes to academic and career goals.
Course planning asks students to make important decisions
with fragmented information
Students often have to jump between course catalogs, degree requirements, advisor input, peer advice, and career goals just to understand whether a course was the right fit. This made enrollment feel stressful and uncertain, especially when students were balancing workload, interests, requirements, and long term goals.
We spoke with 15 students and advisors and found that...
Course planning is not just a scheduling problem. It is an information gathering problem.
Students care about career relevance, but they often do not know how to evaluate it.
Trust regarding AI depends on transparency and control.
Real peer feedback matters more than official descriptions.
Opportunity in the existing landscape
Students have plenty of existing resources but are surrounded by fragmented information across official systems, planning tools, peer reviews, and advisors. Each source helped with part of the decision, but none brought logistics, lived student experience, career relevance, and personal constraints into one planning workflow.
| User need | Official CMU systemsSIO, course catalog | Planning toolsStellic, Coursicle | Peer insight sourcesRate My Professor, friends | Advising resourcesAcademic advisors | MVP |
|---|---|---|---|---|---|
| Course availability | Supports | Supports | Does not support | Partial support | Supports |
| Workload | Partial support | Partial support | Supports | Partial support | Supports |
| Career relevance | Does not support | Partial support | Partial support | Supports | Supports |
| Part of existing planning flow | Supports | Partial support | Does not support | Does not support | Supports |
| Personalized to user goals | Does not support | Partial support | Partial support | Partial support | Supports |
We identified 15 viable concepts and picked 3 to explore further
A web tool that turns long syllabi into structured summaries so students can quickly understand workload, deliverables, and expectations.
A dashboard that maps how skills develop across semesters based on planned coursework and career interests.
A sidebar that lives alongside the CMU registration page and surfaces course summaries, match scores, reviews, and quick actions while students are already planning.
We chose the AI course planner after showing our prototypes to users and analyzing how the three ideas matched user need. The sidebar fits directly into the registration workflow and supports quick comparison, recommendation, and action.
Final MVP
User logs in and fills in their target career, skills, resume, and available times.
- Personalize recommendationsStudents add career goals, skills, resume context, and availability.
- Explore matchesCourse recommendations pair AI descriptions and match rates with the planning workflow.
- Learn from peer reviewsStudents can search prior course reviews before deciding.
- Contribute backReview contribution creates a growing peer-insight loop.
Impact & Validation
Course Pilot surfaced appropriate courses for both STEM and arts oriented goals, showing that the system could respond to different student pathways.
By centralizing course context, skill alignment, and peer insight, the prototype reduced course search time by around 50% during testing.
Relevant courses were consistently found, though some strong matches appeared lower in the list, pointing to ranking refinement as a next step.
I personally discovered a course through Course Pilot, took it the following semester, and found the AI description accurately reflected the skills I hoped to build.