AI Research & Source-Rigor for College & Grad Work
Research and synthesize faster than your peers — and make it defensible enough to hand to a professor or an employer.
About this course
You'll learn to drive AI as a research accelerator — broad scans, literature mapping, argument structuring — while staying the human who verifies every claim, traces every source, and cites it correctly. Here's the edge it gives you: while your classmates are still reading, you're delivering verified, well-argued, properly-sourced work — and you can prove your process to a skeptical supervisor or hiring manager. Every lesson ends in a reusable artifact: a verification checklist, a research-prompt library, an annotated source map. You walk away with a fully verified, correctly-cited mini-literature-review on a question from your own field — the portfolio piece that proves you can research rigorously AND fast.
9 lessons
How AI Actually "Knows" Things (and When It Lies)
Understand why language models hallucinate confident, plausible falsehoods — and where the risk is highest. You'll leave with a one-page mental model of when to trust AI, when to verify, and when to never ask it at all, so you stop being fooled the way most students are.
Framing a Research Question AI Can Actually Help With
Turn a vague assignment into a sharp, answerable research question and a search strategy. You'll produce a structured research brief — scope, key terms, sub-questions, source types — that makes every later AI prompt sharper and your eventual argument tighter.
Fast, Broad Scans Without Losing Rigor
Use AI to map a topic in minutes — major schools of thought, key authors, opposing positions — then immediately pressure-test it. You'll build a reusable 'topic map' artifact and learn the discipline of treating every AI claim as a lead to verify, not a fact to cite.
Verifying Sources and Killing Hallucinated Citations
The core skill. Learn to trace every citation to a real, findable source, spot fabricated references, and use library databases and Google Scholar to confirm. You'll build a personal source-verification checklist you can run on any paper before you submit it.
Reading and Summarizing Dense Material with AI
Feed AI real papers, rulings, or reports and get accurate, faithful summaries — without it inventing findings. You'll learn extraction prompts that quote and locate claims, and produce a set of trustworthy annotated summaries for a real topic.
Synthesizing Sources into a Defensible Argument
Move from a pile of notes to a structured, evidence-backed argument. You'll use AI to test counter-arguments and find gaps, then assemble a claim-evidence-reasoning outline you could defend out loud to a professor.
Citing Correctly (APA, MLA, Chicago) Without Errors
Use AI to format citations and bibliographies fast — then catch the mistakes it makes. You'll build a citation QA pass and produce a correctly formatted reference list for your topic in your program's required style.
Academic Integrity, AI Disclosure, and Defensible Process
Know where the line is: what's legitimate AI-assisted research versus misconduct, and how to disclose AI use the way more institutions now require. You'll write a short, honest 'AI process statement' you can attach to any submission — turning a risk into a credibility signal.
Capstone: A Verified Mini-Literature-Review
Pull it all together: produce a short, fully-verified, correctly-cited literature review on a question from your own field, with your verification checklist and AI process statement attached. This is the portfolio piece that proves to an employer you can research rigorously AND fast.