Hypothesis is the market-leading social annotation platform for higher education, used at more than 300 colleges and universities. It integrates directly into your LMS — Canvas, Blackboard, Moodle, or D2L — so students can highlight text, ask questions, and have conversations in the margins of any PDF, web page, or ebook without leaving your course. Hypothesis is built around three outcomes that matter right now: student engagement and collaboration (turning solitary reading into active, visible, peer-to-peer learning), AI-resistant workflows and literacy (assignments that require genuine critical thinking and can’t be shortcut by generative AI), and career preparation (building the close-reading, source-evaluation, and collaborative skills employers actually look for). Learn more at hypothes.is.

You need Hypothesis enabled in your LMS. If your institution already has Hypothesis, you’re ready — just upload a student PDF as a Hypothesis assignment. If you’re not sure whether your school has access, contact your LMS administrator or visit hypothes.is/get-started.

AI hallucinations are confident-sounding claims that an AI system generates that are factually wrong — fabricated citations, invented statistics, nonexistent authors, or misattributed quotes. They look convincing because the language is fluent and the format is correct, even when the content is not. This course pack uses real examples of hallucination types to teach students how to recognize and verify them.

Social annotation is a pedagogical practice where students add notes in the margins of digital texts — questions, insights, replies to classmates, links to related sources — creating a conversation about what they’re reading. It makes reading active, visible, and social: active because annotation requires close engagement with the text, visible because students can see each other’s thinking in real time, and social because the conversation builds collaboratively, right next to the words being discussed. Research shows social annotation leads to measurable gains in comprehension, participation, and critical thinking across disciplines.

Generative AI can produce a discussion board post in seconds. It can’t replicate the process of reading a passage, identifying a suspicious claim, searching for the original source, and explaining what you found to classmates — all anchored to a specific line of text in a shared document. Social annotation creates a visible trail of genuine student thinking that’s difficult to replicate with AI shortcuts. This course pack takes that a step further by making AI itself the subject: students learn to evaluate AI-generated content by doing the work AI can’t do for them.

Yes. The course pack is licensed CC BY 4.0, which means you can use, share, and adapt it with attribution. We’ll ask for your name, email, and institution when you download so we can follow up once to ask how it went — that’s it.

Pick the one closest to your discipline. The Space Race works for any course — it’s the most broadly accessible. The American Revolution fits humanities and general education. Governing the Machine is designed for social science, law, and policy courses. The Python Code Review is for computer science and data science students. You only need one.

Absolutely. The activity works in any modality — face-to-face, online, hybrid, synchronous, or asynchronous. Students annotate on their own time, and the conversation builds as classmates add to it. The debrief can happen in class or via a follow-up discussion.

Use your LMS group sets with Hypothesis’ group assignment feature. Split students into small teams of 4–6, and each group gets its own annotation layer. They only see their group’s work, which keeps the investigation genuine. The instructor guide includes detailed setup instructions.