Week 1 — Sociology-in-Action Workshop · "Your Biography Meets History"

Course: Introduction to Sociology (SOC 1) · Silver Oak University (fictional sample) · Prof. Adeyemi
Objective: Objective 1 — apply the sociological imagination (personal troubles ↔ public issues) · SLO A (apply theory) & SLO B (reason from evidence)
Worth 50 points · Sociology Workshops group = 15% of the grade · Workshop 1
Mode this week: structured observation/reflection (later weeks alternate with data-interpretation workshops). No special tools — just your own experience, a browser, and an approved chatbot.

This is the course's signature weekly component. Every instructional week has one Sociology Workshop. Some weeks you'll read real social data (a chart or table from the Census, Pew, BLS, the World Bank, or Our World in Data); other weeks you'll observe and reflect on your own social world. Either way you'll end by catching an AI's mistakes. All external resources are links — nothing to buy or download.

Part 1 — The Big Picture

This week you met the discipline's core skill: the sociological imagination (C. Wright Mills, 1959) — the ability to see how your personal biography is shaped by history and social structure. Mills' move is to connect a personal trouble (something private — felt as your own) to a public issue (a structural pattern shared by many). This workshop turns that lens on your own life.

The guiding question: Take something you've experienced as a private, personal matter — and ask: is it also a public issue? What social structures are at work behind it?

Part 2 — Choose Your "Trouble"

Pick one experience from your own life that felt personal — something you'd normally explain in terms of your own choices, effort, or luck. Some examples (use one of these or your own):

• the cost of college or textbooks, or working while studying
• a long or stressful commute
• finding (or not finding) a job
• time spent on social media, or trouble disconnecting
• moving / housing / rent
• balancing family responsibilities with school

Write your choice in one sentence: "A personal trouble I've experienced is ______."

Part 3 — Observation & Reflection Scaffold (fill this in)

Work the three columns for your chosen trouble. This is the what-I-observed → which-concept → so-what move.

Part 4 — Find One Real Number (optional but recommended)

Locate one real statistic that shows your trouble is also a public issue (a shared, measurable pattern) — from an authoritative source. Good starting points (links only):

• U.S. Census Bureau / QuickFacts 🔗 https://www.census.gov/quickfacts/fact/table/US
• Pew Research Center 🔗 https://www.pewresearch.org/
• Bureau of Labor Statistics 🔗 https://www.bls.gov/

Record it carefully: What is measured? · The number + year · The source. Example format: "~38% of U.S. undergraduates worked while enrolled (source + year) — verified on the source's page." Do not paste a number you haven't seen on the source's own page — that's the whole discipline of this course.

Part 5 — Analysis Questions

Answer in a sentence or two each:
1. In your own words, what is the difference between a personal trouble and a public issue? Use your example.
2. Name one social structure behind your trouble, and explain how it shapes the experiences of many people, not just you.
3. If someone said your trouble is "just a matter of personal choices," how would the sociological imagination answer them?
4. If you found a statistic in Part 4: what does it show — and what does it not show? (For instance, does it prove a cause, or just describe a pattern?)

Part 6 — AI-Critique Moment (required — this is the BYOAI step)

Now bring in your approved chatbot (Gemini, Claude, or ChatGPT) and be the sociologist who checks its work.

1. Describe your trouble and ask: "Reframe this as a public issue using the sociological imagination, name the social structures involved, and give me one statistic showing it's widespread."
2. Check everything it says against this week's ideas and a real source:
   - Did it correctly distinguish the personal trouble from the public issue, or did it just restate your private story?
   - Did it overgeneralize or stereotype — e.g., treat a group average as true of every member of a group, or pin the issue on a stereotype about "people like that"? (Chatbots do this constantly.)
   - Did it invent a statistic or a "study"? Search for any number it gives at the source (Census, Pew, BLS). If you can't find it, treat it as fabricated — and say so.
   - Did it slide from correlation to causation (e.g., "X group has more of this because they're Y")?
3. Write 3–4 sentences reporting what the AI got right and at least one thing you had to correct, verify, or flag — an overgeneralization, a correlation-as-causation slip, or a number you couldn't confirm at the source. (If it happened to get everything right, say how you verified each claim — that's the skill.)

The habit all term: the tool drafts, you judge. A chatbot will confidently invent a statistic or stereotype a group — catching it is the point.

Part 7 — What to Submit

Submit a single document (or text entry) with: your chosen trouble (Part 2), your completed scaffold (Part 3), any statistic + source (Part 4, if done), your Part 5 answers, and your Part 6 AI-critique paragraph. Due Sunday, Sep 6, 11:59 p.m. (50 points).

Instructor answer key & model responses — REMOVE BEFORE PUBLISHING TO STUDENTS

Students analyze their own experiences, so responses vary. The key grades the reasoning — the trouble→issue move, the structures named, and the quality of the AI-critique — not a specific "right" trouble.

Model worked example (commute):
- Personal trouble: "My 90-minute commute exhausts me and cuts into study time."
- Public issue: long commutes are a widespread, structural pattern — driven by housing costs pushing affordable homes far from jobs/campus, transit design, and land-use policy.
- Structures at work: the housing market, urban/suburban land use, public-transit funding, the location of jobs and campuses.
- So what? seeing it as structural shifts the "fix" from "just move closer" (often impossible on a budget) toward transit, housing policy, or remote options.
- A real statistic, done right: a student might cite the U.S. Census/ACS mean travel time to work (around the mid-20s of minutes nationally in recent years) — but only after seeing it on the Census page, with the year noted. The key does not assert a specific figure here; the point is that the student verifies it at the source. (If a workshop in a later week supplies a figure, that figure is checked live against the source before it ships.)

Expected answers:
- Part 5 Q1: a personal trouble is private and individual; a public issue is a shared, structural pattern affecting many — the same situation seen at the level of society. Q2: any real structure (economy, housing, work norms, technology, policy) with a plausible mechanism. Q3: the sociological imagination shows that a society-wide rate can't be millions of independent bad choices — structure is doing work. Q4: a statistic typically describes a pattern (correlation/prevalence); it usually does not prove a cause.
- Part 6 (AI-critique): full credit for a specific catch — most commonly the AI inventing a statistic (unverifiable at the source), overgeneralizing/stereotyping a group, or asserting a cause from a mere pattern. Full credit also if the student verified each AI claim against a real source and reported how.

Grading rubric — 50 points

Quality gate (self-checked): this is an observation/reflection workshop, so it asserts no specific statistic as fact — the only numbers are illustrative and explicitly conditioned on the student verifying them at the source (Census/Pew/BLS). The sociological-imagination framing (Mills, 1959), the personal-trouble vs. public-issue distinction, and the named structures are all accurate; the AI-critique explicitly targets fabricated statistics, overgeneralization/stereotyping, and correlation-vs-causation — the discipline's load-bearing AI risks. No correlation is presented as causation.