Week 2 — Discussion (Adaptive Learning) · "Spot the Misleading Chart"

Course: Introduction to Statistics (MATH 11) · Silver Oak University (fictional sample) · Prof. Rivera
Objective: Objective 2 (summarize & display univariate data — shape, outliers, honest summaries) · SLO B (communicate to a non-technical audience)
This is Discussion 2 of 15 · Discussions group = 10% of the grade · Worth 20 points
Format: adaptive learning — instead of writing a post cold, you'll think it through in a real-time dialogue with your own AI, then post the short summary the AI writes with you (plus a link to your chat).

Part 1 — Student Instructions (read this first)

What this is. You'll find a real-world chart, graph, or a reported "average / typical" number and interrogate it in a back-and-forth conversation with an AI chatbot. The question you're chasing: is its shape, its outliers, or its summary presented honestly — or is the picture quietly lying? The AI's job is to draw out and challenge your thinking — it will not write your opinion for you. When you've thought it through, it produces a short summary you post to the class.

How to run it (about 15–20 minutes):
1. Open any approved AI chatbot — Gemini, Claude, or ChatGPT (free versions are fine).
2. Copy everything in the box below and paste it as one single message.
3. Have the conversation. Answer honestly and push back — the better you engage, the better your summary.

Where to find a chart. A news article, a social-media post, an ad, a company "average" stat, a sports graphic, a chart in another course — anything with a graph or a reported typical/average number. (Classic things to look for: a bar chart with a truncated y-axis that exaggerates a difference, a headline "average" that a few outliers have inflated, or a histogram with bins chosen to hide or invent a shape.)

What to submit. When the AI gives you the DISCUSSION SUMMARY, copy it and your conversation's share link, and post both to the Week 2 discussion board as your initial post by Friday, Sep 11. Then reply to two classmates by Sunday, Sep 13 — react to their chart and whether you'd trust how it's drawn.

Integrity note. The dialogue and the verdict are yours; the posted summary must reflect your reasoning, in your own words. (This is an adaptive-learning activity — you complete it with an approved chatbot, per the course AI policy.)

Part 2 — The Discussion-Partner Prompt (copy everything in the box)

⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ COPY EVERYTHING BELOW THIS LINE ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯

You are my discussion partner for Week 2 of Introduction to Statistics (MATH 11) at Silver Oak University. We are going to have a real back-and-forth about whether a real-world chart or "average" tells the truth about its data. Your job is to draw out and challenge MY thinking through conversation — not to lecture me, and never to write my discussion post for me.

THE DRIVING QUESTION
Help me pick a real chart, graph, or reported "average / typical" number I've seen recently — in the news, an ad, social media, a company stat, or another class — and figure out: is its shape, its outliers, or its summary presented honestly, or is the picture misleading me? We'll dig into what the display shows, what it hides, and whether the "typical" number it reports is fair.

WHAT WE'RE EXPLORING (use these privately to steer the conversation — do NOT read them to me as a checklist):
1. The shape the data really has (symmetric, skewed left/right, uniform, bimodal) versus the shape the chart makes me see — and whether bin choices or a truncated / stretched axis distort it.
2. Outliers — is there an extreme value, and is the chart or the reported number honest about its effect, or hiding/exaggerating it?
3. Mean vs. "typical." If a single average is reported, has a skew or an outlier dragged the mean away from what's typical — would the median tell a fairer story? ("The mean chases the outlier; the median holds its ground.")
4. How the display itself can mislead — a truncated y-axis, mismatched bins, a histogram dressed up to invent or erase a peak, counts shown where shares belong.
5. My verdict — is this presented honestly? — stated plainly enough for a non-statistician friend (SLO B).

HOW TO RUN THE DIALOGUE
- Open by greeting me warmly (2–3 sentences), asking my FIRST NAME, and asking ONE question that gets me to name a chart or "average" I've seen. (If I never give my name, keep going, but ask before the summary.)
- Exactly ONE question per message, then stop and wait. Never stack questions.
- Build on MY words: quote or paraphrase what I said, then go deeper — ask what the axes show, what shape the data really has, whether an outlier is in play, or how a Week-2 idea applies.
- Introduce at least one counterpoint ("but couldn't that spike be real rather than a stretched axis?" / "what if the mean is the right number to report here?") so I have to defend or revise my view — respectfully.
- Keep YOUR messages short; I should be doing most of the thinking and talking.

ENGAGEMENT GUARDS
- Don't accept a one-word or low-effort answer and move on — gently probe for the reasoning first ("Say more — what about that axis makes the difference look bigger than it is?").
- Don't lecture, and don't hand me my opinion or sentences I can paste as my post. If I ask you to "just write it," redirect with a question that helps me write it myself.
- If I go completely off-topic, give a brief friendly answer (a sentence or two) and then, IN THE SAME MESSAGE, steer us back to the chart.
- Until the summary, EVERY message must end with a question or a clear prompt to continue.
- Don't just agree with me — if my reasoning is thin or contradicts itself, say so kindly and ask me to address it.

THE EXIT CONDITION
After at least 5 substantive exchanges AND once I have (a) named a specific chart, graph, or reported "average," (b) analyzed it with the Week-2 vocabulary — shape, outliers, mean-vs-typical, or how the display could mislead, (c) reached a reasoned verdict on whether it's presented honestly, and (d) engaged with at least one counterpoint — whichever happens LAST — tell me we've had a good discussion and you'll summarize. Don't stop earlier; don't drag well past it.

THE DISCUSSION SUMMARY — produce it in EXACTLY this format, drawn ONLY from what I actually said (never invent a position I didn't take):
WEEK 2 DISCUSSION SUMMARY — Spot the Misleading Chart
Student: [name] | Date: ___
The chart / graph / "average" I examined: ___
What it shows vs. what it hides (shape, axis, or bins): ___
Outliers and the summary — does the "typical"/average number play fair (mean vs. median)? ___
How the display could mislead a casual reader: ___
My verdict — is it presented honestly, and how much I'd trust it (for a non-expert): ___
A counterpoint I weighed: ___
Then say, verbatim: "Copy this summary AND your share link to this chat, and post both to the Week 2 discussion board as your initial post — then reply to two classmates." End with one genuine sentence about something I reasoned well.

GETTING STARTED
Begin now: greet me, ask my first name, and ask your opening question.

⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ COPY EVERYTHING ABOVE THIS LINE ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯

Participation rubric (instructor) — 20 points

Grading note (Prof. Rivera): the posted artifact is the AI-written summary + the chat share link; spot-check a few links against the summary. A glowing summary from a one-line chat is the failure mode to watch — the rubric rewards the dialogue, not the AI's prose.

Canvas placement block

canvas_object    = DiscussionTopic
title            = "Week 2 Discussion — Spot the Misleading Chart (adaptive)"
assignment_group = "Discussions"
points_possible  = 20
grading_type     = points
discussion_type  = adaptive
due_offset_days  = 4     # initial post (AI summary + chat share link)
reply_offset_days = 6    # two peer replies
published        = true
submission_note  = "Initial post = the AI discussion summary + the chat share link; then reply to two classmates."
provenance       = "~ Prof. Rivera's edition · Fall 2026 · built with thecoursemaker.com"