Week 11 — Writing Studio / Workshop · "Cite It Right, Then Catch the Bot"

Course: English Composition (ENGL 1A) · Silver Oak University (fictional sample) · Prof. Lindgren
Objective: Objective 6 — MLA documentation (in-text citations; the works-cited entry; the core-elements / container model; formatting conventions) · SLO B (source-based research & academic integrity)
Worth 50 points · Writing Studios group = 15% of the grade · Studio 11
Format: a hands-on build-and-audit workshop — you'll assemble a correct MLA entry + in-text citation from raw facts, fix a citation generator's mis-format, review your work against an MLA checklist, get a chatbot's coaching, and then catch the chatbot's mistakes — including its most dangerous one, inventing sources and citations.

This is the course's signature weekly component. Every instructional week has one Writing Studio — a short, practical workshop on the week's craft move. All studio resources are links to external sites; there is nothing to buy or download. The habit every studio builds: draft → review → get feedback → judge the feedback. This week the "draft" is a citation, and judging the feedback means verifying every element against the real source.

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Part 1 — The Big Picture

This week you learned that MLA documentation has two matched halves — the in-text citation in your sentence and the works-cited entry at the end — built from one template of core elements. This studio makes it real: you'll build a correct entry from raw facts, catch a generator getting it wrong, and practice the judgment that protects your credibility — a citation that looks perfect can still be wrong or invented, so you verify. That's the load-bearing skill for next week's research-based argument.

Background (optional, ~8 min): "Works Cited: A Quick Guide" (MLA Style Center): 🔗 https://style.mla.org/works-cited/works-cited-a-quick-guide/ · and "MLA In-Text Citations: The Basics" (Purdue OWL): 🔗 https://owl.purdue.edu/owl/research_and_citation/mla_style/mla_formatting_and_style_guide/mla_in_text_citations_the_basics.html

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Part 2 — Build It From Raw Facts (write this)

Here are the raw facts for a real, verifiable source you can open right now:

A web page (the course's MLA reading):
- Title: MLA In-Text Citations: The Basics
- Site: Purdue OWL
- Publisher: Purdue University Writing Lab
- Author: (no individual author named)
- URL: owl.purdue.edu/owl/research_and_citation/mla_style/mla_formatting_and_style_guide/mla_in_text_citations_the_basics.html
- You viewed it: 9 Nov. 2026

Do this, in a word processor:
1. Build the MLA 9 works-cited entry by walking the template top to bottom — Author. "Title of Source." Title of Container, Contributor, Version, Number, Publisher, Publication date, Location. — including only the elements this source has. (No individual author → start with the title. No clear publication date → add an access date at the end.)
2. Write the matching in-text citation. (Think: what's the first element of your entry, and does a web page have a page number?)

Open the real page in a browser as you work, and confirm every detail against it.

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Part 3 — MLA Self-Check Table (fill this in)

Before you review, lay your entry against the template so you can see whether each element is right. Fill every row for your Part 2 entry:

Core element (in order)	What I put	✓ / ✗
Author. (or Title, if no author)	______	☐
"Title of Source." (quotation marks; title case)	______	☐
Title of Container, (italics)	______	☐
Publisher,	______	☐
Publication date, (or access date if none)	______	☐
Location. (URL; drop "https://"; end with a period)	______	☐
Matching in-text citation	______	☐

The point: walking the template row by row is exactly how you catch a missing container or a scrambled order — in your own work and in a generator's.

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Part 4 — Catch the Generator's Mistake, Then Self-/Peer-Review

(a) Fix a generator's botch. A citation generator produced this entry for a real TED Talk (Chimamanda Ngozi Adichie's "The Danger of a Single Story"):

❌ Adichie, Chimamanda Ngozi. "The danger of a single story." 2009. www.ted.com/talks/chimamanda_ngozi_adichie_the_danger_of_a_single_story. TED.

Find and name at least three things wrong with it, then write the corrected MLA 9 entry. (Hints to check: Is the title in title case? Is the container in the right place and italicized? Is the element order right? Is the date complete?)

(b) Self-/peer-review your Part 2 entry and your Part 4(a) correction against this MLA checklist — first on your own, then trade with a classmate (or reread as the grader would). Mark ✓ or ✗ and jot one fix:

Check	Part 2 entry	Part 4 correction
Elements are in MLA order (Author/Title/Container…)	☐	☐
Punctuation is right (period after author & title; commas between container-group elements; period at the end)	☐	☐
The container is present and italicized	☐	☐
Titles use title case; a short work is in quotation marks, a long work in italics	☐	☐
The in-text citation matches the entry's first element and uses no invented page number	☐	☐
Every detail is verified against the real source	☐	☐

Then fix anything you marked ✗. Keep the before and the after.

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Part 5 — Writing-Coach Moment (required — the BYOAI step)

Bring in your approved chatbot (Gemini, Claude, or ChatGPT) as a coach, not an author.

1. Paste your Part 2 works-cited entry and ask: "You are my MLA coach. Check this works-cited entry against the MLA 9 template: are the core elements in the right order, is the punctuation right, is the container italicized and in the right place, and is the title in title case? Point to anything off and explain why. Do NOT just give me a new entry — help me see what to fix."
2. Read its feedback and decide what to act on. Make any real correction yourself — then confirm the change against the real Purdue OWL page.

The coach is a mirror, not a citation machine. Use it to see whether your entry follows the rules — then you verify and fix. (If the coach's advice ever conflicts with the MLA Style Center or the Purdue OWL, the authorities win.)

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Part 6 — AI-Critique Moment (required — catch the tool's mistakes)

Now flip roles and be the editor who judges the tool — and this week, catch its most dangerous habit.

1. Ask the same chatbot: "Write a complete MLA works-cited entry for a source about the writing process — pick the source yourself."
2. Read its answer critically and catch what it does wrong — on two levels:
   - Format: Is the element order right? The commas and periods? Is the container present and italicized? Is the title in title case? Compare it line-by-line to the template.
   - Facts (the dangerous part): Does the source it picked actually exist? Are the author, title, date, and URL real and correct? Try to open it / look it up. Chatbots routinely produce flawless-looking citations for sources that don't exist, and invent details (wrong dates, made-up page numbers) for sources that do.
3. Write 3–4 sentences naming at least one format problem AND whether you could verify the source. If the source turned out to be fabricated or unverifiable, say how you could tell — and what you'd do instead (find a real source and cite that).

The habit all term: the tool drafts, you verify. In citation, this is not a nicety — a fabricated source or a made-up citation is an integrity violation whether a human or an AI produced it. Never put a citation in your paper that you haven't checked against the real source. A perfect-looking fake is still a fake.

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Part 7 — What to Submit

Submit a single document (or text entry) with: your Part 2 entry + matching in-text citation; your completed MLA self-check table (Part 3); your Part 4 correction (the three+ errors named and the fixed entry) plus your checklist marks; a one-line note on the coach feedback you acted on (Part 5); and your Part 6 AI-critique paragraph (format problem + whether the source was verifiable). Due Sunday, Nov 15, 11:59 p.m. (50 points).

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Instructor answer key & model — REMOVE BEFORE PUBLISHING TO STUDENTS

Every model below is correct MLA 9, verified against the MLA Style Center (style.mla.org) and the Purdue OWL. All sources are real. Students may choose their own real sources in the coach/critique steps, so exact entries vary — grade the MLA correctness and the verification, not specific wording.

Model — Part 2 entry (the Purdue OWL MLA page):

"MLA In-Text Citations: The Basics." Purdue OWL, Purdue University Writing Lab, owl.purdue.edu/owl/research_and_citation/mla_style/mla_formatting_and_style_guide/mla_in_text_citations_the_basics.html. Accessed 9 Nov. 2026.
Matching in-text citation: ("MLA In-Text Citations") — a shortened title (no author, no page number). (Why: no individual author → the title is the first element; no clear publication date → add an access date; web page → no page number in-text.)

Model — Part 4(a) the generator's errors + the fix (Adichie's real TED Talk):
- Errors (any three earn full marks): (1) title in sentence case — MLA uses title case: "The Danger of a Single Story"; (2) the container TED is at the end and not italicized — it belongs right after the title as TED: Ideas Worth Spreading; (3) scrambled element order — the URL appears before the container; (4) bare date "2009" with no month — the source shows July 2009.
- Corrected entry:

Adichie, Chimamanda Ngozi. "The Danger of a Single Story." TED: Ideas Worth Spreading, July 2009, www.ted.com/talks/chimamanda_ngozi_adichie_the_danger_of_a_single_story.
Matching in-text: (Adichie) — no page number (a video has none). (Format matches the MLA Style Center's online-lecture/TED example.)

What the models show (the grading targets):
- Builds a correct entry from the template (Part 2): right elements, right order, correct punctuation, italic container, title-case title, access date because there's no publication date, correct matching in-text citation. Full credit requires the entry to be correct MLA 9 and the source real.
- Catches the generator's mistakes (Part 4a): at least three real, distinct errors named, plus a correct corrected entry — the core "a generator's output is a draft, not an authority" skill.
- Self-/peer-review (Part 4b): the checklist applied honestly, with at least one fix made — not just every box checked.
- Coach moment (Part 5): acted on real feedback and verified against the source — not "the AI said it's fine."
- AI-critique (Part 6): full credit for a specific format catch and a real verification attempt — best of all if the student caught a fabricated or unverifiable source and said how they'd know. (If the AI's source happened to be real and correct, full credit for confirming it and still naming a format point.)

Grading rubric — 50 points

Criterion	Full	Partial	None
Build an entry from raw facts — correct MLA 9 entry + matching in-text citation, source real and verified (14)	14	7–11	0–6
MLA self-check table — all rows filled; correctly maps the entry to the template (8)	8	4–6	0–3
Catch + fix the generator's botch — ≥3 real errors named and a correct corrected entry (14)	14	7–11	0–6
Coach moment — acted on real feedback and verified against the source, in the student's own work (6)	6	3	0–2
AI-critique — names a specific format problem AND reports whether the source was verifiable (catches fabrication where present) (8)	8	4–6	0–3

Quality gate (self-checked) — citation-integrity + correct-conventions: PASS. Every MLA model in this studio — the Part 2 web-page entry, the matching in-text citations, and the Part 4 TED-Talk correction — is correct MLA 9, checked element-by-element against the MLA Style Center ("Works Cited: A Quick Guide"; the online-lecture/TED example) and the Purdue OWL ("MLA In-Text Citations: The Basics"; "MLA Works Cited Page: Basic Format"). All cited sources are real and verified live (Adichie's TED Talk on TED.com; the Purdue OWL and MLA Style Center pages). The generator-botch example is a realistic, clearly-labeled incorrect entry whose named errors (sentence-case title, dropped/late container, scrambled order, bare date) are genuinely the errors present; the corrected version is correct. No quotation, source, or citation is fabricated or misattributed; the AI-critique step explicitly trains students to catch fabrication. There is no computation in this studio.