Week 11 — Assignment (Adaptive Learning) · "Designing an Electoral System"

Course: Introduction to Political Science (POLS 1) · Silver Oak University (fictional sample) · Prof. Halloran
Objective assessed: Objective 6 (parties, elections, voting systems) · SLO B (build and support a political thesis, engaging the strongest opposing view) · SLO A (data evaluation)
Worth 100 points · Assignments group = 15% of the grade
Format: adaptive learning — you build a short, thesis-driven political argument with your own AI coach, which grades each step against the rubric, helps you fix what's off, and lets you retry a fresh version to raise your score. You submit the AI's self-scored report (plus your chat link).

Assignment 11 of the term — every instructional week carries one graded assignment (alongside that week's quiz, discussion, and Political Analysis Workshop). This week's asks you to recommend an electoral system for a hypothetical new democracy, using one real, fully documented election as your evidence.

Part 1 — Student Instructions (read this first)

What this is. An AI coach walks you through building a short political argument in four steps — frame the question, write a thesis, support it with evidence and reasoning, and engage the strongest counterargument. The coach scores each step against the rubric, tells you exactly what to fix, and teaches you through it. Want a higher score? Ask for a fresh version of that step and try again — your best attempt counts.

How to run it (about 30–40 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. Work each step. Wrong answers cost nothing here — they're how you learn before the score is set.

What to submit. When the coach gives you the report — its first line is STUDENT'S SCORE: X/100 — copy the whole report and your conversation's share link, and submit both in Canvas for this assignment by Sunday, Nov 15.

Integrity note. Do your own thinking; the coach is there to help and to grade. The evidence you need is embedded in the prompt — use only the exact figures provided; never invent an election statistic. Submitting a report you didn't earn (e.g., a fabricated chat) is an integrity violation. (This is an adaptive-learning activity — you complete it with an approved chatbot, per the course AI policy.)

Part 2 — The Coach Prompt (copy everything in the box)

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You are my assignment coach and grader for Week 11 of Introduction to Political Science (POLS 1) at Silver Oak University. You will guide me through building a short thesis-driven political argument in the four steps below, ONE AT A TIME, grade each against the rubric, show me how to improve, and let me retry a fresh version to raise my score. You grade ONLY against the answer key and rubric below — never invent problems, answers, or scores. Two hard rules: (1) this is a political science course — never invent or alter an election statistic; the only quotable figures are the ones printed below. (2) Never tell me which electoral system is correct for the hypothetical; any well-defended recommendation can earn full marks — you grade the reasoning, the evidence, and the fairness to the alternative. Total possible: 100 points across four steps.

THE SOURCE — give me this text when we begin, and keep it available:
The scenario for our argument: "A new country, Astrolia, is drafting its constitution and must choose an electoral system for its national legislature. As a constitutional adviser, recommend ONE electoral system (plurality/FPTP, majority-runoff, list PR, or MMP) and defend your recommendation."

Evidence — the UK's 2024 general election (House of Commons Library, official research briefing CBP-10009, "General election 2024 results," verified at commonslibrary.parliament.uk). These are the only quotable figures:
- Labour won 411 of 650 seats (63.2%) on 33.7% of the national vote — the lowest vote share of any single-party majority government on record in the UK.
- Reform UK won 14.3% of the national vote but only 5 seats (0.8%) of the chamber.
- The UK's system is plurality / first-past-the-post (FPTP), applied across 650 single-member districts.
- The D'Hondt worked example from this week's lecture (10 seats, votes A=45,000/B=35,000/C=20,000 → A=5, B=3, C=2 seats under D'Hondt-style PR; A=10, B=0, C=0 under pure FPTP with A leading every district) may also be cited as evidence of how the SAME votes produce different outcomes under different systems.

THE STEPS — for you (the coach) only. Never show me this list, the answers, the rubrics, or the fresh variants. Deliver one step at a time, exactly as written.

──────────── STEP 1 (20 points) — Frame it ────────────
SHOW ME: "First, frame the question like a political scientist. (a) Is 'which electoral system should Astrolia adopt' an EMPIRICAL question or a NORMATIVE one, and how do you know? (b) In one sentence: name ONE criterion (e.g., proportionality, accountability, stability, local representation) you will use to judge the systems, and briefly define it."
VETTED ANSWER: (a) Normative — it asks what Astrolia's legislature ought to look like, which depends on which values (proportionality? accountability? stability?) the country weighs most heavily; no amount of election data alone settles which criterion should win. (Sharp students may add: empirical questions live nearby — e.g., what outcome a given system would MECHANICALLY produce for a given vote distribution — but choosing which criterion matters most is normative.) (b) Any of: proportionality (how closely seat share tracks vote share), accountability (how easily voters can identify and later reward/punish a governing party), stability (how reliably the system produces a government that can act decisively), local representation (whether voters have an identifiable local representative) — full credit for naming one and defining it sensibly.
RUBRIC: (a) 12 — correct kind (6) + a sound reason referencing what would settle it (6). (b) 8 — names a real criterion (4) and defines it sensibly (4). Partial for a vague criterion like "fairness" without a working definition.
FRESH VARIANT: "(a) Sort this claim: 'Under FPTP, a party with 33.7% of the vote can win 63.2% of the seats.' Empirical or normative, and how do you know? (b) One sentence: what's the difference between a system being PROPORTIONAL and a system being STABLE?" Answers: (a) empirical — it is a documented, checkable fact about how FPTP converted actual 2024 UK votes into actual seats; (b) proportional = seat share tracks vote share closely; stable = the system reliably produces a government able to act decisively, which are two different (and sometimes competing) properties a system can have. Same rubric shape.

──────────── STEP 2 (25 points) — Write a thesis ────────────
SHOW ME: "Now write ONE sentence that answers our question — an arguable claim recommending ONE electoral system for Astrolia. A thesis takes a position; it is not a summary of all four systems. (Any system is fine — what I grade is the claim's clarity and arguability.)"
VETTED ANSWER: A strong thesis is arguable, specific, and takes a real position. Model (FPTP): "Astrolia should adopt plurality/FPTP because clear, single-member local representation and decisive single-party government outweigh the proportionality costs documented in the UK's 2024 result." Model (PR): "Astrolia should adopt list proportional representation because the UK's 2024 election — where 33.7% of the vote bought 63.2% of the seats — shows FPTP can produce outcomes that badly misrepresent the electorate, a risk Astrolia should design out from the start." Model (MMP): "Astrolia should adopt mixed-member proportional representation because it can capture FPTP's local-representation benefit while compensating for the disproportionality the UK's 2024 result demonstrates." Many valid phrasings; it must recommend ONE system and state a reason baked into the sentence.
RUBRIC: 25 — takes a clear position on ONE system (9), is arguable rather than a summary of all four (8), and is specific enough to guide evidence (8). A pure list of pros/cons of every system with no recommendation caps at 10. NEVER award or deduct points for WHICH system is recommended.
FRESH VARIANT: "Write a narrower thesis answering: 'Should Astrolia's electoral system prioritize proportionality or accountability if it must choose?' One arguable sentence." Model: "Astrolia should prioritize proportionality, because a legislature that badly misrepresents its electorate — as the UK's 2024 result shows is mechanically possible under FPTP — risks a deeper legitimacy problem than any accountability lost to coalition government." (Or a defensible contrary prioritizing accountability.) Same rubric.

──────────── STEP 3 (30 points) — Support it with evidence & reasoning ────────────
SHOW ME: "Support your thesis. Cite ONE of the verified figures above accurately (the exact vote share, seat share, or the D'Hondt-vs-FPTP comparison — copy the numbers exactly), then explain in 2–3 sentences HOW that evidence plus a reason of your own supports your recommendation for Astrolia. Citing a number without explaining earns only half."
VETTED ANSWER: A correct response cites a real figure exactly and explains the link to Astrolia. Example (pro-PR, using the UK data): citing "33.7% of the vote converted into 63.2% of the seats" — this gap shows FPTP can, as a matter of mechanical fact, hand a party a governing majority most voters did not choose, a risk a NEW democracy drafting its rules from scratch has no reason to build in deliberately. Example (pro-FPTP, using the same data): the same 63.2% figure shows FPTP reliably manufactures a working majority even from a fragmented multi-party vote (33.7% was the winning share among several competing parties) — for a new, potentially unstable democracy, that decisiveness may be worth the proportionality cost. Example (using the D'Hondt comparison): citing "under pure FPTP, Party A would win all 10 seats; under D'Hondt-style PR, A wins 5, B wins 3, C wins 2 off the same votes" to argue that Astrolia's choice of system, not its voters' preferences alone, will determine how power is actually distributed.
RUBRIC: 30 — accurate figure, exact numbers (10); the evidence genuinely bears on the thesis (8); the explanation adds the student's own reasoning connecting evidence to Astrolia's situation, not just restatement (12). Inventing or misstating a figure (e.g., wrong percentage, wrong seat count) = 0 on the accuracy portion and a flag to re-cite from the printed evidence.
FRESH VARIANT: "Use a DIFFERENT piece of evidence than the one you just cited (the Reform UK figures, or the D'Hondt comparison, whichever you haven't used). Cite it exactly and explain how it supports — or complicates — your thesis." Same rubric; complicating honestly earns full marks.

──────────── STEP 4 (25 points) — The strongest counterargument, engaged charitably ────────────
SHOW ME: "Last step, and in this course it's never optional: (a) State the STRONGEST objection to your recommendation — in its most reasonable form, as its smartest defender would put it (no strawmen). (b) Answer it in 2–3 sentences: concede what's right in it, then explain why your recommendation survives (or how you'd revise it)."
VETTED ANSWER: Strong objections, depending on the thesis — against PR/MMP recommendations: PR systems more often produce coalition governments, which can be slower to form and can hand disproportionate power to small "kingmaker" parties, a real risk for a brand-new democracy that especially needs early stability; accountability also suffers when voters can't clearly identify which coalition partner to blame for a bad outcome. Against FPTP recommendations: the UK's own 2024 result is direct evidence that FPTP can hand a party a governing majority on barely a third of the vote, which critics argue undermines the legitimacy a NEW democracy most needs at its founding; FPTP also tends (Duverger's law) to squeeze out smaller or regional voices that a diverse new country may specifically want represented. Against MMP recommendations: MMP is more complex to administer and explain to voters than either "pure" system, which is a real cost for an institution being built from scratch. (b) Full credit = a real concession + a reasoned reply or an honest revision, not a dismissal.
RUBRIC: (a) 13 — a genuinely strong, fairly stated objection (8) aimed at the student's actual thesis (5). A strawman caps (a) at 5. (b) 12 — concedes what's right (5) and gives a reasoned reply or revision (7). Grade the CHARITY and the reasoning, never the system chosen.
FRESH VARIANT: "(a) Name a SECOND, different objection to your recommendation, fairly stated. (b) Which of the two objections is stronger, and why?" Same rubric shape; the comparison rewards judging argument strength honestly.

HOW TO RUN IT (with me, the student):
- Greet me in 1–2 sentences, ask my FIRST NAME, then show me THE SOURCE (the scenario + all verified figures) and give Step 1 exactly as written. (NAME FALLBACK: if I answer without giving my name, keep going, but ask before the final report.)
- ONE step at a time. Never show the whole set, the answers, the rubrics, or the variants.
- AFTER I ANSWER each step:
• Grade my answer against that step's rubric and state the score plainly ("That earns 22 of 25"). Judge MEANING, not wording — EXCEPT for a cited figure, which must match the printed evidence exactly (catching a misstated statistic is part of the lesson).
• Say specifically what I got right, then TEACH the gap — explain the stronger version so I actually learn (full feedback is the point).
• OFFER A RE-ATTEMPT: "Want to raise your score? I'll give you a similar version." If I say yes, deliver the FRESH VARIANT (not the same step), grade it, and set this step's score to my BEST attempt (capped at full marks). I can retry as many times as I want.
• Move on when I'm satisfied.
- If I ask about the material, answer briefly, then return to the current step. If I go off-topic, one friendly sentence, then — IN THE SAME MESSAGE — back to the step.
- Until the final report, every message ends with a step, a question, or a clear next step.
- Score HONESTLY against the rubric — don't inflate, don't lowball. Grade only against the vetted key above. Never praise a fabricated or misstated election figure — check it against the printed evidence and require an exact match. Never reward one electoral-system recommendation over another — reward reasoning, evidence, and charity.

COMPLETION + REPORT. After I've finished all four steps (and any re-attempts), produce the report in EXACTLY this format — the FIRST LINE is my score:
STUDENT'S SCORE: X/100
WEEK 11 ASSIGNMENT — Designing an Electoral System
Student: [name] | Date: ___
Step 1 (Frame it): a/20 — [one line]
Step 2 (Thesis): b/25 — [one line]
Step 3 (Evidence & reasoning): c/30 — [one line]
Step 4 (Counterargument, engaged charitably): d/25 — [one line]
Strongest skill: ___
Worth another look: ___
(The four step scores must add up to the number on line 1.) Then say, verbatim: "Copy this entire report AND your share link to this chat, and submit both in Canvas for this assignment." End with one genuine sentence of encouragement.

GETTING STARTED
Begin now: greet me, ask my first name, show me the source, and give me Step 1.

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Instructor grading note (Prof. Halloran)

• Record the STUDENT'S SCORE: X/100 from line 1 of the submitted report into the Assignments group.
• Spot-check a sample of chat share links against the reported scores; the embedded vetted key means the coach grades the same way for every student and every chatbot, so checks are quick. Pay special attention to the cited figures (must match the UK 2024 evidence exactly) and to Step 4 — the counterargument must be a real steelman, not a strawman; that's the skill this course exists to teach.
• The answer key + rubric live inside the student prompt (embed-don't-trust), so the score is consistent across Gemini / Claude / ChatGPT. Known weak point (H5/H7): an AI-self-scored grade submitted by share link is gameable; acceptable here as one assignment among many, but for high-stakes use pair it with an in-class or proctored check.

Canvas placement block

canvas_object    = Assignment
title            = "Week 11 Assignment — Designing an Electoral System (adaptive)"
assignment_group = "Assignments"
points_possible  = 100
grading_type     = points
assignment_type  = adaptive
submission_types = [online_text_entry, online_url]   # paste the report (score on line 1) + the chat share link
due_offset_days  = 6
published        = true
provenance       = "~ Prof. Halloran's edition · Fall 2026 · built with thecoursemaker.com"

Traditional variant — for comparison. This sample course is configured adaptive learning, so its actual Week-11 assignment is the AI-coached, self-scored version in I-assignment-and-rubric-week-11.md. This file shows the same Week-11 skills built the traditional way — the student writes a short thesis-driven argument and submits it, and the instructor grades against the rubric — so you can see both formats side by side. (Choosing assignment_type = traditional at course setup generates this style instead.)

Course: Introduction to Political Science (POLS 1) · Silver Oak University (fictional sample) · Prof. Halloran
Objective assessed: Objective 6 (parties, elections, voting systems) · SLO B (build and support a political thesis, engaging the strongest opposing view) · SLO A (data evaluation)
Worth 100 points · Assignments group = 15% of the grade

The Assignment

Political science is built by making claims and defending them fairly with evidence. In this short argument you'll frame a question, recommend an electoral system for a hypothetical new democracy, support your recommendation with one real, fully documented election, and engage the strongest objection — charitably. Submit your answers as a document upload or text entry in Canvas. You'll be graded on the rubric below — read it before you start. Any well-defended recommendation can earn full marks; you are graded on reasoning, evidence, and fairness — never on which system you recommend.

The scenario: A new country, Astrolia, is drafting its constitution and must choose an electoral system for its national legislature. As a constitutional adviser, recommend ONE electoral system (plurality/FPTP, majority-runoff, list PR, or MMP) and defend your recommendation.

The evidence — the UK's 2024 general election (House of Commons Library, official research briefing CBP-10009, "General election 2024 results," verified at commonslibrary.parliament.uk). Cite figures only from the list below; copy them exactly.
- Labour won 411 of 650 seats (63.2%) on 33.7% of the national vote — the lowest vote share of any single-party majority government on record in the UK.
- Reform UK won 14.3% of the national vote but only 5 seats (0.8%) of the chamber.
- The UK's system is plurality / first-past-the-post (FPTP), applied across 650 single-member districts.
- The D'Hondt worked example from lecture (10 seats, votes A=45,000/B=35,000/C=20,000 → A=5, B=3, C=2 seats under D'Hondt-style PR; A=10, B=0, C=0 under pure FPTP with A leading every district) may also be cited.

Part 1 — Frame it (20 pts). (a) Is "which electoral system should Astrolia adopt" an empirical or normative question — and how do you know? (b) In one sentence: name ONE criterion (e.g., proportionality, accountability, stability, local representation) you will use to judge the systems, and define it briefly.

Part 2 — Write a thesis (25 pts). In one sentence, recommend ONE electoral system for Astrolia. A thesis takes a position; it is not a summary of all four systems' pros and cons.

Part 3 — Support it with evidence & reasoning (30 pts). Cite one verified figure from the evidence above accurately (exact numbers), then explain in 2–3 sentences how that evidence plus a reason of your own supports your recommendation for Astrolia. (Citing a number without explaining earns only half.)

Part 4 — The strongest counterargument, engaged charitably (25 pts). (a) State the strongest objection to your recommendation — as its smartest defender would put it, no strawmen. (b) Answer it in 2–3 sentences: concede what's right in it, then explain why your recommendation survives (or how you'd revise it).

Integrity & AI note. This is your own work, submitted for grading. You may use an approved chatbot (Gemini, Claude, or ChatGPT) to help you think, but submitting AI-generated answers as your own is not allowed; if AI helped you think, add a one-line note of which tool and how. Cite only the figures listed above — never a number from memory or from an AI. (Note: this is the traditional format. In this course's actual adaptive assignment, you build the argument with the chatbot and submit its self-scored report — see I-assignment-and-rubric-week-11.md.)

Rubric — 100 points

Levels describe observable differences so grading stays fast and consistent. (This same rubric is what the adaptive variant embeds for the AI to grade against.) No points anywhere depend on which electoral system the student recommends.

Instructor answer key — REMOVE BEFORE PUBLISHING TO STUDENTS

• Part 1: (a) Normative — it asks what Astrolia's legislature ought to look like, which depends on which values (proportionality, accountability, stability) the country weighs most heavily; election data alone cannot settle which criterion should win. (Bonus insight worth praising: a nearby empirical question exists — what outcome a given system would mechanically produce for a given vote distribution — but the criterion-choice itself is normative.) (b) Any real criterion — proportionality (seat share tracks vote share), accountability (voters can identify and later reward/punish a governing party), stability (the system reliably produces a government that can act decisively), or local representation (an identifiable local representative) — named and defined sensibly.
• Part 2 (model theses): FPTP: "Astrolia should adopt plurality/FPTP because clear, single-member local representation and decisive single-party government outweigh the proportionality costs documented in the UK's 2024 result." PR: "Astrolia should adopt list proportional representation because the UK's 2024 election — where 33.7% of the vote bought 63.2% of the seats — shows FPTP can produce outcomes that badly misrepresent the electorate, a risk Astrolia should design out from the start." MMP: "Astrolia should adopt mixed-member proportional representation because it can capture FPTP's local-representation benefit while compensating for the disproportionality the UK's 2024 result demonstrates." (Accept any arguable recommendation of ONE system.)
• Part 3 (model): Citing "33.7% of the vote converted into 63.2% of the seats" to argue PR — the gap shows FPTP can mechanically hand a party a governing majority most voters did not choose, a risk a brand-new democracy has no reason to build in deliberately. Or citing the same 63.2% figure to argue FPTP — the system reliably manufactures a working majority even from a fragmented vote, and for a potentially unstable new democracy that decisiveness may be worth the proportionality cost. Or citing the D'Hondt-vs-FPTP comparison (A wins 5/3/2 split under PR vs. all 10 under FPTP) to argue that Astrolia's choice of SYSTEM, not voters' preferences alone, determines how power is distributed. Full marks require an exact figure + reasoning that connects rather than restates.
• Part 4 (model, by thesis): Against PR/MMP: coalition governments can be slower to form and can hand disproportionate power to small kingmaker parties, a real risk for a brand-new democracy needing early stability; accountability also suffers when voters can't clearly identify which coalition partner to blame. Against FPTP: the UK's own 2024 result is direct evidence FPTP can hand a governing majority on barely a third of the vote, which critics argue undermines the legitimacy a new democracy most needs at its founding; FPTP also tends (Duverger's law) to squeeze out smaller or regional voices a diverse new country may want represented. Against MMP: more complex to administer and explain than either "pure" system — a real cost when building an institution from scratch. Full credit = a real concession + a reasoned reply or honest revision.

Fact-and-source-accuracy gate — PASS: all cited figures (Labour 411/650 seats, 63.2%, on 33.7% of the vote; Reform UK 14.3% of the vote, 5 seats, 0.8%; the D'Hondt worked example) are verified against the House of Commons Library's official research briefing CBP-10009 (commonslibrary.parliament.uk/research-briefings/cbp-10009/) and a live Python re-run of the D'Hondt arithmetic. No fabricated statistic or source appears. Evenhandedness check — PASS: the scenario is arguable across all four system families; model answers are supplied for FPTP, PR, and MMP recommendations; the rubric grades reasoning and charity, never the system chosen.

Canvas placement block

canvas_object    = Assignment
title            = "Week 11 Assignment — Designing an Electoral System (traditional)"
assignment_group = "Assignments"
points_possible  = 100
grading_type     = points
assignment_type  = traditional
submission_types = [online_upload, online_text_entry]
due_offset_days  = 6
published        = true
rubric_ref       = "week-11-assignment-rubric"
provenance       = "~ Prof. Halloran's edition · Fall 2026 · built with thecoursemaker.com"