Week 11 · Biology Lab & Inquiry

Week 11 Biology Lab & Inquiry: Coin-Toss Genetics

Introduction to Biology Free sample edition

Part 1 — The Big Picture

This week you learned that each parent passes exactly one allele of each gene, because the two alleles separate when homologous chromosomes part in meiosis I, and that a Punnett square for two Tt parents predicts genotypes 1:2:1 and phenotypes 3:1. In this lab you test that prediction with two coins at a kitchen table. Each coin stands in for a Tt parent: heads is the dominant allele T and tails is the recessive allele t, and each comes up half the time, the way each allele goes into half the gametes. Flipping both coins makes one offspring. You write a hypothesis, flip 100 times, tally the three genotypes after 20 flips and after 100, compare your counts with the counts the odds predict, and see whether more flips land closer to 3:1. Then you check a chatbot's account of your lab and catch where it garbles a ratio, swaps mitosis for meiosis, scrambles an order, mislabels a structure, oversimplifies dominance, or invents a number.

Time budget: Plan for about 120 minutes.

Part 2 — The Task

Guiding question: How close does a coin-toss model of a cross between two Tt parents come to the 3:1 phenotype ratio, and does it come closer after 100 flips than after 20?

Before you begin — hypothesis: Before you flip, write one hypothesis in the if… then… because… form: if two Tt parents are modeled by two fair coins, then the phenotype counts after 100 flips will land near or far from 3 dominant to 1 recessive, because of a reason about segregation and chance that you can state. Then predict whether your 20-flip tally or your 100-flip tally will sit closer to 3:1.

Workshop data: Your own 100 two-coin flips, or the illustrative fallback tallies

Source: Coin tallies you record yourself at a kitchen table with the procedure in Part 3, counted after the first 20 flips and again after all 100; if you cannot flip coins, use the illustrative fallback tallies printed in the fallback, which were constructed for this lab and are not real data.

Rows: 100 two-coin flips, summarized as 3 genotype rows (TT, Tt, tt) in the tally table, with one column after 20 flips and one after 100 flips; the first scaffold table has 5 rows that name the parts of the test rather than data, and the reasoning table has 3 rows
Columns: genotype, tally after 20 flips, tally after 100 flips, expected count in 100 flips, and the gap from expected
Unit: a count of offspring (two-coin flips) of each genotype

Part 3 — Materials & Procedure

Tools and materials

Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet)
Two coins of any kind, a cup to shake them in if you like, and a pencil and paper or a phone for tallying
A document or notebook for your written answers

Ways of working

virtual-simulation-inquiry
at-home-protocol-and-data-table
figure-and-diagram-interpretation

Procedure

Open a spreadsheet (Google Sheets or any free spreadsheet) or a sheet of paper and make three tally rows labelled TT, Tt, and tt. Decide which coin is parent 1 and which is parent 2, and write down the rule: heads is T, tails is t. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: Three labelled tally rows and a written heads-and-tails rule.
Before you flip, fill in the first table in Part 4: your hypothesis, your prediction, what each coin stands for, what you count, and what you keep the same on every flip. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: The first table has an if… then… because… hypothesis and a prediction for the 20-flip and 100-flip tallies.
Flip both coins together and read them: two heads is TT, one head and one tail is Tt (in either order), and two tails is tt. Make one tally mark in the matching row. Keep flipping the same way, from the same height, onto the same surface. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: One tally mark per two-coin flip, in exactly one of the three rows.
After 20 flips, stop and copy your three tallies into the 20-flip column of the tally table in Part 4. Check that they add to 20. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: Three counts in the 20-flip column that sum to 20.
Keep going until you reach 100 flips in all, counting the first 20, then copy your three tallies into the 100-flip column and check that they add to 100. If you use a spreadsheet, type the three counts into cells B2 to B4 and check that =SUM(B2:B4) returns 100. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: Three counts in the 100-flip column that sum to 100.
Fill in the expected counts for 100 flips from the odds, find each gap from expected, and then add TT and Tt to get the dominant count and divide it by the tt count to get the dominant-to-recessive ratio, once for 20 flips and once for 100. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: Expected counts, three gaps, two dominant counts, and two ratios, each with its sum or division shown.

Fallback route

When to use it: Use this route if you have no coins or cannot flip 100 times at home.

Use the illustrative fallback tallies below, constructed for this lab and not real data, as your tally table, then complete every scaffold table, analysis question, and the critique step from them and submit the same items for equal credit. Fill the empty columns yourself.

This route earns the same credit as the primary route.

Illustrative fallback tallies of two-coin flips, constructed for this lab, that stand in for your own coins.

Fallback model data
Genotype	Tally after 20 flips	Tally after 100 flips
TT	7	24
Tt	10	53
tt	3	23

Part 4 — The Scaffold

Name every part of the test before the first flip, so the model is fair from the start.

Student scaffold table 1
Part of the test	Your answer
Hypothesis (if… then… because…)
Prediction: which tally lands closer to 3:1, the 20-flip or the 100-flip one
What each coin stands for, and what heads and tails mean
What you count on each flip
Two things you keep the same on every flip

Record your tallies, then compare them with the counts the odds predict for 100 flips.

Student scaffold table 2
Genotype	Tally after 20 flips	Tally after 100 flips	Expected count in 100 flips	Gap from expected (100 flips)
TT
Tt
tt
Dominant count (TT + Tt)
Dominant ÷ recessive

Explain the three results that matter most, from the rules of inheritance.

Student scaffold table 3
Question	Your reasoning
Why do TT and Tt both count toward the dominant phenotype?
Which event in meiosis does one coin flip stand for?
Which tally sat closer to 3:1, and why would you expect that?

Part 5 — Analysis Questions

Show the sums and divisions for your dominant count and your dominant-to-recessive ratio after 20 flips and after 100 flips, write the expected counts for 100 flips from the probabilities 1⁄4, 1⁄2, and 1⁄4, and find each gap from expected.
Does your 100-flip evidence support or fail to support the 3:1 prediction? Write one conclusion sentence that uses supports or fails to support rather than proves, and explain why a real run lands near the predicted ratio rather than exactly on it.
Explain what one coin flip models in a real Tt parent, naming the law of segregation and the division of meiosis it comes from, and explain why the genotype ratio 1:2:1 and the phenotype ratio 3:1 are different ratios.
Compare your 20-flip ratio with your 100-flip ratio. Which sat closer to 3:1? Use the law of large numbers, in your own words, to say what you would expect after 1,000 flips.
Choose one and answer it in 3–4 sentences. (a) Coins are a model of a cross, not a real cross: name one way real parents and offspring differ from two fair coins, and say how that limits what your tallies can claim. (b) Your 100 flips are one run: name one way your own flipping could have pushed the counts off the odds, and say how you would reduce it next time.

Part 6 — AI-Critique Moment

Choose one equal-credit critique route. Route A: ask an approved AI tool to critique your completed work, then check its response against your own evidence. Route B is the no-AI equivalent printed below.

Approved tools: Claude, Gemini, ChatGPT, Grok, Microsoft Copilot.

Prompt to paste:

I've pasted my completed Week 11 Biology Lab & Inquiry tables above. I used two coins as two Tt parents, heads for the dominant allele T and tails for the recessive allele t, flipped both coins 100 times, and tallied TT, Tt, and tt. Please do six things. First, give the genotype ratio and the phenotype ratio a cross of two Tt parents predicts, and say whether my tallies support that prediction. Second, check my dominant count, my recessive count, and my dominant-to-recessive ratio, showing each sum and division. Third, put meiosis I and meiosis II in order and say which one separates the two alleles of a gene. Fourth, say which structures carry the T allele and the t allele in a Tt parent: two sister chromatids, or two homologous chromosomes. Fifth, explain in one or two sentences why the dominant allele's trait shows in a Tt offspring. Sixth, tell me the exact percentage of people worldwide who carry a recessive allele for a common trait, with its source.

Test the response for these likely failures:

Chatbots often give the phenotype ratio of a Tt by Tt cross as 1:2:1, which is the genotype ratio, or count only TT as showing the dominant trait.
Chatbots sometimes say the alleles separate during mitosis, or that each parent's body cells split their alleles before the egg or sperm forms.
Chatbots sometimes put meiosis II first, or say sister chromatids separate in meiosis I and homologs in meiosis II.
Chatbots sometimes say the T and t alleles sit on two sister chromatids of one chromosome.
Chatbots often say the dominant allele is stronger, overpowers or destroys the recessive one, or is more common in people.
Asked for a worldwide carrier percentage, chatbots often state a precise figure and cite a source that was never given.

Write 3–5 sentences naming one thing the chatbot got right and at least two places it went wrong or overreached, quoting its words and correcting each with evidence from your own tables or this week's chapter.

Equivalent route (no AI required)

No AI account is required for this lab. Instead of the chatbot, critique this flawed analysis, printed here in full: "My coins gave 24 TT, 53 Tt, and 23 tt, so the phenotype ratio is 24:53:23, which is close to 1:2:1, exactly as Mendel predicted for phenotypes. That shows the T allele is stronger and wipes out the t allele whenever they meet. Each parent passes one allele because the chromosomes split in mitosis, and the two alleles sit on two sister chromatids. Meiosis II happens first and separates the alleles, then meiosis I finishes the job. About 38 percent of people carry a hidden recessive allele for this trait, according to a study." Mark it up: quote each flawed sentence, name what is wrong (a garbled ratio, a mitosis-for-meiosis swap, a mis-ordered process, a mislabeled structure, an over-simplified mechanism, or an invented figure), cite the evidence from your tables or this week's chapter, and write a corrected sentence beneath it. This route assesses the same objectives (Objective 5 and Objective 6) as the chatbot critique, takes comparable effort (about 30 minutes and 200–300 words), is scored by the same scoring criteria for the same credit, and its own submission artifact is the marked-up flawed analysis, posted in place of the chatbot share link and report.

Part 7 — What to Submit

All three completed scaffold tables, filled from your own coins or the illustrative fallback tallies
Written answers to all five analysis questions
The chatbot critique report with its share link, or the equivalent route's marked-up flawed analysis

Deliverable:

A short Biology Lab & Inquiry report on coin-toss genetics: three completed tables (the named parts of the test, the tallies after 20 and 100 flips with the expected counts, gaps, dominant counts, and ratios, and the reasoning about the phenotype, segregation, and the law of large numbers), written answers to five analysis questions, and a critique of a chatbot's account of your lab, or, on the equivalent route, a marked-up correction of the printed flawed analysis. Submit in any accessible file type or as a link; a recorded response may be submitted as audio or video with a transcript, or as text. Choose a written, recorded, or visual form for your answers; every form is graded by the same scoring criteria.

Rubric

The rubric below shows how each submitted part is evaluated; bands are full, partial, or none.

Workshop evaluation criteria
Criterion	Full	Partial	None
Testable hypothesis and the parts of the model	A falsifiable if… then… because… hypothesis and a 20-versus-100 prediction appear before the first flip, the heads-and-tails rule is stated, and what is counted and what is held the same are named.	A hypothesis appears but is not falsifiable or lacks the prediction, or the coin rule, the count, or a held condition is missing.	No hypothesis, or the parts of the model are not named.
Completed tally table with expected counts, gaps, and ratios	Both tally columns come from the student's own flips or the fallback tallies and add to 20 and 100, the expected counts and gaps are correct, and each dominant count and ratio shows its sum and division and is correct for those tallies.	The table is filled, but one or two expected counts, gaps, dominant counts, or ratios are wrong, or the sums and divisions are not shown.	No tallies are recorded, or the tallies are invented rather than flipped or taken from the fallback.
Inheritance analysis: ratios, segregation, and the law of large numbers	Questions 1 to 4 are answered accurately: the conclusion uses supports or fails to support, TT and Tt are both read as dominant with 1:2:1 kept apart from 3:1, one flip is tied to segregation in meiosis I, and the 20-flip and 100-flip ratios are compared through the law of large numbers.	Some of questions 1 to 4 are accurate, but the genotype and phenotype ratios are blurred, segregation is placed in the wrong division, or the two tallies are not compared.	Questions 1 to 4 are missing or inaccurate throughout.
Critique of the chatbot or of the printed flawed analysis	On either route, at least two errors are quoted and corrected with evidence from the student's own tables or the chapter, and one correct point is acknowledged; both routes earn this band equally.	On either route, errors are named but corrected without evidence, or only one error is caught.	No critique appears, or pasted output is submitted without any checking.
Reflection on the limits of the model	The chosen reflection option is answered in 3–4 sentences that tie a specific difference between coins and real parents, or a specific flaw in the flipping, to a concrete change in the test or in what can be claimed.	The reflection is answered but stays general or names no specific change.	No reflection is submitted.

Quality Gate

Every tally comes from your own coin flips or the printed fallback tallies, never from memory or a chatbot.
The 20-flip tallies add to 20 and the 100-flip tallies add to 100.
Each dominant count shows its sum, each ratio shows its division, and each expected count shows the probability it came from.
The hypothesis was written before the first flip and has the if… then… because… form.
TT and Tt are both counted as the dominant phenotype, and the genotype and phenotype ratios are kept apart.
No measurement, percentage, study, or source is invented anywhere in the submission.
The critique quotes the chatbot or the flawed analysis and corrects at least two errors with evidence from your tables or the chapter.

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