Project on the screen the headline: '2019 study: Drinking coffee linked to longer life.' Underneath, project two cartoon study designs side-by-side. Study A: surveyed 500,000 adults about coffee habits and tracked deaths over 10 years. Study B: randomly assigned 200 adults to drink 3 cups/day vs 0 cups/day for 10 years. Ask students at their tables (3 min): 'Which study can claim coffee CAUSES longer life? Why?' Cold-call 3 tables. Steer toward: Study A only shows correlation — coffee drinkers might also exercise more, be wealthier, etc. Study B controls those variables by random assignment. Land the punchline: today you become Study B — you'll design the experiment, not just observe. Transition: 'The difference between a real experiment and a survey is CONTROL. Let's break that down.'

1. 12m

   Variables: IV, DV, and Controlled

   Draw on the board the three-column variables table: Independent | Dependent | Controlled, with rows 'What it is' and 'How it's measured.' Walk through using a worked example: 'Does water temperature affect how fast an Alka-Seltzer tablet dissolves?' Fill in: IV = water temperature (°C, thermometer); DV = time to fully dissolve (seconds, stopwatch); Controlled = water volume (50.0 mL graduated cylinder), tablet mass (one whole tablet ~3.2 g), container (250 mL beaker), stirring (none), tablet orientation (dropped flat). Emphasize the rule: ONE IV at a time, or you can't attribute the change. Ask cold-call: 'If I also crushed the tablet in the hot-water trial, what's wrong?' (Two IVs changed — confounded.) Common confusion to address: 'controlled variable' ≠ 'control group.' Controlled variables are factors held constant; a control group is a baseline trial (room-temp water here).

2. 8m

   Hypotheses are not guesses

   Project on screen three candidate statements and ask students to vote (fingers 1, 2, or 3) for which is a real hypothesis: 1) 'I think hot water is better.' 2) 'Alka-Seltzer dissolves faster in hot water.' 3) 'If water temperature increases from 5 °C to 50 °C, then the tablet's dissolve time will decrease, because higher kinetic energy increases collision frequency between water molecules and the tablet surface.' Most will pick 3. Reinforce: a hypothesis is testable, falsifiable, and grounded in prior knowledge (here, kinetic molecular theory from earlier units). Address misconception directly: 'A hypothesis is NOT a guess. It's a prediction with reasoning.' Also address: 'If your data don't support your hypothesis, your experiment did NOT fail. Disconfirmation is valid science — it just means your prediction was wrong, not your method.'

3. 5m

   Data tables and graphs

   Project on the screen a sample data table (5 temperatures, 3 trials each, mean column) paired with the same data plotted as a scatter graph: x-axis 'Water temperature (°C)' from 0–60, y-axis 'Dissolve time (s)' from 0–120. Point out: (a) units in column headers, (b) trials averaged so random error is visible, (c) IV on x-axis, DV on y-axis — always. Ask: 'What's the trend?' (Inverse — higher T, shorter time.) Note that the graph shows error bars on each point; this is how you visualize uncertainty. Tell students they will produce both a table and a graph today.

1. 25m

   Protocol Critique: Spot the Flaws

   Distribute the handout. Pairs have 12 minutes to mark up the protocol and fill in the variables table for what the student INTENDED to test. Then 8 minutes to write 3 specific design improvements. Last 5 minutes: cold-call pairs to share one flaw and one fix. Walk around and check that students are flagging specifics — push back on 'human error' as too vague. The flawed protocol reads: 'Brianna wants to know if surface area affects Alka-Seltzer dissolve rate. She drops a whole tablet into 50 mL of cold tap water at 8 °C and times it. Then she crushes a tablet, drops the powder into 100 mL of hot tap water at 45 °C, and times that. Hot water dissolved faster, so she concludes crushing makes tablets dissolve faster.' Expected flaws students should catch: (1) Three variables changed at once — surface area, volume, AND temperature — so the conclusion about surface area is unsupported. (2) No replication — n=1 per condition. (3) 'Hot tap water' temperature wasn't held constant, only measured once. (4) Conclusion contradicts the stated hypothesis (she set out to test surface area but concluded about crushing in a confounded way). On the board draw the side-by-side diagram of her two setups with all THREE differences highlighted in red — this is the visual anchor.

   Materials

   • Printed flawed protocol handout (one per pair)
   • Highlighters
   • Variables-table template

   Example outputs

   • Flaw: Brianna changed surface area, water volume (50 vs 100 mL), AND temperature (8 vs 45 °C) at the same time. She can't tell which caused the faster dissolve. Fix: hold volume at 50.0 mL and temperature at 22 °C in both trials; only crush the tablet in the experimental condition.
   • Flaw: Only one trial per condition — random variation (timing reflex, tablet defects) isn't averaged out. Fix: run at least 3 trials per condition and report the mean ± range. 'More data is better' is only true if the design is sound first.
2. 50m

   Design Your Own: Alka-Seltzer Rate LabLab

   Each lab group of 3 picks ONE independent variable to test from the menu: (A) water temperature [5 °C, 22 °C, 45 °C], (B) surface area [whole, halved, crushed], or (C) tablet count in fixed volume [½, 1, 2 tablets in 100 mL]. Distribute the lab planning sheet. Minutes 0–10: Groups complete the planning sheet — write hypothesis in If/then/because form, fill the variables table (have students sketch the three-column table in their notebook with all controlled variables explicitly listed), sketch the side-by-side setup diagram with the varied factor circled in red. Teacher signs off before they get reagents. Minutes 10–35: Groups run 3 trials × 3 conditions = 9 trials. Record dissolve time (stopwatch starts when tablet hits water, stops when last solid disappears). Build data table with means. Minutes 35–50: Each group plots IV (x) vs mean DV (y) on graph paper or Desmos, then writes a 4-sentence conclusion: (1) restate the hypothesis, (2) cite specific data ('At 5 °C, mean = 84 s; at 45 °C, mean = 19 s'), (3) supported / not supported, (4) ONE specific source of error and how it could bias results. Walk around: push groups to name specific errors ('I started the timer ~0.3 s late because of reaction lag' — not 'human error'). Check that crushed-tablet groups are using the same MASS not the same number of pieces. Check that temperature groups are RE-measuring temperature at the moment of drop, not 2 minutes earlier.

   Materials

   • Alka-Seltzer tablets (4 per group)
   • 250 mL beakers (3 per group)
   • 100 mL graduated cylinders
   • Thermometers (-10 to 110 °C)
   • Hot plates or access to hot/cold tap water
   • Ice
   • Stopwatches or phone timers
   • Electronic balance (0.01 g)
   • Mortar and pestle (for surface-area groups)
   • Lab notebooks
   • Goggles, aprons

   Example outputs

   • Temperature group: Hypothesis — 'If water temperature increases from 5 °C to 45 °C, then dissolve time will decrease, because higher kinetic energy increases collision frequency at the tablet surface.' Data: 5 °C → 84, 81, 88 s (mean 84.3); 22 °C → 41, 38, 44 s (mean 41.0); 45 °C → 19, 21, 18 s (mean 19.3). Conclusion: hypothesis supported; dissolve time decreased ~4× over a 40 °C range. Source of error: water cooled by ~3 °C during the 22 °C and 45 °C trials before tablet was dropped — would cause the high-T point to read SLOWER than truth, underestimating the effect.
   • Surface-area group: Hypothesis supported — whole tablet 42 s, halved 28 s, crushed 9 s. Source of error: crushed powder partially floated and stuck to beaker walls above water line, so 'fully dissolved' was hard to call — would inflate dissolve-time readings for the crushed condition, making the effect look smaller than it is.

1. A student tests how fertilizer concentration (0%, 1%, 5%) affects bean-plant height after 2 weeks. All plants get 50 mL water/day, the same soil, and the same window. Identify the independent variable, the dependent variable, and TWO controlled variables.

   short answerIV: fertilizer concentration (0%, 1%, 5%). DV: bean-plant height after 2 weeks (cm). Controlled variables (any 2): water volume per day (50 mL), soil type, light exposure (same window), and implicitly plant species, pot size, start date.

2. Which statement best describes a scientific hypothesis?

   multiple choiceC. A testable prediction grounded in prior knowledge, often phrased 'If…then…because….' (Not A 'an educated guess with no reasoning,' not B 'a proven fact,' not D 'the conclusion of an experiment.')

3. Marcus runs an experiment and his data do NOT support his hypothesis. He writes: 'My experiment failed.' Explain in 2–3 sentences why this statement is scientifically incorrect.

   short answerThe experiment did not fail — it produced valid disconfirming evidence. A hypothesis being unsupported means the prediction was wrong, not the method. Disconfirmation is a real, useful scientific outcome and often drives the next round of investigation.

4. A group reports: 'At 50 °C the tablet dissolved in 18 s; at 20 °C it dissolved in 45 s. Average human reaction time on a stopwatch is about 0.25 s.' Calculate the percent uncertainty introduced by reaction time on the 18 s measurement, and state whether this uncertainty alone could explain the difference between the two conditions.

   calculationPercent uncertainty = (0.25 s / 18 s) × 100% ≈ 1.4%. The difference between conditions is 45 − 18 = 27 s, which is ~150% of the 18 s value — far larger than the ~1.4% reaction-time uncertainty. Reaction time alone cannot explain the difference; the temperature effect is real.

• ☐Alka-Seltzer tablets (~5 per group, plan for breakage)
• ☐250 mL beakers (3+ per group)
• ☐100 mL graduated cylinders
• ☐Thermometers (-10 to 110 °C)
• ☐Hot plates and ice (or hot/cold tap access)
• ☐Stopwatches or phone timers
• ☐Electronic balance (0.01 g)
• ☐Mortar and pestle (1 per surface-area group)
• ☐Goggles and aprons (class set)
• ☐Printed flawed-protocol critique handout
• ☐Lab planning sheet with variables table
• ☐Graph paper or Desmos access on lab computers