Unit 01 · Day 1
From Phenomena to Questions
Transform curiosity into a focused scientific question that identifies observable evidence, measurable variables, and an appropriate method of investigation.
Learning objectives
- Distinguish a broad topic, a scientific phenomenon, and an investigable question.
- Identify a factor that varies and an outcome that can be observed or measured.
- Revise subjective or ambiguous wording into an operationally defined question.
- Select an appropriate evidence pathway: experiment, observation, fieldwork, model, survey, historical record, or dataset.
- Explain what evidence would and would not be sufficient to answer a proposed question.
Materials
- Science notebook or digital portfolio
- Pencil or keyboard
- Three ordinary phenomena from home, school, or the environment
- Optional: Atlas Evidence Analysis and Evidence Citation Studio from the Interactive Science Studio below
Today is a question-design lesson. Do not test hazardous materials, medicines, flames, mains electricity, unknown chemicals, biological samples, human-subject interventions, wildlife handling, road behavior, or any activity that requires professional supervision. A strong scientific question can be designed before any investigation is authorized.
1. Begin with a phenomenon, not an answer
A phenomenon is an observable event, pattern, relationship, or process that invites explanation. Scientists begin by noticing something that can be described before deciding why it happens.
Broad topic: melting.
Premature explanation: “Metal makes ice melt faster because metal is hotter.”
Better starting question: How does the surface material beneath an equal-mass ice cube affect the time required for the cube to lose half its initial mass under the same room conditions?
The better question does not assume the explanation. It identifies a comparison, a measurable outcome, and conditions that can later be controlled or documented.
Choose one ordinary phenomenon. Write one sentence containing only what could be observed or measured. Then write a separate sentence containing your current explanation. Label the second sentence hypothesis or interpretation, not fact.
2. Build an investigable question
An investigable question is narrow enough to gather evidence and precise enough that another investigator can understand what would count as a result.
- Factor or comparison: What changes, differs, or is being compared?
- Outcome: What will be observed, counted, timed, measured, classified, or calculated?
- Population or system: What object, organism, dataset, place, or process is being studied?
- Conditions: Which circumstances need to stay consistent or be documented?
- Feasibility: Can the evidence be collected safely, ethically, lawfully, and within available time?
More investigable: How does daily light duration affect the mean stem-height change of the same plant species over seven days when starting size, water volume, container, growing medium, and measurement method are kept consistent?
A detailed question is not automatically a good experiment. The proposed method must still be safe, ethical, practical, and capable of producing evidence relevant to the question.
3. Operational definitions turn vague words into measurable rules
An operational definition states exactly how a variable or outcome will be recognized or measured in the investigation. Words such as best, healthy, strong, effective, fast, and successful are often too ambiguous until a measurement rule is supplied.
Operational version: Which of three named paper-airplane designs has the greatest mean horizontal flight distance across ten launches from the same marked release line using the same paper type and launch procedure?
Rewrite “Which type of music is best for studying?” as a non-intervention question using a supplied or hypothetical dataset. Define the participant group, listening condition, study task, and measured outcome. Do not design an experiment on classmates without appropriate educator review and consent procedures.
4. Not every scientific question requires a controlled experiment
The evidence pathway must fit the question. Forcing every question into an experiment can produce weak or unethical science.
| Question type | Appropriate evidence pathway | Example |
|---|---|---|
| Cause-and-effect under controllable conditions | Controlled experiment | How does wing length affect paper-helicopter descent time? |
| Natural pattern that should not be manipulated | Observation or field study | How does bird-species richness vary among three existing habitats? |
| Past process | Historical records or archived evidence | How has the date of first spring flowering changed in a long-term local record? |
| Large or inaccessible system | Model or simulation | How does changing one model parameter alter projected system behavior? |
| Pattern in existing measurements | Dataset analysis | What relationship appears between two recorded variables, and what causal claims are not justified? |
For each of your three phenomena, write the evidence pathway you would choose and one sentence explaining why that method fits better than the alternatives.
5. Evidence sufficiency: what would actually answer the question?
Before collecting data, identify what evidence would count as relevant and what would remain unresolved. One observation may generate a question but rarely supports a broad causal conclusion. Repeated measurements, comparison conditions, transparent methods, uncertainty, and alternative explanations often matter.
Relevant evidence: repeated descent-time measurements for clearly defined wing lengths under consistent release conditions.
Not enough by itself: one launch, one observer’s impression that a helicopter “looked slower,” or a web page claiming long wings always fall more slowly.
Choose one question you wrote today. List three pieces of evidence that would strengthen an answer and two findings that would still leave the question unresolved.
6. Interactive evidence audit
Open Atlas Evidence Analysis from the Interactive Science Studio. Enter or copy your strongest question into your notebook first. Then classify the parts of your thinking as observation, question, assumption, proposed evidence, and limitation. The tool supports the audit; your notebook remains the evidence of learning.
Write one sentence describing something the tool helped you notice and one sentence describing something the tool could not determine for you.
7. Mentor conference prompt
Use the Mentor button when you want questioning or feedback. Ask the mentor to challenge the clarity of your question without rewriting the entire answer for you. A useful request is: “Which word in my question is hardest to measure, and what evidence would make the question more precise?”
Do not include private identifying information, passwords, grades, medical details, or other sensitive personal data in a mentor or beta submission. The page-level Mentor and Beta controls pass only sanitized public page context.
Portfolio evidence
Submit all four items in your notebook or digital portfolio:
- One phenomenon described without explanation.
- One experimental question with clearly measurable variables.
- One observational, historical, modeling, or dataset question with the evidence pathway identified.
- A short justification explaining what evidence would be sufficient, what would remain uncertain, and one safety or ethical boundary.
Exit check
Can another student identify what would be measured, what evidence pathway would be used, and what conclusion your question could not justify? If not, revise the question once more.
Mastery boundary: This lesson is part of the Unit 01 evidence cycle. Required objective and human-reviewed evidence must meet the course ≥80% mastery standard before the unit is finalized.