Nature of Science Study Notes

Nature of Science

Definition of Science

  • Science: A particular way of knowing about the world, focusing on explanations substantiated by observations and experiments.

    • Quote from The National Academy of Sciences: "Science is a particular way of knowing about the world. In science, explanations are limited to those based on observations and experiments that can be substantiated by other scientists. Explanations that cannot be based on empirical evidence are not part of science."

Key Scientific Terms

Fact

  • Fact: An objective, verifiable observation.

    • Example: Water boils at 100 degrees Celsius.

Principle

  • Principle: A statement based on repeated experimental observation that describes an aspect of the world.

    • Example: Greenhouse effect.

Law

  • Law: A broad concept or principle that describes patterns in nature; often accepted as facts.

    • Examples:

    • Newton’s laws of motion.

    • Boyle’s gas laws.

    • Law of Conservation of Mass.

Theory

  • Theory: An explanation of an observed phenomenon that organizes facts and research from scientists to explain why something happens. It never becomes a fact or a law.

    • Example: Evolutionary theory.

The Scientific Method

  • Science is based on experimentation. Our understanding of the world is continuously refined with new findings.

  • There is no single way to design an experiment, yet it typically follows this general sequence:

    1. Ask a question.

    2. Conduct background research.

    3. Construct a hypothesis.

    4. Test the hypothesis in an experiment.

    5. Analyze data.

    6. Draw conclusions and communicate them.

Ask a Question

  • Observation: A description of something you can see, smell, touch, taste, or hear.

    • Must be objective, not subjective.

    • Example: The ground is wet.

  • Inference: A guess about an object or outcome based on observations.

    • Multiple inferences can arise from a single observation.

    • Examples:

    • It rained.

    • Someone was watering the plants.

Types of Observations

  • Qualitative Observation: Describes qualities.

    • Examples:

    • Green liquid

    • Large hole

    • Sour taste

    • Sweet smell

  • Quantitative Observation: Uses numbers to measure something.

    • Examples:

    • 4 feet long

    • 6 legs

    • 7.2 grams

    • 100 mL

Considerations for Quantitative Data

  1. Precision: How close your measurements are to each other.

    • Consistency and specificity of data are vital.

  2. Accuracy: How close your measurement is to the correct or accepted value.

    • Correctness of data is crucial.

    • State the most specific reading on instruments and estimate one more decimal place.

Experimental Design

Conduct Background Research

  • Determine the purpose/objective of the experiment.

    • Identify existing information related to your question.

    • Purpose/Objective: A statement clearly showing what question is being answered in the investigation.

Construct a Hypothesis

  • Hypothesis: A testable prediction that describes a cause and effect relationship between variables.

    • Format: “If (IV) then (DV).”

    • IV (Independent Variable): The factor the experimenter changes; typically represented on the X-axis.

    • DV (Dependent Variable): The factor that changes in response to the IV; typically represented on the Y-axis.

    • Example Scenario: If different drinks are consumed before a race, then the running speed will vary.

Test the Hypothesis in an Experiment

  • Materials: List all materials required for the experiment, including specifics like quantity and brand.

  • Procedures: Document every step taken in the experiment to allow replication, using action verbs and organizing steps in a numbered format.

Experimental Group(s) and Control Group

  • Experimental Group(s): The group(s) being tested.

  • Control Group: The normal group used for comparison.

Constants in Experimental Design

  • Constants: The aspects of an experiment that remain unchanged to ensure validity.

    • Maintain consistency across variables not being tested to ensure differences measured in the DV are due solely to the IV.

    • Example: Runners' age, gender, breakfast, and training conditions should remain constant.

    • Importance of multiple trials to eliminate chance errors and ensure precision in the data.

Data Analysis and Conclusion

Analyze the Data

  • Results: Organize data in a structured format, such as data tables or graphs for clarity.

  • Analysis: Make statements about data trends and patterns, noting any potential errors.

Draw Conclusions and Communicate

  • State whether your hypothesis was supported or rejected based on experimental data. Note that data does not prove or disprove but supports or fails to support hypotheses.

  • Discuss real-world applications or implications of findings.

Intersection of Science and Technology

  • Science: The advancement of knowledge and understanding questions based on observations.

  • Technology: The advancement of society, focusing on solving practical problems.

    • Defined as the application of scientific discoveries to meet human needs and goals through the development of products and processes.

    • Engineering: Applies scientific and mathematical principles to address challenges effectively.

Technological Design Process

  1. Problem Identification: Clearly define the problem or need.

  2. Solution Design: Brainstorm, research, sketch, and refine the best design, considering constraints like cost, time, and materials.

  3. Implementation: Build and test the solution, making iterative improvements.

  4. Evaluation: Assess if the problem was resolved and constraints met.

Lab Activities and Career Research

  • Lab Activity: Water Tower Challenge - practical application of scientific principles in design.

  • Research and Report: Exploring careers in science to understand various professional pathways and implications of scientific knowledge.