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Science or Not Lecture Notes and Sample Class Activities

Lecture overview

This module introduces students to scientific inquiry and data-driven thinking. Working in small groups, students evaluate various claims about things that are “scientifically proven”. They create a hypothesis and design an experiment to test these claims. Students also 1) evaluate instances in which observational experiments are necessary, 2) construct a graph from a data set, and 3) draw conclusions from the data set.

Inquiry Learning Outcomes

At the end of this module, students will be able to:

  1. Distinguish among ideas that can and cannot be tested by science; evaluate statements and determine which are scientific or and which are not scientific.
  2. Create and defend a scientific argument by identifying and evaluating valid sources of scientific evidence.
  3. Distinguish among the scientific terms: theory, hypothesis, and prediction.
  4. Construct hypotheses to explain biological phenomena:
    1. Propose hypotheses that are appropriate to the given scenario or question.
    2. Evaluate several hypotheses to select the one which best explains observations, or is best supported by data.
    3. Predict what would be most likely to occur under given experimental conditions in a test of a specific hypothesis, and justify predictions using biological concepts.
  5. Design experiments to test biological hypotheses:
    1. Identify the dependent and independent variables, and control and experimental treatments in any experiment.
    2. Identify situations in which no “control treatment” is appropriate, and design an experiment where subjects are tested more than once or the experimental treatment levels take a wide range of values.
    3. Justify the steps and procedures for an experiment.
  6. Create graphs from a data set.
    1. Decide what type of graph is the most appropriate type to display a data set.
    2. Decide to which axis each variable should be assigned in order to represent a specific hypothesis properly.
  7. Use experimental results to support or refute a hypothesis:
    1. Interpret graphs and/or raw data with respect to a hypothesis
    2. Distinguish correlation from causation, and correctly attribute phenomena to biological mechanisms.
    3. Demonstrate how to distinguish observations/data resulting from a specific cause from those caused by random chance.
    4. Explain why experimental evidence may lead to multiple interpretations, and propose ways to address this limitation (e.g., many samples should be taken, many related experiments should be performed).
  8. Interpret and communicate scientific ideas effectively
    1. Use the conventions of scientific writing, including images and graphs, e.g. in laboratory reports.
    2. Interpret and paraphrase information from valid sources, such as the textbook and the primary literature.
  9. Explain why hypotheses and even theories may be subject to revision.

Sample Class Activities

  1. Students examine a claim that is “scientifically proven”. Some examples are provided (see below), but students can also search for other claims. These claims can be used to generate class discussion about science v/s not science, where scientific information can be found, and the importance of evidence. (Inquiry 1, Inquiry 2, Inquiry 3)
  2. Students propose a hypothesis and design an experiment to test their “claim”.  Discussion of good hypotheses and experimental design can be generated by comparing hypotheses and experimental design amongst different students/groups. (Inquiry 4, Inquiry 5)
  3. Students consider an experiment on the effects of class attendance to performance in a class. This activity allows students the opportunity to compare controlled experiments to observational experiments. (Inquiry 5)
  4. Students construct a graph from hypothetical class attendance v/s class performance data.  Discussion of appropriate graph type and format can be generated by comparing graphs amongst different students/groups. (Inquiry 6)
  5. Students generate a figure caption for the graph and draw conclusions. This is a good opportunity for discussion about correlation v/s causation, multiple interpretations of data, and revision of conclusions. (Inquiry 7, Inquiry 8, Inquiry 9)
  6. Some clicker questions are provided, which can be interspersed throughout the module or given at the end as a quiz:

Access the slides here