{"id":18,"date":"2018-07-30T09:00:49","date_gmt":"2018-07-30T14:00:49","guid":{"rendered":"https:\/\/wp.geneseo.edu\/ibis-curriculum\/?p=18"},"modified":"2018-10-30T16:16:41","modified_gmt":"2018-10-30T20:16:41","slug":"science-or-not-lecture-notes","status":"publish","type":"post","link":"https:\/\/wp.geneseo.edu\/ibis-curriculum\/science-or-not-lecture-notes\/","title":{"rendered":"Science or Not Lecture Notes and Sample Class Activities"},"content":{"rendered":"

Lecture overview<\/strong><\/h2>\n

This module introduces students to scientific inquiry and data-driven thinking. Working in small groups, students evaluate various claims about things that are \u201cscientifically proven\u201d. 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.<\/span><\/p>\nInquiry Learning Outcomes<\/span>

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At the end of this module, students will be able to:<\/span><\/p>\n

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  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.<\/span><\/li>\n
  2. Create and defend a scientific argument by identifying and evaluating valid sources of scientific evidence.<\/span><\/li>\n
  3. Distinguish among the scientific terms: theory, hypothesis, and prediction.<\/span><\/li>\n
  4. Construct hypotheses to explain biological phenomena:<\/span>\n
      \n
    1. Propose hypotheses that are appropriate to the given scenario or question.<\/span><\/li>\n
    2. Evaluate several hypotheses to select the one which best explains observations, or is best supported by data.<\/span><\/li>\n
    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.<\/span><\/li>\n<\/ol>\n<\/li>\n
    4. Design experiments to test biological hypotheses:<\/span>\n
        \n
      1. Identify the dependent and independent variables, and control and experimental treatments in any experiment.<\/span><\/li>\n
      2. Identify situations in which no \u201ccontrol treatment\u201d is appropriate, and design an experiment where subjects are tested more than once or the experimental treatment levels take a wide range of values.<\/span><\/li>\n
      3. Justify the steps and procedures for an experiment.<\/span><\/li>\n<\/ol>\n<\/li>\n
      4. Create graphs from a data set.<\/span>\n
          \n
        1. Decide what type of graph is the most appropriate type to display a data set.<\/span><\/li>\n
        2. Decide to which axis each variable should be assigned in order to represent a specific hypothesis properly.<\/span><\/li>\n<\/ol>\n<\/li>\n
        3. Use experimental results to support or refute a hypothesis:<\/span>\n
            \n
          1. Interpret graphs and\/or raw data with respect to a hypothesis<\/span><\/li>\n
          2. Distinguish correlation from causation, and correctly attribute phenomena to biological mechanisms.<\/span><\/li>\n
          3. Demonstrate how to distinguish observations\/data resulting from a specific cause from those caused by random chance.<\/span><\/li>\n
          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). <\/span><\/li>\n<\/ol>\n<\/li>\n
          5. Interpret and communicate scientific ideas effectively<\/span>\n
              \n
            1. Use the conventions of scientific writing, including images and graphs, e.g. in laboratory reports.<\/span><\/li>\n
            2. Interpret and paraphrase information from valid sources, such as the textbook and the primary literature.<\/span><\/li>\n<\/ol>\n<\/li>\n
            3. Explain why hypotheses and even theories may be subject to revision.<\/span><\/li>\n<\/ol>\n<\/div>\n

              Sample Class Activities<\/strong><\/h3>\n
                \n
              1. Students examine a claim that is \u201cscientifically proven\u201d. <\/span>Some examples are provided (see below)<\/span>, 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)<\/span><\/li>\n
              2. Students propose a hypothesis and design an experiment to test their \u201cclaim\u201d. \u00a0Discussion of good hypotheses and experimental design can be generated by comparing hypotheses and experimental design amongst different students\/groups. (Inquiry 4, Inquiry 5)<\/span><\/li>\n
              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)<\/span><\/li>\n
              4. Students construct a graph from hypothetical class attendance v\/s class performance <\/span>data<\/span><\/a>. \u00a0Discussion of appropriate graph type and format can be generated by comparing graphs amongst different students\/groups. (Inquiry 6)<\/span><\/li>\n
              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)<\/span><\/li>\n
              6. Some clicker questions are provided, which can be interspersed throughout the module or given at the end as a quiz:<\/span><\/li>\n<\/ol>\n