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A Short Laboratory Module to Help Infuse Metacognition during an Introductory Course-based Research ExperienceLearning Objectives
- Students will be able to evaluate the strengths and weaknesses of data.
- Students will be able to employ prior knowledge in formulating a biological research question or hypothesis.
- Students will be able to distinguish a research question from a testable hypothesis.
- Students will recognize that the following are essential elements in experimental design: identifying gaps in prior knowledge, picking an appropriate approach (ex. experimental tools and controls) for testing a hypothesis, and reproducibility and repeatability.
- Students will be able to identify appropriate experimental tools, approaches and controls to use in testing a hypothesis.
- Students will be able to accurately explain why an experimental approach they have selected is a good choice for testing a particular hypothesis.
- Students will be able to discuss whether experimental outcomes support or fail to support a particular hypothesis, and in the case of the latter, discuss possible reasons why.
Air Quality Data Mining: Mining the US EPA AirData website for student-led evaluation of air quality issuesLearning ObjectivesStudents will be able to:
- Describe various parameters of air quality that can negatively impact human health, list priority air pollutants, and interpret the EPA Air Quality Index as it relates to human health.
- Identify an air quality problem that varies on spatial and/or temporal scales that can be addressed using publicly available U.S. EPA air data.
- Collect appropriate U.S. EPA Airdata information needed to answer that/those questions, using the U.S. EPA Airdata website data mining tools.
- Analyze the data as needed to address or answer their question(s).
- Interpret data and draw conclusions regarding air quality levels and/or impacts on human and public health.
- Communicate results in the form of a scientific paper.