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  • Plant ecology students surveying vegetation at Red Hills, CA, spring 2012.  From left to right are G.L, F.D, A.M., and R.P.  Photo used with permission from all students.

    Out of Your Seat and on Your Feet! An adaptable course-based research project in plant ecology for advanced students

    Learning Objectives
    Students will:
    • Articulate testable hypotheses. (Lab 8, final presentation/paper, in-class exercises)
    • Analyze data to determine the level of support for articulated hypotheses. (Labs 4-7, final presentation/paper)
    • Identify multiple species of plants in the field quickly and accurately. (Labs 2-3, field trip)
    • Measure environmental variables and sample vegetation in the field. (Labs 2-3, field trip)
    • Analyze soil samples using a variety of low-tech lab techniques. (Open labs after field trip)
    • Use multiple statistical techniques to analyze data for patterns. (Labs 4-8, final presentation/paper)
    • Interpret statistical analyses to distinguish between strong and weak interactions in a biological system. (Labs 4-7, final presentation/paper)
    • Develop and present a conference-style presentation in a public forum. (Lab 8, final presentation/paper)
    • Write a publication-ready research paper communicating findings and displaying data. (Lab 8, final presentation/paper)
  • Possible implementations of a short research module

    A Short Laboratory Module to Help Infuse Metacognition during an Introductory Course-based Research Experience

    Learning 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.
  • Students preforming the leaky neuron activity.

    The Leaky Neuron: Understanding synaptic integration using an analogy involving leaky cups

    Learning Objectives
    Students will able to:
    • compare and contrast spatial and temporal summation in terms of the number of presynaptic events and the timing of these events
    • predict the relative contribution to reaching threshold and firing an action potential as a function of distance from the axon hillock
    • predict how the frequency of incoming presynaptic action potentials effects the success of temporal summation of resultant postsynaptic potentials
  • Image from http://www.epa.gov/airdata/ad_maps.html

    Air Quality Data Mining: Mining the US EPA AirData website for student-led evaluation of air quality issues

    Learning Objectives
    Students 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.
  • 3D Print Models: A collection of 3D models printed from online repository files.