Skip to main content

You are here

Filters

Introductory Biology

  • Adult female Daphnia dentifera. Daphnia spp. make a great study system due to their transparent body and their ease of upkeep in a lab.

    Dynamic Daphnia: An inquiry-based research experience in ecology that teaches the scientific process to first-year...

    Learning Objectives
    Students will be able to:
    • Construct written predictions about 1 factor experiments.
    • Interpret simple (2 variables) figures.
    • Construct simple (2 variables) figures from data.
    • Design simple 1 factor experiments with appropriate controls.
    • Demonstrate proper use of standard laboratory items, including a two-stop pipette, stereomicroscope, and laboratory notebook.
    • Calculate means and standard deviations.
    • Given some scaffolding (instructions), select the correct statistical test for a data set, be able to run a t-test, ANOVA, chi-squared test, and linear regression in Microsoft Excel, and be able to correctly interpret their results.
    • Construct and present a scientific poster.
  • Figure 2. ICB-Students come to class prepared to discuss the text
  • This collage contains original images taken by the course instructor. The images show a microscopic view of stomata on the underside of a Brassica rapa leaf (A), B. rapa plants in their growth trays (B), a flowering B. rapa plant (C), and different concentrations of foliar protein (D). Photos edited via Microsoft Windows Photo Editor and Phototastic Collage Maker.

    A flexible, multi-week approach to plant biology - How will plants respond to higher levels of CO2?

    Learning Objectives
    Students will be able to:
    • Apply findings from each week's lesson to make predictions and informed hypotheses about the next week's lesson.
    • Keep a detailed laboratory notebook.
    • Write and peer-edit the sections of a scientific paper, and collaboratively write an entire lab report in the form of a scientific research paper.
    • Search for, find, and read scientific research papers.
    • Work together as a team to conduct experiments.
    • Connect findings and ideas from each week's lesson to get a broader understanding of how plants will respond to higher levels of CO2 (e.g., stomatal density, photosynthetic/respiratory rates, foliar protein concentrations, growth, and resource allocation).
    Note: Additional, more specific objectives are included with each of the four lessons (Supporting Files S1-S4)
  • 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.