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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.
Cutthroat trout in Colorado: A case study connecting evolution and conservationLearning ObjectivesStudents will be able to:
- interpret figures such as maps, phylogenies, STRUCTURE plots, and networks for species delimitation
- identify sources of uncertainty and disagreement in real data sets
- propose research to address or remedy uncertainty
- construct an evidence-based argument for the management of a rare taxon
A flexible, multi-week approach to plant biology - How will plants respond to higher levels of CO2?Learning ObjectivesStudents 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).
Investigating Cell Signaling with Gene Expression DatasetsLearning ObjectivesStudents will be able to:
- Explain the hierarchical organization of signal transduction pathways.
- Explain the role of enzymes in signal propagation and amplification.
- Recognize the centrality of signaling pathways in cellular processes, such as metabolism, cell division, or cell motility.
- Rationalize the etiologic basis of disease in terms of deranged signaling pathways.
- Use software to analyze and interpret gene expression data.
- Use an appropriate statistical method for hypotheses testing.
- Produce reports that are written in scientific style.