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- (-) Remove Introductory Biology filter Introductory Biology
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- (-) Remove Ability to use quantitative reasoning filter Ability to use quantitative reasoning
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).
Modeling the Research Process: Authentic human physiology research in a large non-majors courseLearning ObjectivesStudents will be able to:
- Read current scientific literature
- Formulate testable hypotheses
- Design an experimental procedure to test their hypothesis
- Make scientific observations
- Analyze and interpret data
- Communicate results visually and orally
Quantifying and Visualizing Campus Tree PhenologyLearning ObjectivesThe Learning Objectives of this lesson span across the entire semester.
- Observe and collect information on phenological changes in local trees.
- Become familiar with a database and how to work with large datasets.
- Analyze and visualize data from the database to test their hypotheses and questions.
- Develop a research proposal including empirically-driven questions and hypotheses.
- Synthesize the results of their analysis in the context of plant biodiversity and local environmental conditions.
Dynamic Daphnia: An inquiry-based research experience in ecology that teaches the scientific process to first-year...Learning ObjectivesStudents 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.
CURE-all: Large Scale Implementation of Authentic DNA Barcoding Research into First-Year Biology CurriculumLearning ObjectivesStudents will be able to: Week 1-4: Fundamentals of Science and Biology
- List the major processes involved in scientific discovery
- List the different types of scientific studies and which types can establish causation
- Design experiments with appropriate controls
- Create and evaluate phylogenetic trees
- Define taxonomy and phylogeny and explain their relationship to each other
- Explain DNA sequence divergence and how it applies to evolutionary relationships and DNA barcoding
- Define and measure biodiversity and explain its importance
- Catalog organisms using the morphospecies concept
- Geographically map organisms using smartphones and an online mapping program
- Calculate metrics of species diversity using spreadsheet software
- Use spreadsheet software to quantify and graph biodiversity at forest edges vs. interiors
- Write a formal lab report
- Extract, amplify, visualize and sequence DNA using standard molecular techniques (PCR, gel electrophoresis, Sanger sequencing)
- Explain how DNA extraction, PCR, gel electrophoresis, and Sanger sequencing work at the molecular level
- Trim and assemble raw DNA sequence data
- Taxonomically identify DNA sequences isolated from unknown organisms using BLAST
- Visualize sequence data relationships using sequence alignments and gene-based phylogenetic trees
- Map and report data in a publicly available online database
- Share data in a formal scientific poster
Homologous chromosomes? Exploring human sex chromosomes, sex determination and sex reversal using bioinformatics...Learning ObjectivesStudents successfully completing this lesson will:
- Practice navigating an online bioinformatics resource and identify evidence relevant to solving investigation questions
- Contrast the array of genes expected on homologous autosomal chromosomes pairs with the array of genes expected on sex chromosome pairs
- Use bioinformatics evidence to defend the definition of homologous chromosomes
- Define chromosomal sex and defend the definition using experimental data
- Investigate the genetic basis of human chromosomal sex determination
- Identify at least two genetic mutations can lead to sex reversal
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.
Promoting Climate Change Literacy for Non-majors: Implementation of an atmospheric carbon dioxide modeling activity as...Learning Objectives
- Students will be able to manipulate and produce data and graphs.
- Students will be able to design a simple mathematical model of atmospheric CO2 that can be used to make predictions.
- Students will be able to conduct simulations, analyze, interpret, and draw conclusions about atmospheric CO2 levels from their own computer generated simulated data.