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- (-) Remove Introductory Biology filter Introductory Biology
- (-) Remove Interpreting results/data filter Interpreting results/data
- (-) Remove Ability to tap into the interdisciplinary nature of science filter Ability to tap into the interdisciplinary nature of science
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.
Exploring the March to Mars Using 3D Print ModelsLearning Objectives
- Students will be able to describe the major aspects of the Mars Curiosity Rover missions.
- Students will be able to synthesize information learned from a classroom jigsaw activity on the Mars Curiosity Rover missions.
- Students will be able to work in teams to plan a future manned mission to Mars.
- Students will be able to summarize their reports to the class.
Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence...Learning ObjectivesAt the end of this lesson, students will be able to:
- Define similarity in a non-biological and biological sense when provided with two strings of letters.
- Quantify the similarity between two gene/protein sequences.
- Explain how a substitution matrix is used to quantify similarity.
- Calculate amino acid similarity scores using a scoring matrix.
- Demonstrate how to access genomic data (e.g., from NCBI nucleotide and protein databases).
- Demonstrate how to use bioinformatics tools to analyze genomic data (e.g., BLASTP), explain a simplified BLAST search algorithm including how similarity is used to perform a BLAST search, and how to evaluate the results of a BLAST search.
- Create a nearest-neighbor distance matrix.
- Create a multiple sequence alignment using a nearest-neighbor distance matrix and a phylogram based on similarity of amino acid sequences.
- Use appropriate bioinformatics sequence alignment tools to investigate a biological question.
Does it pose a threat? Investigating the impact of Bt corn on monarch butterfliesLearning ObjectivesStudents will be able to:
- Apply genetics concepts to a relevant case study of Bt corn and monarch butterflies
- Read figures and text from primary literature
- Identify claims presented in scientific studies
- Evaluate data presented in scientific studies
- Critically reason using data
- Evaluate the consequences of GM technology on non-target organisms
- Communicate scientific data orally
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.
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
Building Trees: Introducing evolutionary concepts by exploring Crassulaceae phylogeny and biogeographyLearning ObjectivesStudents will be able to:
- Estimate phylogenetic trees using diverse data types and phylogenetic models.
- Correctly make inferences about evolutionary history and relatedness from the tree diagrams obtained.
- Use selected computer programs for phylogenetic analysis.
- Use bootstrapping to assess the statistical support for a phylogeny.
- Use phylogenetic data to construct, compare, and evaluate the role of geologic processes in shaping the historical and current geographic distributions of a group of organisms.
Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active TeachingLearning Objectives
- From raw RNAseq data, run a basic analysis culminating in a list of differentially expressed genes.
- Explain and evaluate statistical tests in RNAseq data. Specifically, given the output of a particular test, students should be able to interpret and explain the result.
- Use the Linux command line to complete specified objectives in an RNAseq workflow.
- Generate meaningful visualizations of results from new data in R.
- (In addition, each chapter of this lesson plan contains more specific learning objectives, such as “Students will demonstrate their ability to map reads to a reference.”)
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
Teaching the Biological Relevance of Chemical Kinetics Using Cold-Blooded Animal BiologyLearning ObjectivesStudents will be able to:
- Predict the effect of reaction temperature on the rate of a chemical reaction
- Interpret a graph plotted between rate of a chemical reaction and temperature
- Discuss chemical kinetics utilizing case studies of cold-blooded animals
You and Your Oral Microflora: Introducing non-biology majors to their “forgotten organ”Learning ObjectivesStudents will be able to:
- Explain both beneficial and detrimental roles of microbes in human health.
- Compare and contrast DNA replication as it occurs inside a cell versus in a test tube
- Identify an unknown sequence of DNA by performing a BLAST search
- Navigate sources of scientific information to assess the accuracy of their experimental techniques
Follow the Sulfur: Using Yeast Mutants to Study a Metabolic PathwayLearning ObjectivesAt the end of this lesson, students will be able to:
- use spot plating techniques to compare the growth of yeast strains on solid culture media.
- predict the ability of specific met deletion strains to grow on media containing various sulfur sources.
- predict how mutations in specific genes will affect the concentrations of metabolites in the pathways involved in methionine biosynthesis.