You are here
Search found 3 items
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).
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
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.”)