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A clicker-based case study that untangles student thinking about the processes in the central dogmaLearning ObjectivesStudents will be able to:
- explain the differences between silent (no change in the resulting amino acid sequence), missense (a change in the amino acid sequence), and nonsense (a change resulting in a premature stop codon) mutations.
- differentiate between how information is encoded during DNA replication, transcription, and translation.
- evaluate how different types of mutations (silent, missense, and nonsense) and the location of those mutations (intron, exon, and promoter) differentially affect the processes in the central dogma.
- predict the molecular (DNA size, mRNA length, mRNA abundance, and protein length) and/or phenotypic consequences of mutations.
Coevolution or not? Crossbills, squirrels and pineconesLearning Objectives
- Define coevolution.
- Identify types of evidence that would help determine whether two species are currently in a coevolutionary relationship.
- Interpret graphs.
- Evaluate evidence about whether two species are coevolving and use evidence to make a scientific argument.
- Describe what evidence of a coevolutionary relationship might look like.
- Distinguish between coadaptation and coevolution.
An active-learning lesson that targets student understanding of population growth in ecologyLearning ObjectivesStudents will be able to:
- Calculate and compare population density and abundance.
- Identify whether a growth curve describes exponential, linear, and/or logistic growth.
- Describe and calculate a population's growth rate using linear, exponential, and logistic models.
- Explain the influence of carrying capacity and population density on growth rate.
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.