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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.”)
A first lesson in mathematical modeling for biologists: RocsLearning Objectives
- Systematically develop a functioning, discrete, single-species model of an exponentially-growing or -declining population.
- Use the model to recommend appropriate action for population management.
- Communicate model output and recommendations to non-expert audiences.
- Generate a collaborative work product that most individuals could not generate on their own, given time and resource constraints.
In-class peer grading of daily quizzes increases feedback opportunitiesLearning ObjectivesEach of these objectives are illustrated with a succinct slide presentation or other supplemental material available ahead of class time through the course administration system. Learners found it particularly helpful to have video clips that remind them of mathematical manipulations available (in the above example objective c). Students understand that foundational objectives tend to be the focus of the quiz (objectives a-d) and that others will be given more time to work on together in class (objectives e-g), but I don't specify this exactly to reduce temptation that 'gamers' take a shortcut that would impact their group work negatively later on. However, the assignment for a focused graded group activity is posted as well, so it is clear what we are working towards; if desired individuals could prepare ahead of the class.
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.