Search

Students will be able to...

• Identify their values and interests.
• Identify careers that align with their values and interests.
• Identify academic programs and co-curricular experiences that will prepare them for a career.
• Create the first draft of a BioMap Degree Plan to support achievement of their career goals.
• Articulate how their undergraduate academic experience will prepare them for their future career.
• Use professional communication skills

• Describe how cells can produce proteins at the right time and correct amount. 
• Diagram a bacterial promoter with −35 and −10 elements and the transcription start site.
• Describe how mutational analysis can be used to study promoter sequence requirements.
• Develop a promoter mutation hypothesis and design an experiment to test it.
• Successfully and safely manipulate DNA and Escherichia coli for ligation and transformation experiments. 
• Design an experiment to verify a mutated promoter has been cloned into a destination vector. 
• Design an experiment to measure the strength of a promoter. 
• Analyze data showing reporter protein produced and use the data to assess promoter strength. 
• Define type IIs restriction enzymes.
• Distinguish between type II and type IIs restriction enzymes.
• Explain how Golden Gate Assembly (GGA) works.
• Measure the relative strength of a promoter compared to a standard promoter.  

Students will be able to:

• Describe how the scientific method can be used to answer real-world problems.
• Define the basic components of an experiment.
• Predict how tolerance of extreme temperatures and phenotypic plasticity may influence individual fitness and ultimately shape the evolution of organisms.
• Understand the basic principles of climate change and evaluate how these changes in temperature regimes will impact organisms.

1. Test hypotheses related to the role of ACTN3 in skeletal muscle function.
2. Explain how polymorphic variants of the ACTN3 gene affect protein structure and function.
3. List and explain the differences between fast twitch and slow twitch muscle fibers.
4. List and explain possible roles of the ACTN3 protein in skeletal muscle function.
5. Find and analyze relevant scientific publications about the relationship between ACTN3 genotype and muscle function.
6. Formulate hypotheses related to the relationship between ACTN3 genotype and skeletal muscle function.
7. Design experiments to test hypotheses about the role of ACTN3 in skeletal muscle function.
8. Statistically analyze experimental results using relevant software.
9. Present experimental results in writing.

Students will:

• Develop a prediction and a testable hypothesis based on class-collected data
• Use a PivotTable to summarize a complex dataset to address the specific question
• Interpret results of the experiment and summarize the findings in an engaging way

• Census an animal population in the same study area using three different methods.
• Quantitatively compare estimates of population size and/or density generated by each method.
• Articulate the assumptions of each method and explain how violations of these assumptions may bias the results in a given scenario.
• Select the most appropriate method for estimating population size and/or density for a given species and habitat. Justify this choice by explaining why it will produce more reliable data in this scenario than other methods.
• Possible extension: Predict how a given method will perform in a different habitat or for a different species and test this hypothesis by querying a national dataset.

• Students will define a Poisson distribution.
• Students will generate a data set on the probability of a T cell being infected with a virus(es).
• Students will predict the likelihood of one observing the mean value of viruses occurring.
• Students will evaluate the outcomes of a random process.
• Students will hypothesize whether a process is Poissonian and design a test for that hypothesis.
• Students will collect data and create a histogram from their data.

• Students will be able to explain how the energy from sugars is transformed into ATP via cellular respiration.
• Students will be able to predict an outcome if there is a perturbation in the cellular respiration pathway.
• Students will be able to state and evaluate a hypothesis.
• Students will be able to interpret data from a graph, and use that data to make inferences about the action of a drug.

Students 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).

Note: Additional, more specific objectives are included with each of the four lessons (Supporting Files S1-S4)

Students will be able to:

• discuss how the immune system functions to maintain homeostasis of the human body, especially during an influenza infection.
• describe how biological factors, such as sex and age, affect immune system functions.
• propose hypotheses regarding the impact of sex hormones and age on the immune response to influenza and vaccine efficacy based on feedback loops.
• design experiments with mammalian model systems and immunology-based lab assays to test hypotheses.
• analyze primary data that support or refute proposed hypotheses.
• communicate findings through poster presentations in a manner similar to a research conference.

Students will:

• Engage in meta-cognitive learning.
• Develop and conduct an authentic scientific inquiry.
• Generate a testable research question based on observations.
• Evaluate different methods of visualizing data.
• Generate and interpret graphs to answer questions.
• Communicate the results of research and the nature of science in oral and written form.
• Place exploratory research into a larger context of the scientific process.
• Participate in citizen science initiatives.
• Collaborate with peers on a scientific task.

Students successfully completing this lesson will be able to:

• Effectively use the bioinformatics databases (SNPedia, the UCSC Genome Browser, and NCBI) to explore SNPs of interest within the human genome.
• Identify three health-related SNPs of personal interest and use the UCSC Genome Browser to define their precise chromosomal locations and determine whether they lie within a gene or are intergenic.
• Establish a list of all genome-wide association studies correlated with a particular health-related SNP.
• Predict which model organism would be most appropriate for conducting further research on a human disease.

Task A Learning Objectives:

• Recognize multiple sources of variability in biological experiments (e.g. organismal variation, measurement variation, environmental variation, etc.).
• Design ways to manage relevant sources of variation (e.g. use precise instruments, average measurements, sample a large number of individuals, use controls during experimental design, use different sampling strategies).

Task B Learning Objectives:

• Identify the salient features of graphical representations.
• Recognize that different types of graphical representations are appropriate for representing different types of data.
• Generate graphical representations of data to answer a specific experimental question.

Task C1 Learning Objectives:

• Develop mathematical expressions for summary statistics (e.g. average, standard deviation) without drawing on conventional resources (e.g. textbooks, internet, course notes).
• Apply summary statistics when representing experimental data and the variation present within that data.

Task C2 Learning Objectives:

• Derive the relationship between sample size and summary statistics by analyzing a data set.

Task D Learning Objectives:

• Predict statistical significance using graphical representations of two samples.
• Explain how summary statistics are used in the equation for a t-statistic.
• Evaluate statistical significance using a t-statistic.
• Explain the relationship between t-statistics, p-values, and conclusions about significance.

Students 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

Students 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