New Pedagogic Methods
Pedagogy: Teaching with Data
Results 41 - 60 of 149 matches
Climate Change and Atlantic Hurricanes: A GIS Inquiry
Chris Van de Ven, Albion College
Students make hypotheses about how hurricane numbers, locations, or intensities have been changing, and then use hurricane tracks, wind speed, barometric pressure, and dates to test their hypotheses.
Tropical Cyclones, Sea Surface Temperature, and Beyond
Danielle Schmitt, Princeton University
The activity will use historical data of sea surface temperature and tropical cyclone origin and/or tracks to identify trends. Students use Arc GIS to explore projected SST changes and predict areas where tropical ...
Comparative Planetary Geomorphology
Jennifer Anderson, Winona State University
This is a laboratory exercise to introduce comparative planetary geomorphology by investigating common geologic features on the Earth, Moon, and Mars. -
What does the core/mantle boundary look like?
Suzanne Baldwin, Syracuse University
This activity explores how earth scientists infer what materials are present at the core mantle boundary and what this boundary might look like. It provides students with the opportunity to contribute to the ...
Investigating the Effect of Warmer Temperatures on Hurricanes
Serena Poli, Eastern Michigan University
Students investigate the link between ocean temperatures and hurricane intensity, analyze instrumental and historical data and speculate on possible future changes.
Scott Cooper, UW-La Crosse
In this activity students explore the evolution of proteins by comparing 2D and 3D alignments of orthologs and paralogs.
Writing a Wikipedia Genetic Disease Article
Writing a Wikipedia article about a genetic disease is a good culminating activity for a genetics course or module, as it requires synthesizing and interpreting a wide range of genetic information. This assignment also includes a potential service component, which is normally very difficult in genetics.
Long Term Ecological Resources
Scott Cooper, UW-La Crosse
Students analyze data on temperature and precipitation collected from 26 different Long Term Ecological Research sites and compare them with annual net primary productivity. The students then form an ecological rule to explain their results.
Scott Cooper, UW-La Crosse
In this activity, students are assigned different alleles of the gene for phenylalanine hydroxylase to research using OMIM (Online Mendelian Inheritance in Man). They are then asked to both explain and illustrate how this mutation may cause the disease phenylketonuria (PKU).
An active problem-based assignment that uses the Genbank database to teach the basics of molecular biology and molecular evolution
Plant Pest Control
This learning experience introduces participants to scientific inquiry, hypothesis formation, experimental design, data analysis, and interpretation.
Monohybrid Fruit Fly Crosses: A Simulation
This assignment uses a computer simulation of fruit fly genetics to have students design and interpret monohybrid crosses of a trait with simple dominant and recessive alleles. Detailed instructions with animated examples, background material, a sample report and a rubric are included.
Using an Applet to Demonstrate Confidence Intervals
Students will utilize an applet to further expand their knowledge of confidence intervals.
Influence of Outliers on Correlation
In this visualization activity, students will observe their instructor create a scatterplot and observe how the correlation coefficient changes when outlier points are added. Students are then given a follow up assignment which guides them through the applet. In addition, the assignment provides insight about outliers and their effect on correlation.
Coke vs. Pepsi Taste Test: Experiments and Inference about Cause
This lesson plan and activity are based on material from the NSF-funded AIMS Project (Garfield, delMas and Zieffler, 2007). For more information contact Joan Garfield at firstname.lastname@example.org
The Coke vs. Pepsi Taste Test Challenge has students design and carry out an experiment to determine whether or not students are able to correctly identify two brands of cola in a blind taste test. In the first ...
Reese's Pieces Activity: Sampling from a Population
This activity is based on an adaptation by Joan Garfield and Dani Ben-Zvi of an activity from Rossman and Chance (2000), Workshop Statistics: Discovery with Data, 2nd Edition.
This activity uses simulation to help students understand sampling variability and reason about whether a particular samples result is unusual, given a particular hypothesis. By using first candies, then a web applet, and varying sample size, students learn that larger samples give more stable and better estimates of a population parameter and develop an appreciation for factors affecting sampling variability.
Simulating Size and Power Using a 10-Sided Die
Erin Blankenship, University of Nebraska--Lincoln
This group activity illustrates the concepts of size and power of a test through simulation. Students simulate binomial data by repeatedly rolling a ten-sided die, and they use their simulated data to estimate the size of a binomial test.
Simulating the Effect of Sample Size on the Sampling Distribution of the Mean
David Lane, Rice University
A java applet that simulates the sampling distribution of the mean. It allows students to explore the effect of sample size.
Simulating a P-value for Testing a Correlation with Fathom
Robin Lock, St. Lawrence University
This activity has students use Fathom to test the correlation between attendance and ballpark capacity of major league baseball teams by taking a sample of actual data and scrambling one of the variables to see how the correlation behaves when the variables are not related. After displaying the distribution of correlations for many simulated samples, students find an approximate p-value based on the number of simulations that exceed the actual correlation.
Stream Characteristics Lab
Wendy Van Norden, harvard-westlake school
Students determine the relationship between the sinuosity of a river and its gradient by calculating gradients and sinuosity, and generating a graph on Excel. They then test the relationship by making measurements on a picture generated on Google Earth.