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# Pedagogy Show all Pedagogy

## Teaching with Data

84 matches# Research on Learning

Results 1 - 20 of **84 matches**

Global Temperatures part of Pedagogy in Action:Library:Teaching with Data:Examples

Students analyze the global temperature record from 1867 to the present. Long-term trends and shorter-term fluctuations are both evaluated.

The Modern Atmospheric CO2 Record part of Pedagogy in Action:Library:Teaching with Data:Examples

Students compare carbon dioxide (CO2) data from Mauna Loa Observatory, Barrow (Alaska), and the South Pole over the past 40 years to help them better understand what controls atmospheric CO2.

Earth's Radiation Budget: Part 1 part of Pedagogy in Action:Library:Teaching with Data:Examples

In this activity students explore the Earth's radiation budget using Earth radiation Budget Experiment (ERBE) data archived at the IRI/LDEO Climate Data Library (more info) .

Comparing Carbon Calculators part of Pedagogy in Action:Library:Teaching with Data:Examples

Carbon calculators, no matter how well intended as tools to help measure energy footprints, tend to be black boxes and can produce wildly different results, depending on the calculations used to weigh various ...

Stratospheric Ozone part of Pedagogy in Action:Library:Teaching with Data:Examples

Students explore observational data from ozone-sondes, TOMS, and UARS measurements to learn about changes in stratospheric ozone over the past several decades.

Water Quality-Total Dissolved Solids part of Pedagogy in Action:Library:Teaching with Data:Examples

Students use a microcomputer connected to a conductivity probe to measure the total dissolved solids in local area water samples.

Writing a Wikipedia Genetic Disease Article part of Pedagogy in Action:Library:Teaching with Data:Examples

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.

Monohybrid Fruit Fly Crosses: A Simulation part of Pedagogy in Action:Library:Teaching with Data:Examples

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.

Phenylketonuira part of Pedagogy in Action:Library:Teaching with Data:Examples

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).

Protein Evolution part of Pedagogy in Action:Library:Teaching with Data:Examples

In this activity students explore the evolution of proteins by comparing 2D and 3D alignments of orthologs and paralogs.

Long Term Ecological Resources part of Pedagogy in Action:Library:Teaching with Data:Examples

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.

Sun Spot Analysis part of Pedagogy in Action:Library:Teaching with Data:Examples

Introductory students use Excel to graph monthly mean Greenwich sunspot numbers from 1749 to 2004 and perform a spectral analysis of the data using the free software program "Spectra".

Using Mass Balance to Understand Atmospheric CFCs part of Pedagogy in Action:Library:Teaching with Data:Examples

Students use an interactive online mass balance model help understand the observed levels of chlorofluorocarbon CFC-12 over the recent past.

Plant Pest Control part of Pedagogy in Action:Library:Teaching with Data:Examples

This learning experience introduces participants to scientific inquiry, hypothesis formation, experimental design, data analysis, and interpretation.

When is Dinner Served? Predicting the Spring Phytoplankton Bloom in the Gulf of Maine (College Level) part of Pedagogy in Action:Library:Teaching with GIS:Examples

College-level adaptation of the Earth Exploration Toolbook chapter. Students explore the critical role phytoplankton play in the marine food web.

Searching Genbank part of Pedagogy in Action:Library:Teaching with Data:Examples

An active problem-based assignment that uses the Genbank database to teach the basics of molecular biology and molecular evolution

Reese's Pieces Activity: Sampling from a Population part of Pedagogy in Action:Library:Teaching with Data Simulations:Examples

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 part of Pedagogy in Action:Library:Teaching with Data Simulations:Examples

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 part of Pedagogy in Action:Library:Teaching with Data Simulations:Examples

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 part of Pedagogy in Action:Library:Teaching with Data Simulations:Examples

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.