TeachingWithData.org Resources for Teaching Quantitative Literacy in the Social Sciences. John Paul DeWitt & Lynette Hoelter University of Michigan ASA Annual Meeting, August 15, 2010. Presentation Outline:. Introducing the project partners Quantitative Literacy
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TeachingWithData.orgResources for Teaching Quantitative Literacy in the Social Sciences
John Paul DeWitt & Lynette Hoelter
University of Michigan
ASA Annual Meeting, August 15, 2010
Quickly connects users to datasets…
..or Data Driven Learning Modules
Brief List of available dataset collections
Menu for choosing a dataset for analysis
Author and Institution
Commands for selecting variables, creating tables, graphing, and recoding
Basic information about the dataset
Running the “marginals” command shows the categories for each variable and frequencies
Students can quickly run simple cross tabulations to see distributions and test hypotheses
Controlling for an additional variable allows for deeper analysis
New ACS data with improved look & feel coming Fall 2010
Shield was dismayed to find that, in a survey of his new students, 44 percent could not read a simple 100 percent row table and about a quarter could not accurately interpret a scatter plot of adult heights and weights.
Chandler, Michael Alison. What is Quantitative Literacy?, Washington Post, Feb. 5, 2009
Calculation: Ability to perform mathematical operations
Interpretation: Ability to explain information presented in a mathematical form (e.g., tables, equations, graphs, or diagrams)
Representation: Ability to convert relevant information from one mathematical form to another (e.g., tables, equations, graphs or diagrams)
Analysis: Ability to make judgments based on quantitative analysis
Method selection: Ability to choose the mathematical operations required to answer a research question
Estimation/Reasonableness Checks: Ability to recognize the limits of a method and to form reasonable predictions of unknown quantities
Communication: Ability to use appropriate levels and types of quantitative information (data, reasoning, tools) to support a conclusion or explain a situation in a way that takes the audience into account.
Find/Identify/Generate Data: Ability to identify or generate appropriate information to answer a question
Research design: Understand the links between theory and data
Confidence: Level of comfort in performing and interpreting a method of quantitative analysis
Often cited by students as something “tangible” that they have learned
Definable skill set useful in many career paths
Easy to tie to everyday life
“Data in the News” feature – good way to bring in current events
Include resources for high school teachers
Ability to link data to analysis and/or visualization tools
Ability for faculty to rate and comment on resources
Peer-reviewed materials and capability for faculty to upload their own resources
Community building through professional associations and networks of users
What have you tried?
What has worked best?
Favorites we should include in TwD?
PI: George C. Alter, ICPSR
Co-PI: William H. Frey, SSDAN
Funded by National Science Foundation grant DUE-0840642