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American Sociological Association August 11, 2009 San Francisco, California

Teaching Quantitative Literacy in Introduction to Sociology. August 11, 2009. American Sociological Association August 11, 2009 San Francisco, California Organizer: William H. Frey. SSDAN Materials. Find this presentation and other training resources at http://ssdan.net/training.html.

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American Sociological Association August 11, 2009 San Francisco, California

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  1. Teaching Quantitative Literacy in Introduction to Sociology August 11, 2009 American Sociological Association August 11, 2009 San Francisco, California Organizer: William H. Frey

  2. SSDAN Materials • Find this presentation and other training resources at http://ssdan.net/training.html

  3. Outline • Quantitative Literacy • Why is it important? • Resources from the Social Science Data Analysis Network (SSDAN) • DataCounts! and WebCHIP • CensusScope • Coming soon! (ICPSR and SSDAN Partnerships) • Assessment Materials • Digital Library (TeachingWithData.org) • Resources from ICPSR’s Online Learning Center (OLC) • Learning Modules and Data

  4. Quantitative Literacy • Importance • Students are participants in a democratic society • Skills include: • Questioning the source of evidence in a stated point • Identifying gaps in information • Evaluating whether an argument is based on data or opinion/inference/pure speculation • Using data to draw logical conclusions • Student Comfort and Aptitude • Over 50% of early undergraduate students report substantial “statistics anxiety” • Using only one or two learning modules has yielded significant increases in students’ comfort • Solution: Introduce students to “real world” data early and often

  5. Quantitative Literacy

  6. SSDAN: Background • Started in 1995 • University-based organization that creates demographic media and makes U.S. census data accessible to policymakers, educators, the media, and informed citizens. • web sites • user guides • hands-on classroom computer materials

  7. SSDAN • DataCounts! (www.ssdan.net/datacounts) • Collection of approximately 85 Data-Driven Learning Modules (DDLMs) • WebCHIP (simple contingency table software) • Datasets (repackaged decennial census and American Community Survey) • Target is lower undergraduate courses • CensusScope (www.CensusScope.org) • Maps, charts, and tables • Demographic data at local, region, and national levels • Key indicators and trends back to 1960 for some variables • Update coming this fall

  8. Quickly connects users to datasets… ..or Data Driven Learning Modules SSDAN: DataCounts!

  9. Brief List of available dataset collections Menu for choosing a dataset for analysis SSDAN: DataCounts!

  10. WebCHIP Demonstration • Starting with a question • Do immigrants who entered the U.S. recently earn less than those who entered decades ago? (How does the year of entry affect earnings for immigrants?) • Does race make a difference? 10

  11. WebCHIP Demonstration Using 2005 American Community Survey data, we will look at the data set: workim05.dat This data set looks at full-time year-round civilian workers age 25+ for race, gender, age, immigration, education and earnings variables. 11

  12. Planning • We will use an extract of the 2005 American Community Survey • What would we expect to see in a table that answers the question? When immigrated Earnings 12

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  17. Planning • Now that we’ve seen the variables and their categories, we know the table headers 17

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  23. Percent-Across Table Percent-Down Table 23

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  26. One table for each control variable category (i.e. one table for each race) 26

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  28. One graph will appear for each control variable category. Select “Next Graph” to view each chart. 28

  29. One graph for each control variable category (i.e. one table for each race) 29

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  32. Quickly connects users to datasets… ..or Data Driven Learning Modules SSDAN: DataCounts!

  33. SSDAN: DataCounts! • Submitting a module: • Sections are clearly laid out • Forces faculty to create modules with specific learning goals in mind. • Makes re-use of module much easier

  34. Faceted browsing to refine the search • Appropriate Grade Levels • Subjects (e.g. Family, Sexuality and Gender) • Learning Time SSDAN: DataCounts! Title Author and Institution Brief Description

  35. SSDAN: DataCounts! • Data Driven Learning Modules are clearly laid out • Easy to read • Instructors can quickly identify whether a module would be relevant to a specific course

  36. SSDAN • DataCounts! • Collection of approximately 85 Data Driven Learning Modules (DDLMs) • WebCHIP (simple contingency table software) • Datasets (repackaged decennial census and American Community Survey) • Target is lower undergraduate courses • CensusScope • Maps, charts, and tables • Demographic data at local, region, and national levels • Key indicators and trends back to 1960 for some variables

  37. SSDAN: CensusScope New ACS data with improved look & feel coming Fall 2009

  38. SSDAN: CensusScope • Charts, Trends, and Tables • All available for states, counties, and metropolitan areas

  39. SSDAN-OLC • SSDAN’s primary focus is to assist in the dissemination of social data into the classroom with sites like DataCounts! and CensusScope • Until recently, ICPSR primarily targeted researchers, the OLC now provides a welcomed Instructors’ portal to ICPSR resources and is continuing its outreach to educators

  40. Student Benefits: Critical thinking skills Increases students’ comfort with quantitative reasoning Many schools have focus on quantitative literacy and related skills ASA charge for exposure “early and often” Engages students with the discipline more fully Better picture of how social scientists work Prevents some of the feelings of “disconnect” between substantive and technical courses Piques student interest Opens the door to the world of data

  41. Looking Ahead • Assessment Tools and Results

  42. Looking Ahead • TeachingWithData.org (October 2009) • Social Science Pathway to the National Science Digital Library • Virtual repository of resources to support the teaching of quantitative social sciences • Data-Driven Learning Modules • Data Sources • Pedagogical Resources • Analysis and Visualization Tools • Other Resources useful to instructors • Collaboration tools • Web 2.0 technologies

  43. Acknowledgements • National Science Foundation • Inter-university Consortium for Political and Social Research • Population Studies Center • Institute for Social Research • University of Michigan

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