Quantitative Literacy Through Social Science: Don’t Be Afraid of Data!

International Conference on College Teaching and Learning

April 11, 2012

Linda DettermanLynette Hoelter

ICPSR, Univ. of Michigan

Session Outline• Defining “quantitative literacy (QL)” and

“data”• Why the emphasis on quantitative literacy?• “But, I teach English…

– …. I don’t ‘do’ data”– …. my students don’t ‘do’ data”– …. what does quantitative literacy mean for

me?”• Tools for incorporating data in the classroom• Evidence of effectiveness from social

sciences

Defining Quantitative Literacy/Reasoning, Numeracy

“Statistical literacy, quantitative literacy, numeracy --Under the hood, it is what do we want people to be able to do: Read tables and graphs and understand English statements that have numbers in them. That’s a good start,” said Milo Schield, a professor of statistics at Augsburg College and a vice president of the National Numeracy Network.

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

• Skills learned & used within a context• Skills:

– Reading and interpreting tables or graphs and to calculating percentages and the like

– Working within a scientific model (variables, hypotheses, etc.)

– Understanding and critically evaluating numbers presented in everyday lives

– Evaluating arguments based on data– Knowing what kinds of data might be useful in

answering particular questions• For a straightforward definition/skill list, see

Samford University’s (not social science specific)

What do we mean by “data”?• Definitions differ by context. Data can be:

– Citing another author who supports your point– Analysis of newspaper articles, blogs, Twitter feeds,

commercials, etc. looking for themes– The result of an in-depth interview or observation– Information from medical tests, experiments, and

other “scientific” exercises• For this presentation, “data” refers to

summary information presented numerically in graphs, charts, or tables and the underlying survey results.

From Where Do Data Come?• Administrative records (e.g., human

resource files, police records)• Census and other government data

collections• Individuals responding to a survey

– Highly standardized– Recorded (“coded”) as numbers and these

numbers can be used in combination to say something about the group of people who responded

Why is QL Important?

• Critical for a democratic society (Steen 2001)– Informed citizenry – must be able to make

sense of information coming from multiple sources.

– “The wall of ignorance between those who are quantitatively literate and those who are not can threaten democratic culture.

– Quantitative literacy largely determines an individual’s capacity to control his or her quality of life and to participate effectively in social decision-making” (MAA 2004: xii)

Importance (Con’t)• Job skills

Why QL Across the Curriculum?

• “Quantitative literacy largely determines an individual’s capacity to control his or her quality of life and to participate effectively in social decision-making.

• Educational policy and practice have fallen behind the rapidly changing data-oriented needs of modern society, and undergraduate education is the appropriate locus of leadership for making the necessary changes

• QL is not about ‘basic skills’ but rather, like reading and writing, is a demanding college-level learning expectation that cuts across the entire undergraduate curriculum

• The current calculus-driven high school curriculum is unlikely to produce a quantitatively literate student population” (MAA 2004:xii)

QL Outside of Math/Statistics

• Other disciplines provide context for numbers, giving them meaning

• More repetition of skills, better learning

• Inclusion in multiple settings reduces student anxiety

• Teacher anxiety can be reduced with tools (pre-made exercises, interpretations given)

How to Include Data• Start class with a data-based news article• Have students interpret charts/graphs from

popular media and critique news articles• Require empirical evidence to support claims

in essays• Question banks and exercises allow students

to work with surveys and the resulting data• Have students collect data• Engage students by having them find maps,

graphs, or other data that provide examples of course content.

Tools for Faculty

• Data archives– Public opinion– Topic-specific archives

• Quantitative news blogs• Pre-made exercises, pedagogical

examples• Collections of resources

Public Opinion Data• Roper Center for Public Opinion

Research http://www.ropercenter.uconn.edu

• Gallup: http://www.gallup.com• NORC reports & data:

www.norc.org/Research/DataFindings• Pew Social & Demographic Trends:

http://www.pewsocialtrends.org/

Topic-specific Archives

• Association of Religion Data Archives(www.thearda.com)• Sociometrics (family, AIDS, maternal

drug abuse, etc.)

News Blogs & Quick Facts

• TeachingWithData.org – Data in the News

• U.S. Census Newsroom • Other government sources;

organizations – beware of credibility

Collections of Resources

• Science Education Resource Center (Carleton College – pedagogical materials)

• TeachingWithData.org• ICPSR

– Online Learning Center– Modules– Tools (SSVD, Bibliography, SDA)

Arguments and Evidence from Social Sciences• Increased learning

– Makes course content relevant to students– Emphasizes substantive points– Higher student engagement (typically)

• Better sense of field– Less disconnect between substantive and

technical courses– Learn how social scientists actually work

More Arguments/Evidence

• Provides students with marketable skills– ASA survey – statistical knowledge

most widely represented on resumes– Enhances writing and critical thinking

How might you use survey or other data in YOUR course? Other ideas? Challenges?

Questions???

• For more information: – Lynette Hoelter (lhoelter@umich.edu)– Linda Detterman (

lindamd@umich.edu)