Grow Up, Branch Out: Quantitative Literacy for the 21st Century

This interactive video and set of resources was developed to support a faculty workshop offered by the Massachusetts Department of Higher Education in 2019. Special thanks to Robert Awkward, DHE’s Director of Learning Outcomes Assessment, for organizing and providing financial and logistical support for these workshops; and to Mary-Ann Winkelmes, Director of Teaching and Learning at Brandeis University, for co-facilitating the workshops by engaging participants in designing transparent assignments.

Interactive Video (≈20 mins.)

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This H5P interactive video is best experienced full screen.

Click here to view the non-interactive version (33 mins.) via YouTube. The full transcript of this video is also available.

Linked Resources

“More Than a Math Problem”

Massachusetts’ 2009 Sales Tax Increase: 5% to 6.25%
Tracing the Origin of the Massachusetts Sales Tax
Herwick III, Edgar B. WGBH News, January 16, 2018. Includes historical information about the development and various increases in the tax.
Speaker Pushing Sales Tax of 6.25%
Vizer, M. and Drake, J.C. Boston Globe, April 27, 2009. Source of the “1.25 percent increase” claim from the video.
Mass. Governor Signs Transportation Reform Bill
LeBlanc, S. Associated Press, June 26, 2009. The source of the “25 percent increase” claim to which, in fairness, LeBlanc adds appropriate context in the paragraph that follows.
Beyond Mathematics: What is Quantitative Literacy?
Calculation vs. Context: Quantitative Literacy and Its Implications for Teacher Education
Madison, B. L., & Steen, L. A. (Eds.). (2008). June 22-24, 2007, Wingspread Conference Center, Racine, Wisconsin. Mathematical Association of America. (Link above is to full text PDF, made available by Mathematical Association of America.)

“The Case for Quantitative Literacy”

Mathematics and Democracy: The Case for Quantitative Literacy
Steen, L. A. (Ed.). (2001). NCED. (Link above is to full text PDF, made available by Mathematical Association of America.)
Achieving Quantitative Literacy: An Urgent Challenge for Higher Education
Steen, L. A. (Ed.). (2004). MAA Notes No. 62. Mathematical Association of America.
Current Practices in Quantitative Literacy
Gillman, R. (Ed.). (2006). MAA Notes No. 70. Mathematical Association of America.
Shifting Contexts, Stable Core: Advancing Quantitative Literacy in Higher Education
Tunstall, S., Karaali, G., & Piercey, V. (Ed.). (2019). MAA Notes No. 88. Mathematical Association of America.
Why Quantitative Literacy?
Data Never Sleeps 5.0
A report and infographic on the volume of data collected on a daily basis.
How Much Data Do We Create Every Day?
Marr, B. Contributed for With companion video
“Numbers are Tools, Not Truth”
Heard through Dr. Yasmiyn Irizarry‘s Twitter feed.
The Era of Blind Faith in Big Data Must End
O’Neil, C. (2017). TED Conference 2017. See also her book, below.
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
O’Neil, C. (2016). Broadway Books.
Motivated Numeracy and Enlightened Self-Government
Kahan, D. M., Peters, E., Dawson, E. C., & Slovic, P. (2017). Behavioural Public Policy, 1(1), 54-86.
Why Quantitative Literacy? U.S. versus Developed Nations
American Students, Better than Average
Graphic excerpt from: Chang, K. (2013, Sept. 2). “Expecting the Best Yields Results in Massachusetts.” New York Times. Reporting on promising increases in U.S. eighth-grade mathematics scores in the 2011 TIMSS study.
OECD Survey of Adult Skills
Desjardins, R., Thorn, W., Schleicher, A., Quintini, G., Pellizzari, M., Kis, V., & Chung, J. E. (2013). OECD skills outlook 2013: First results from the survey of adult skills. 
Why Quantitative Literacy? The Workforce Mandate
Data Science for Undergraduates: Opportunities and Options
National Academies of Sciences, Engineering, and Medicine. (2018). Washington, DC: The National Academies Press. 
The Quant Crunch: How Demand for Data Science Skills is Disrupting the Job Market
Miller, S., & Hughes, D. (2017). Burning Glass Technologies.
Answering the Call: Designing Authentic Experiences
Transforming Developmental Education: Massachusetts Department of Higher Education
The Department of Higher Education (DHE) in partnership with institutions of public higher education are working together to transform developmental education and have adopted a three-pronged approach to reduce remediation and increase student success: (1) Implementation of mathematics pathways; (2) Support through the co-requisite model; (3) Use of multiple measures.
Answering the Call: Establishing QL Programs
Quantitative Reasoning for College Graduates: A Complement to the Standards
Sons, L. R. (Ed.) (1996). Mathematical Association of America.

“Roots and Trunk: The Big Q”

Quantway: reimagining Freshman Math
Quantway (Carnegie Math Pathways)
Introduction, course descriptions, and how to get connected with this two-semester foundational quantitative literacy program.
Math Pathways (Charles A. Dana Center)
Organizational leadership for creating aligned pathways of introductory math courses appropriate for each students’ major, including (though not limited to) foundations of quantitative reasoning.
QLRA: A Standardized Measure of QL Skills
QLRA: Towards Developing a Quantitative Literacy/Reasoning Assessment Instrument
Gaze, E. C., Montgomery, A., Kiliç-Bahi, S., Leoni, D., Misener, L., & Taylor, C. (2014). Numeracy, 7(2), 4.
New Approaches for Stats & Methods
Liberal learning and the sociology major updated: Meeting the challenge of teaching sociology in the twenty-first century.
McKinney, K., Howery, C. B., Strand, K. J., Kain, E. L., & Berheide, C. W. (2004). Washington, DC: American Sociological Association.
LEAP Rubric: Measuring Big-Q in Context
VALUE Rubrics
Association of American Colleges & Universities (AACU)
Building a Data Science Pipeline
Data Science for Undergraduates: Opportunities and Options
National Academies of Sciences, Engineering, and Medicine. (2018). National Academies Press.
Includes video:
Preparing Undergraduates for a Data-Driven Workplace
Data Science Specialization, Bowling Green State University
Undergraduate program as a specialization within mathematics major
Data Science Programs, Iowa State University
Interdisciplinary programs including certificate, minor, major, and graduate levels
Data Science B.A., University of California-Berkeley
Interdisciplinary program with gen-ed onramps & more humanities courses than most

“Leaves and Flowers: The Little Q”

Numbers Into Words: Quantitative Writing
Using Quantitative Writing
Bean, J.C., Seattle University, et al. Module hosted by National Numeracy Network
Integration with writing programs: A strategy for quantitative reasoning program development
Grawe, N. D., & Rutz, C. A. (2009). Numeracy, 2(2), 2.
QuIRK Project: Holistic Rubric for Writing
QuIRK: Quantitative Inquiry, Reasoning, and Knowledge
Carleton College. NSF-supported project to assess quantitative literacy using holistic rubrics on portfolios of student writing
According to Sources: Data in Journalism
Math anxiety and elementary teachers: What does research tell us?
Wood, E. F. (1988).  For the learning of mathematics, 8(1), 8-13.
Communication students’ mathematics anxiety: Implications for research methods instruction
Baus, R. D., & Welch, S. A. (2008). Communication Research Reports, 25(4), 289-299.
More Numerate: Numbers & Evidence for News Writers
Hewlett Foundation-funded curriculum module and resources for journalism students
Measuring habits of mind: Toward a prompt-less instrument for assessing quantitative literacy
Boersma, S., & Klyve, D. (2013).  Numeracy, 6(1), 6.
Quantitatively Breaking Cognitive Illusions
Examples of QR Programs
NICHE project list, including the “overlay” or “encounter” model
NICHE: Internet Exercises and Modules for Teaching Quantitative Reasoning Skills
Variety of web-based teaching modules from CUNY’s Numeracy Infusion Course for Higher Education
Numeracy Infusion Course for Higher Education (NICHE), 1: Teaching Faculty How to Improve Students’ Quantitative Reasoning Skills through Cognitive Illusions
Wang, F., & Wilder, E. I. (2015).  Numeracy, 8(2), 6.
The MPG Illusion, Revisited
Salomone, M. Retrieved from . The details on the cognitive illusion from the video, why it “tricks” our relational ways of thinking, and why this is a cultural issue.

“Branching Out”

Now What? Resources to Support Quantitative Literacy
National Numeracy Network (NNN)
U.S. professional organization for faculty, staff, and administrators across disciplines. (Not to be confused with National Numeracy UK, which focuses more on basic skills outside of higher education.)
J. Numeracy
Premier open-access journal in the field of quantitative literacy education. Operated by the National Numeracy Network.
SIGMAA QL: Quantitative Literacy Special Interest Group
Mathematical Association of America-supported working group for identifying appropriate prerequisite mathematics and statistics skills for QL, and implementing innovative curriculum to support it.
QMaSC: A Handbook for Directors of Quantitative and Mathematics Support Centers
Coulombe, Grace; O’Neill, Mary B.; and Schuckers, Michael (Ed.) (2016). 
NECQL 2019: Northeast Consortium for Quantitative Literacy
Annual late spring conference 20-plus-years running
SEQuEL: Southeastern Massachusetts Quantitative Engagement & Literacy
Annual early spring conference hosted by Quantity Across the Curriculum at Bridgewater State University
Now What? The Next Evolution for Your Campus
Raising Academic Standards: A Guide to Learning Improvement
Keimig, R. T. (1983).  ASHE-ERIC Higher Education Research Reports, No. 4. (This article inspired the organizational-development activity that concludes the video.)
Going Public: What Institutional Moments Bring Everyone to the Table?
Parsons, A., Salomone, M., & Smith, B. (2019). In Tunstall, S., Karaali, G., & Piercey, V. (Ed.). Shifting Contexts, Stable Core: Advancing Quantitative Literacy in Higher Education.  MAA Notes No. 88. Mathematical Association of America. (Link above is to preprint)

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