Writing to Learn with Quantitative Information “Once students understand HOW things are said, they can better understand WHAT is being said, and only then do they have a chance to know WHY it is said” –Robert Jamison “Learning the Language of Mathematics”

Short In-Class Exercise  Choose a “meaty” graph from your field that is either ambiguous or supports several potential conclusions about the data.  Provide the chart or graph and, if applicable, the data set  Pose open “writing to learn” questions for free write (in class) or homework. Examples might include:  What is this graph arguing?  What conclusions can you draw from this data?  What conclusions are suggested but not fully supported by this graph/chart alone?  (If applicable) Write out 1-2 other conclusions that might be supported by the data set.

Example Chart

Example Graph

Numeracy (or Quantitative Literacy) Teaching Quantitative Reasoning Learning (Skill Development) Most K–12 math classes Arithmetic / algebra / geometry Context-light (or –free) Acquisition (Application) Social/physical science classes Argument from evidence, sources Context-intensive Writing-intensive Literacy A Literacy Analogy: Quantitative Reasoning Teaching Critical Reasoning Learning (Skill Development) Early-grades English classes Structure / spelling / grammar Context-light (or –free) Acquisition (Application) Humanities/Social science classes Argument from evidence, sources Context-intensive Writing-intensive

Quantitative Reasoning Is… Sophisticated reasoning using elementary mathematics The core set of “math” skills need not extend past the college-freshman level. Understood and argued in a variety of written, graphical, and appropriate mathematical formats Ultimately, reasoning – and hence writing – takes center stage, followed by visual aids, followed by data and charts, and finally algebra. (This is a bit like an “upside-down math class.”) A “ habit of mind ” and a “conspiracy” across disciplines QR is a lens through which topical questions may be asked and answered across the curriculum, through whatever context is appropriate to the discipline.

Quantitative Literacy (“Case”) Quantitative literacy stresses the use of mathematical and logical tools to solve common problems. QL is inseparable from its context (17). Quantitative literacy can be understood and expressed in a variety of written, graphical, and mathematical formats. The Quantitative Literacy Design Team (part of the National Council on Education and the Disciplines) breaks quantitative literacy into the following components:  Elements(Confidence, logic, sensibility, interpretation)  Expressions(In public, personal, and professional spheres)  Skills(Basic algebra, statistics, modeling, etc.)

What Is It? Elements of QR (“Case” 8)  Confidence with Mathematics  Cultural Valuation / Appreciation  Interpretation of Data  Logical Thinking  Informed Decision-Making  Mathematics in Context  Number Sense / Estimation  Practical (Applied) Skills  Prerequisite Knowledge

Where Is It? Expressions of QR (“Case” 10)  Public  Citizenship / Government  Cultural Roles, History, Scientific Method  Personal  Finances (Debts, Accounts, Investments, Mortgages…)  Personal Health (Treatments, Insurances, Studies…)  Professional  Small Business Management / Data Analysis  Statistical Quality Control  Scheduling, Budgeting, Inventory Planning, …

What’s It Made Of? Skills of QR (“Case” 16)  Arithmetic, esp. Proportions and Percentages  Basic Algebra, through Exponents/Logs  Data Interpretation / Representation  Basic Statistics / Sampling and Chance  Logical Reasoning  Computer Skills (Excel, SPSS, Maple, etc.)