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