PRELIMINARY

 

Mathematics For Measurement: “Math for practical arts

Mary Parker (mparker@austincc.edu)  and  Hunter Ellinger (hunter@ellinger.org)

Saturday, January 14, 2006    Joint Mathematics Meetings    San Antonio, Texas

Detailed materials at http://www.schoolsupport.net/MFM/

 

Topic modules for the MFM course (spring semester 2006)

   Part 1. (4 weeks) – Review and Basic Tools

Algebra Review - Solving Equations and Evaluating Expressions

Rounding

Using a Calculator

Formulas - Computing and Graphing

Using a Spreadsheet

Angles and Construction of Diagrams

Linear Equations - Algebra

Linear Models - Word Problems

Introduction to Data and Modeling

Propagation of Errors due to Rounding

   Part 2: (3 weeks) – Basic Trigonometry & Use of Approximations

Introduction to Trigonometry

Trigonometric Ratios and Relationships

Computing with Approximate Numbers: Significant Digits

Measurement Sensitivity: Sensitivity of a Formula to Errors in Input Values

Communicating the Results of Computing with Approximate Numbers

   Part 3: (5 weeks) – Measurement Noise & General-Triangle Trigonometry

Curve Fitting: Separating "Signal" from "Noise"

Describing Noise in Measured Values: Standard Deviation

Propagation of Noise I: One Measured Input Value into a Formula.

Sine and Cosine Formulas on Larger Intervals

Solving General Triangles

The "Ambiguous Case"

   Part 4: (4 weeks) – Correction and Combination of Measurements

Removing Bias from a Measurement Process: Calibration

Propagation of Noise, Part II: Averaging Multiple Measurements – A Useful Rule

Propagation of Noise, Part III: Combining Measured Input Values – Empirical Method

Propagation of Noise, Part IV: Combining Measured Input Values Other Rules

   Solving Applications Problems (students select project problems from teacher-supplied list)

 


Motivation for developing the course

The main purpose is to make connections between mathematical thinking and the sophisticated practical thinking of which students are already capable.

 The urgency of this goal stems from the deep alienation from mathematics that the majority of students feel by the time they enter college.

The standard school sequence is simplistic applications of increasingly sophisticated techniques, rather than the increasingly sophisticated application of simple techniques that would be much more effective.

Sophistication is largely drawn from concepts (e.g., measurement-process stability) that students have already developed in practical contexts – MFM is a course designed for adults

Differences between liberal-arts and practical-arts students

Practical arts majors form a significant minority of the enrollment of American community colleges  -- more focused, attention to individual topics is more dependent on the perceived relevance, often active resistance to abstract generalizations.  But substantial practical vocational experience, skill at detecting the oversimplifications.

Goal:  A “math for practical arts” course

MFM is an attempt to recapture “sophisticated application of simple techniques” while also enhancing student competence with important tools (e.g., spreadsheet programs, technical drawing), concepts (e.g., noise propagation, error sensitivity), and techniques (e.g., curve-fitting, practical trigonometry).

Measurement is an area with which almost all adult have substantial experience, is relevant to almost all vocational areas, is connected to math requiring only limited prerequisite skills, is of immediate utility (practical & math), is related to advanced topics, and is well suited for investigation with spreadsheets (a robust tool of lifelong utility).

HIGH-LEVEL COURSE OBJECTIVES

          [1] Enable students to state much of their existing quantitative knowledge about their areas of specialization in terms of numeric values and appropriate formulaic relationships, and give them confidence in the utility and relevance of such statements.

          [2] Enhance the ability of students to communicate on measurement-related matters with engineers or similar mathematically-adept leaders of their communities of vocational practice.

          [3] Provide, for each area of mathematical technique learned, concrete methods that can be used to check, illustrate, and approximate it (such as graphs for functional formulas and scale diagrams for trigonometric problems).

INSTRUCTIONAL TACTICS

Diagrams   Spreadsheets: formulas, data, fitting, statistics   RoundingàApproximationàNoise

Cross-references to slope, graphing, approximation, formulas, calculators, trigonometry

Noise measurement, propagation (both empirical and theoretical); calibration for errors

 

 

 

 

PRELIMINARY