Teaching Linear Algebra: Technology and Resources Leslie Hogben Iowa State University, USA 3rd University Mathematics Courses Forum Chengdu, China November.

Slides:



Advertisements
Similar presentations
Matrices, Digraphs, Markov Chains & Their Use. Introduction to Matrices  A matrix is a rectangular array of numbers  Matrices are used to solve systems.
Advertisements

Panel: Mathematics in CS Iowa Undergraduate Computer Science Consortium October 2005.
Improving Students’ Flexibility in Algebra: The Benefits of Comparison Jon R. Star Michigan State University (Harvard University, as of July 2007)
E-learning in preparation of mathematics teachers and in mathematics teaching Working meeting to project EuroMath Innsbruck, 2004.
College Algebra for Teachers Laurie Burton Western Oregon University MAA PREP Active Learning Workshop July 7, 2003 “Algebra Theme” Day.
Experiences Teaching Math Using Wikipedia Andrew Knyazev Twenty-Third Annual International Conference on Technology in Collegiate Mathematics Denver, Colorado.
By Kim Bonifield Academic Instructor: Math Specialist Tulsa Tech – Lemley Campus Using a Graphing Calculator in an Algebra 2 Classroom.
Celebrating a Century of Advancing Mathematics Designing a Major in the Mathematical Sciences 2015 CUPM Curriculum Guide to Majors in the Mathematical.
ECE Introduction to Control Systems -
CE 311 K - Introduction to Computer Methods Daene C. McKinney
AN INTEGRATED PROJECT-BASED COURSE IN MATHEMATICS AND ENGINEERING WITH ENTREPRENEURSHIP Dr. Shinemin Lin Savannah State University.
Chapter 7 Matrix Mathematics Matrix Operations Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display.
Presentation at AIMS Willy Hereman Department of Applied Mathematics and Statistics Colorado School of Mines Golden, CO USA Tuesday, April 22, 2014,
Table of Contents Solving Linear Systems of Equations - Calculator Methods Consider the following augmented matrix... The rows can be written as... Row.
© 2005 Baylor University Slide 1 Course Introduction Fundamentals of Engineering Analysis Approximate Running Time - 5 minutes Distance Learning / Online.
Math with a Twist! Algebra 1 Geometry Algebra 2.
Academy Algebra II/Trig
Applications  Computer Graphics,  Electronics,  Chemistry,  Biology,  Differential Equations,  Economics,
Little Linear Algebra Contents: Linear vector spaces Matrices Special Matrices Matrix & vector Norms.
Copyright © 2007 Pearson Education, Inc. Slide 7-1.
Graphing Calculators, Technology, and Teaching Mathematics By: Dave Usinski
INTRODUCTION FOR PERL MONGERS MATLAB. Outline 1. Matlab, what is it good for 2. Matlab’s IDE & functions 3. A few words about Maple 4. What needs to be.
AP Calculus AB 8/12/15 Mrs. Langley. Who Should Take AP Calculus AB? Students must successfully complete four years of college preparatory mathematics.
Proposal for Background Requirements Changes For the current MS/PhD programs, background requirements are expressed in the "Background Preparation Worksheet"
CMPS 1371 Introduction to Computing for Engineers MATRICES.
Do Now: Evaluate: 3AB. Algebra II 3.7: Evaluate Determinants HW: p.207 (4-14 even) Test : Friday, 12/6.
1 Ch. 4 Linear Models & Matrix Algebra Matrix algebra can be used: a. To express the system of equations in a compact manner. b. To find out whether solution.
1 MAC 2103 Module 3 Determinants. 2 Rev.F09 Learning Objectives Upon completing this module, you should be able to: 1. Determine the minor, cofactor,
Sage: A Free, Open-Source Mathematics Software Program By NPZR.
Instruction for Mathematical Knowledge for Teachers of Elementary/Middle Grades Melissa Hedges Hank Kepner Gary Luck Kevin McLeod Lee Ann Pruske UW-Milwaukee.
P1 RJM 06/08/02EG1C2 Engineering Maths: Matrix Algebra 1 EG1C2 Engineering Maths : Matrix Algebra Dr Richard Mitchell, Department of Cybernetics AimDescribe.
The Islamic University of Gaza Faculty of Engineering Civil Engineering Department Numerical Analysis ECIV 3306 Introduction Course Outline.
Lecture 1: Matlab Universe
Linear Algebra Diyako Ghaderyan 1 Contents:  Linear Equations in Linear Algebra  Matrix Algebra  Determinants  Vector Spaces  Eigenvalues.
Halomda Educational Software ( Established 1988) Mathematics and Science for Primary, Intermediate and High schools, Colleges and Universities Computer.
Matrices and linear transformations For grade 1, undergraduate students For grade 1, undergraduate students Made by Department of Math.,Anqing Teachers.
Reviving Continuum Mechanics: Computation across the undergraduate curriculum Michael Dennin UC Irvine Special Thanks to Peter Taborek, Bill Heidbrink.
Linear Algebra Course Activity 2: Finding Similarities and Dissimilarities in DNA Sequences of HIV Patients Objective: Classify the types of Distances.
Warm- Up Solve the following systems using elimination or substitution : 1. x + y = 6 -3x + y = x + 4y = 7 x + 2y = 7.
Arab Open University Faculty of Computer Studies M132: Linear Algebra
Linear Algebra Diyako Ghaderyan 1 Contents:  Linear Equations in Linear Algebra  Matrix Algebra  Determinants  Vector Spaces  Eigenvalues.
WHAT IS THE APPROPRIATE MATHEMATICS THAT COLLEGES STUDENTS SHOULD KNOW AMATYC Conference November 20, 2015 Phil Mahler & Rob Farinelli.
What Place Does Philosophy Have in Teaching Mathematics? Preliminary report. Martin E Flashman Department of Mathematics Humboldt State University Arcata,
Course Overview: Linear Algebra
Computer Graphics Mathematical Fundamentals Lecture 10 Taqdees A. Siddiqi
STEM AT WSU MATHEMATICS EDUCATION: TEACHING AND RESEARCH LIBBY KNOTT
Aligning the BVSD Curriculum with the new Colorado Academic Standards.
INTRODUCTION SC116: Algebraic Structures Short Title of the Course: ALG Instructor: Professor Samaresh Chatterji.
1 Embedded Math as an Effective Tool for Smooth Transition from High School into Integrated Engineering: Teacher  and E  Centered Learning Riadh W. Y.
Row Reduction on Excel Michael D. Smith Lycoming College January 8, 2016.
Maths for Signals and Systems Linear Algebra for Engineering Applications Lectures 1-2, Tuesday 13 th October 2014 DR TANIA STATHAKI READER (ASSOCIATE.
Chapter 7: Systems of Equations and Inequalities; Matrices
Solving Systems by Using Matrices
Core Math Tools (CMT) Kyle Linford.
BEng(CompSc) Curriculum Structure & Highlights
Chapter 7 Matrix Mathematics
Introduction Mathcad is a product of mathSoft inc. The Mathcad can help us to calculate, graph, and communicate technical ideas. It lets us work with.
Larger Systems of Linear Equations
Math Linear Algebra Introduction
An Introduction to Maple
Engineering Analysis (EELE 3301)
Eigenvalues and Eigenvectors
Maths for Signals and Systems Linear Algebra in Engineering Class 2, Tuesday 2nd November 2014 DR TANIA STATHAKI READER (ASSOCIATE PROFFESOR) IN SIGNAL.
All we need in Game Programming Course Reference
Linear Algebra Berlin Chen
A square matrix is a matrix with the same number of columns as rows.
RAYAT SHIKSHAN SANSTHA’S S.M.JOSHI COLLEGE HADAPSAR, PUNE
Linear Algebra Berlin Chen
Linear Algebra Berlin Chen
Presentation transcript:

Teaching Linear Algebra: Technology and Resources Leslie Hogben Iowa State University, USA 3rd University Mathematics Courses Forum Chengdu, China November 2007 Leslie Hogben Iowa State University, USA 3rd University Mathematics Courses Forum Chengdu, China November 2007

Contents  Technology  Effect of LACSG  Teaching linear algebra research  Bibliography of linear algebra resources  Technology  Effect of LACSG  Teaching linear algebra research  Bibliography of linear algebra resources

Technology  Basic matrix computation  Visualization  Computation projects  Basic matrix computation  Visualization  Computation projects

Use of technology for basic matrix computations  Students learn and understand method (for example, RREF)  Then use technology to solve:  Larger more interesting problems  Greater variety of problems  Students learn and understand method (for example, RREF)  Then use technology to solve:  Larger more interesting problems  Greater variety of problems

Technology for basic matrix computations  Calculators  M ATLAB, Octave  Mathematica, Maple, SAGE  Calculators  M ATLAB, Octave  Mathematica, Maple, SAGE

Basic matrix computations  matrix arithmetic  Inverse  transpose  RREF  row operations  matrix arithmetic  Inverse  transpose  RREF  row operations  determinant  eigenvalues  eigenvectors  LU  QR

Calculators: TI 89, 92, Voyage 200  Matrix operations  Easy to use  Hard to print  Matrix operations  Easy to use  Hard to print  Arithmetic:  Symbolic  Exact  Decimal

Software: M ATLAB, Octave  Matrix operations  Easy to use  Easy to print  Matrix operations  Easy to use  Easy to print  Arithmetic:  Symbolic ?  Not exact  Decimal

Octave  Free open-source download  octave/octave.html octave/octave.html  Like M ATLAB  Free open-source download  octave/octave.html octave/octave.html  Like M ATLAB

Software: Mathematica, Maple, SAGE  Matrix operations  Hard to use  Easy to print  Matrix operations  Hard to use  Easy to print  Arithmetic:  Symbolic  Exact  Decimal

SAGE  Free download   Can also run on-line  Excellent capabilities  Free download   Can also run on-line  Excellent capabilities

TI Calculators  Entering a matrix:  [1,2,3;4,5,6;1,0,1]  a  Displays nicely:  Entering a matrix:  [1,2,3;4,5,6;1,0,1]  a  Displays nicely:

TI Calculators: Matrix operations

TI Calculators: Menus

SAGE  Make matrix space M  Then enter matrix as A =M([[1,1/2,1], [3,-2,4/3], [4,-3/2,7/3]]); A  Displays nicely  Make matrix space M  Then enter matrix as A =M([[1,1/2,1], [3,-2,4/3], [4,-3/2,7/3]]); A  Displays nicely

file:///Users/hogben/A%20Leslie/A%20research/07CHINA/HogbenUMCF/Linear%20Algebra%20Examples%20(SAGE).webarchive

Mathematica  Entering a matrix:  a={{1,2,3},{4,5,6},{7,8,9}}  Displays nicely only if told to:  Entering a matrix:  a={{1,2,3},{4,5,6},{7,8,9}}  Displays nicely only if told to:

Mathematica : Matrix operations

Mathematica: Menus exist but are harder to use than typing

Visualization Software: Richard Varga’s Gershini 20.dir/gershini.html file:///Users/hogben/A%20Leslie/A%20research/07CHINA/Hogben UCMF/gershini.webarchive

Computation projects A project is:  A multi-part activity  Involves technology  Usually involves an application A project is:  A multi-part activity  Involves technology  Usually involves an application

Sample Projects  Markov chains  Electric circuits (current/voltage only)  Gershgorin circles  Computer graphics  Markov chains  Electric circuits (current/voltage only)  Gershgorin circles  Computer graphics

Effect of LACSG  Lead to ongoing discussion of teaching linear algebra  Some criticism from math educators, but had very little effect  Some recommendations widely adopted  Others (omissions from core) ignored  Lead to ongoing discussion of teaching linear algebra  Some criticism from math educators, but had very little effect  Some recommendations widely adopted  Others (omissions from core) ignored

Why was LACSG influential?  LACSG recommendations made sense to faculty teaching linear algebra  Many universities and authors were already revising their linear algebra courses and texts in a similar manner.  LACSG recommendations made sense to faculty teaching linear algebra  Many universities and authors were already revising their linear algebra courses and texts in a similar manner.

Some LACSG recommendations were already happening  In 1979 I taught linear algebra from a “LACSG-style” text (Anton)  Matrix oriented, emphasized R n  Applications in a supplement  Not much technology  No use of partitioned matrices  In 1979 I taught linear algebra from a “LACSG-style” text (Anton)  Matrix oriented, emphasized R n  Applications in a supplement  Not much technology  No use of partitioned matrices

What LACSG advice adopted?  Matrix oriented  Emphasis on R n  All core topics  Applications  Use of technology  Matrix oriented  Emphasis on R n  All core topics  Applications  Use of technology

What was not adopted?  Defer abstract vector spaces and linear transformations to 2nd course  2nd course at small colleges  Defer abstract vector spaces and linear transformations to 2nd course  2nd course at small colleges

LACSG+ core  Matrix oriented  Emphasizes R n  LACSG core + abstract vector spaces + linear transformations  Widely adopted  Matrix oriented  Emphasizes R n  LACSG core + abstract vector spaces + linear transformations  Widely adopted

LACSG’s partitioned matrices

Partitioned matrices in texts  Partitioned matrix perspective partially evident in Lay, Leon, Strang,  Fully in the graduate text by Zhang  Partitioned matrix perspective partially evident in Lay, Leon, Strang,  Fully in the graduate text by Zhang

Iowa State University  21,000 undergraduates and 5,000 graduate students  140 undergraduate mathematics majors (many will become high school teachers)  50 PhD and MS students in math and applied math  21,000 undergraduates and 5,000 graduate students  140 undergraduate mathematics majors (many will become high school teachers)  50 PhD and MS students in math and applied math

Linear Algebra at ISU  In mid-1980s ISU faculty evaluated the first undergraduate linear algebra course (math 307)  Course was split into two  Both matrix oriented and use technology for basic computation  In mid-1980s ISU faculty evaluated the first undergraduate linear algebra course (math 307)  Course was split into two  Both matrix oriented and use technology for basic computation

Linear Algebra at ISU  Math 307 is a LACSG first course aimed at students in other fields  Math 317 is a first linear algebra course for math majors and emphasizes proof writing but is matrix oriented and uses technology  Math 471 is numerical linear algebra  Math 307 is a LACSG first course aimed at students in other fields  Math 317 is a first linear algebra course for math majors and emphasizes proof writing but is matrix oriented and uses technology  Math 471 is numerical linear algebra

Teaching Linear Algebra Research  US-NSF Research Experiences for Undergraduates (REU) program  ISU combinatorial matrix theory research group  US-NSF Research Experiences for Undergraduates (REU) program  ISU combinatorial matrix theory research group

US-NSF REU  US has a problem persuading undergraduates to enter graduate school  REUs show students what doing math is like and create enthusiasm for math  More REU students go to graduate school  US has a problem persuading undergraduates to enter graduate school  REUs show students what doing math is like and create enthusiasm for math  More REU students go to graduate school

ISU Combinatorial Matrix Theory Research Group  Summer REU for undergraduates  Academic year early research course for first year graduate students  Summer REU for undergraduates  Academic year early research course for first year graduate students

Bibliography of Linear Algebra Resources  Technology bibliography  LACSG bibliography  Undergraduate research bibliography  Technology bibliography  LACSG bibliography  Undergraduate research bibliography

Thank you!