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Conceptualizing Applied Probability through Project- Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

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Page 1: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

Conceptualizing Applied Probability

through Project-Based Learning

Timothy I. Matis, Ph.D.

Department of Industrial Engineering

Texas Tech University

Page 2: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 2

Lubbock, Texas -- Top 5

• Flat as a Pancake

• Lots of Cotton

• Lots of Oil

• Lots of Wind

• Friendly Folks

Page 3: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 3

Overview of Presentation

• How I got here

• Project-based learning

• Developing “Soft skills”

• Implementation challenges

• Creating teams versus groups

• How we did

Page 4: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 4

Undergraduate Modules

• Students presented with a non-trivial “real-world” problem whose solution involves the application of stochastic methods

• Problem is solved in teams through an iterative model building, testing, parameterization, and analyzing process

• Each modules spans 3-4 weeks time

• A total of 6 modules were created

Page 5: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 5

Clips

Page 6: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 6

Pedagogy• Based on the “How People Learn” research

compilation of the National Research Council

• Creation of a knowledge-centered learning environment for the conceptualization and synthesis of stochastic modeling concepts

Page 7: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 7

Soft Skills

• Relevant Literature– R. Felder, “A whole new mind for a flat world”

Chem. Eng. Ed., 40(2), 96-97, 2006– J. Lang, et al., "Industry expectations of new

engineers: A survey to assist curriculum designers," J. of Eng. Ed., 88, 43-51, 1999

• Necessary “Soft Skills” for Engineers– Creative researchers– Design functional and attractive products

Page 8: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 8

Soft Skills Cont’d

• Necessary skills cont’d– Holistic, multidisciplinary thinkers– Strong interpersonal skills– Language skills and cultural awareness– Self-directed learners

• The team-based implementation of the modules helps develop these skills

Page 9: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 9

Implementation Findings

• A few revolts– 3 weeks per module is very short– Hands-off approach can be dangerous

• A properly functioning student team (not group) is critical !!

• A properly functioning student team (not group) is critical !! (repetition for emphasis)

Page 10: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 10

How to Organize Teams?

• Many possibilities (student selection, random assignment, instructor social engineering, etc.)

• Poor selection and management will only create groups, not teams.

• Review of literature (2004 ASEE proc.)– R. Bannerot “Characteristics of Good Team Players”– S. Sauer and P.E. Arce, “Team Member Selection”

Page 11: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 11

Functional-Based Organization

Three individuals and four roles– Team Leader – calls meetings, communicates

with instructor, sets timeline– Team Engineer – performs all calculations

and computer programs, manages webpage– Team Innovator – brainstorms and proves

possible solution approaches– Team Doubter = Team Leader + Team

Engineer – challenges ideas presented by the Team Innovator

Page 12: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 12

Hybrid Selection

1. Instructor explains functions to the class

2. Students rate their ability to perform each function on a scale of 1 to 10 (confidentially)

3. Instructor organizes groups using ratings as a guide

Page 13: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 13

A Few Tips

• Explain time requirement (approx 2-3 hours per day) to class on first day– Possibly give a pre-test to the class– Have a stack of drop slips signed and ready

• Don’t make a fourth individual the Team Doubter– Being the critic is easy– Negativity breeds resentment from team

Page 14: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 14

How we did 2nd time

• Quantitative assessments available, but not displayed here

• Verbatim sampling of longitudinal qualitative responses (6 months out)– “It was a lot of work at the time, but I don’t

think I would have remembered the stuff without the projects”

– “I am surprised at how much I know about modeling compared to my coworkers at (prominent defense company)”

Page 15: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 15

Concluding Comments(with past sessions in mind)

• The instructor is both a teacher (lecture) and research facilitator (projects) – Session 3K

• This curricular approach is targeted to advanced undergraduate – Session 3K

• Manipulating large sets of data is critical and non-trivial in Op. Res. and Probability Modeling – Session 2E

Page 16: Conceptualizing Applied Probability through Project-Based Learning Timothy I. Matis, Ph.D. Department of Industrial Engineering Texas Tech University

July 6, 2006 Slides Prepared for ICOTS 7 16

Concluding Comments Cont’d(with past sessions in mind)

• The modules help unpack, organize, and synthesize what students already know – Session 6B

• My opinion that the use of modules to create a knowledge-centered environment is only practical in advanced courses; yet the teaming strategies presented here may be and should be implemented in lower level courses