conceptualizing applied probability through project-based learning timothy i. matis, ph.d....
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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](https://reader030.vdocuments.net/reader030/viewer/2022032611/56649e875503460f94b8a487/html5/thumbnails/1.jpg)
Conceptualizing Applied Probability
through Project-Based Learning
Timothy I. Matis, Ph.D.
Department of Industrial Engineering
Texas Tech University
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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
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Overview of Presentation
• How I got here
• Project-based learning
• Developing “Soft skills”
• Implementation challenges
• Creating teams versus groups
• How we did
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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
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Clips
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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
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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
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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
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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)
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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”
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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
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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
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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
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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)”
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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
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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