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Building Comfort with MATLAB

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Building Comfort with MATLAB

  1. 1. Building Comfort With MATLAB Wendy Thomas Associate Professor of Bioengineering University of Washington 1
  2. 2. My Teaching Experience • Bioen 201 (2008 – 2010) sophomore core: intro to mathematical programming (5 weeks) and circuits (5 weeks) • Bioen 485/585 (2004 – 2016) senior + graduate elective: computational differential equation modeling for bioengineering • Bioen 503 (2010 – 2013) graduate core: systems bioengineering (analytic and computational systems models) 2
  3. 3. Keys to Building Comfort With MATLAB SOFTWARE SUPPORT • hands-on support in front of the computer (lab, class or office hours with laptops or in computer lab) • Peer tutoring/workshops are great! • tutorials (linked online or made just for the course, but should get student from ground zero to the first assignment) • Practice 3
  4. 4. Keys to Building Comfort With MATLAB Each activity requires: • MOTIVATION – Task should be easier to perform in MATLAB than in common alternatives (calculator, EXCEL), even at this stage of experience. – Task should relate to something of value (course content or common experiences) • LIMITED LEARNING OBJECTIVES – Identify a limited set of computing concepts and MATLAB tools that are easy to learn at this stage of experience – Don’t let students spend hours on something unrelated to the objectives. Jump start by providing needed resources such as: • Pseudo-code activity to help design algorithm • sample commented code for related problem • Tutorial-like part 1 followed by independent part 2 4
  5. 5. Comfort With What? Key scientific computing skills: • INTRODUCTORY SKILLS: – Arrays & algebra – Scripts & functions, – Plots – Flow control – Basic input/output • INTERMEDIATE SKILLS: – Use documentation to learn new skills – Debugging – More input and output – common functions: fminsearch, ODEs, statistics, visualization tools, etc, • ADVANCED SKILLS: – Algorithm design – Data structures (e.g. Structures(1).awesome) – GUI design – Advanced visualization tools – Reliability tools (version control, visual checks of analysis, etc.) 5
  6. 6. Set Expectations • Designing algorithms … • Debugging – Test hypotheses to divide and conquer – Much more efficient than experiments to teach logic 6 Move from cook book labs to independent thinking
  7. 7. Lesson 1 Motivation: • MATLAB is easier and more reliable for moderately complex calculations and for plotting functions. Learning Objectives: • command line and scripts • Simple syntax • Arrays • Plot command • Maybe: Input (load) Activity examples: • plot how an algebraic expression changes with one or more parameter values to explore an equation from class • Plot and analyze data from a wet lab • Plot and analyze a provided data set 7
  8. 8. Lesson 2 Motivation: • MATLAB helps with data analysis Learning Objectives: • Input and output data • Flow control • Look up and call functions Activity • Process long data set obtained in a lab to make calculations. • Long time series data are great for this. • My class: calculate viscoelastic properties of material from repeated stress cycle data. 8
  9. 9. Lesson 3 Motivation: • MATLAB provides flexible fitting of models to data Learning Objectives: • Write functions • fminsearch Activity • Test hypotheses to relate experimental data to concepts in class. • My class: drug delivery nanoparticles 9 0 10 20 30 0 10 20 30 40 50 60 70 0 10 20 30 -10 0 10 20 30 40 0 10 20 30 0 20 40 60 80 100 120 0 10 20 30 0 5 10 15 20 25 30 35

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