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  1. Spanish
  1. 3-030-S-SecondOrderIntro

    Modeling Scenarios 22 Apr 2016 Contributor(s): Brian Winkel

    SPANISH LANGUAGE VERSION  We have placed in Supporting Docs both Student and Teacher Version (LaTeX and PDF Versions) with a Spanish LaTeX Class file, SIMIODE-SPANISH. Names will be x-y-S-Title-StudentVersion-Spanish and x-y--T-Title-TeacherVersion-Spanish.

    https://www.simiode.org/resources/1724

  2. 1-030-S-IntraocularGasBubbles

    Modeling Scenarios 2 Jun 2015 Contributor(s): Brian Winkel

    We offer a mathematical modeling experience using differential equations to model the volume of an intraocular gas bubble used by ophthalmologists to aid the healing of a surgically repaired region of the retina. We ask students to compare the traditional ``empirical'' model used by the ophthalmological profession with  more

    https://www.simiode.org/resources/346

  3. 3-061-S-ChemEng

    Modeling Scenarios 28 Nov 2019 Contributor(s): Eric Stachura

    Chemical and biomedical applications of differential equations SPANISH LANGUAGE VERSION  We have placed in Supporting Docs a Spanish version of this Student Modeling Scenario.

    https://www.simiode.org/resources/6481

  4. 1-007-S-AntTunnelBuilding

    Modeling Scenarios 31 May 2015 Contributor(s): Brian Winkel

    We pose the prospect of modeling just how long an ant takes to build a tunnel. With a bit of guidance students produce a model for the time it takes to build a tunnel of length x into the side of a damp sandy hill. SPANISH LANGUAGE VERSION  We have placed in Supporting Docs both Student and Teacher Version (LaTeX and PDF Versions) with a

    https://www.simiode.org/resources/289

  5. 1-007-T-AntTunnelBuilding

    Modeling Scenarios 31 May 2015 Contributor(s): Brian Winkel

    We pose the prospect of modeling just how long an ant takes to build a tunnel. With a bit of guidance students produce a model for the time it takes to build a tunnel of length x into the side of a damp sandy hill. SPANISH LANGUAGE VERSION  We have placed in Supporting Docs both Student and Teacher Version (LaTeX and PDF Versions) with a

    https://www.simiode.org/resources/280

  6. 1-005-S-OilSlick

    Modeling Scenarios 31 May 2015 Contributor(s): Brian Winkel

    We describe a modeling activity for students in  which modeling with difference and differential equations is appropriate. We have used this model in our coursework for years and have found that it enlightens students as to the model building process and parameter estimation for a  linear, first-order, non-homogeneous, ordinary

    https://www.simiode.org/resources/196

  7. 1-031-T-CoolIt

    Modeling Scenarios 2 Jun 2015 Contributor(s): Brian Winkel

    We offer data on the temperature of water in a beaker which resides in a room of constant temperature and also in an environment of nonconstant temperature. Students are encouraged to consider both empirical and analytic modeling approaches. We offer additional data sets in Excel spreadsheets for further work. SPANISH LANGUAGE

    https://www.simiode.org/resources/361

  8. 1-005-T-OilSlick

    Modeling Scenarios 31 May 2015 Contributor(s): Brian Winkel

    We describe a modeling activity for students in  which modeling with difference and differential equations is appropriate. We have used this model in our coursework for years and have found that it enlightens students as to the model building process and parameter estimation for a  linear, first-order, non-homogeneous, ordinary

    https://www.simiode.org/resources/184

  9. 5-001-T-LSDAndProblemSolving

    Modeling Scenarios 2 Jun 2015 Contributor(s): Brian Winkel

    We describe the use of  a two compartment model of a linear system of first order linear differential equations to model  lysergic acid diethylamide (LSD) in the body. We provide the data from the literature. We offer students the opportunity to build a two compartment model to fully analyze the administration and absorption of LSD in 8

    https://www.simiode.org/resources/395

  10. 1-030-T-IntraocularGasBubbles

    Modeling Scenarios 2 Jun 2015 Contributor(s): Brian Winkel

    We offer a mathematical modeling experience using differential equations to model the volume of an intraocular gas bubble used by ophthalmologists to aid the healing of a surgically repaired region of the retina. We ask students to compare the traditional ``empirical'' model used by the ophthalmological profession with  more

    https://www.simiode.org/resources/334

  11. 5-001-S-LSDAndProblemSolving

    Modeling Scenarios 2 Jun 2015 Contributor(s): Brian Winkel

    We ask students to build differential equations to model lysergic acid diethylamide (LSD) in the body. We provide the data from the literature. We offer students the opportunity to build a model to fully analyze the administration and absorption of LSD in 8 student volunteers. We also compare the model predictions with data from the

    https://www.simiode.org/resources/411

  12. 3-061-T-ChemEng

    Modeling Scenarios 28 Nov 2019 Contributor(s): Eric Stachura

    Students will be lead through a classical chemical engineering problem: to calculate the concentration profile of cyclohexane within a catalyst pellet by solving a second order linear differential equation. Then students will analyze the concentration as the radius of the catalyst shrinks to zero. Finally, they will explore a Mathematica Module

    https://www.simiode.org/resources/6480

  13. 3-030-T-SecondOrderIntro

    Modeling Scenarios 22 Apr 2016 Contributor(s): Brian Winkel

    Abstract:  We outline the solution strategies involved in solving second order, linear, constant coefficient ordinary differential equations, both homogeneous and nonhomogeneous and offer many application and modeling activities. COMMENTS (to teacher): We have assembled all the techniques, theory, and machinery for solving second order,

    https://www.simiode.org/resources/1725

  14. 1-031-S-CoolIt

    Modeling Scenarios 2 Jun 2015 Contributor(s): Brian Winkel

    We offer data on the temperature of water in a beaker which resides in a room of constant temperature and also in an environment of nonconstant temperature. Students are encouraged to consider both empirical and analytic modeling approaches. We offer additional data sets in Excel spreadsheets for further work. SPANISH LANGUAGE

    https://www.simiode.org/resources/372

  15. 1-015-S-Torricelli

    Modeling Scenarios 3 Jun 2015 Contributor(s): Brian Winkel

    We help students develop a model (Torricelli's Law) for the height of a falling column of water with a small hole in the container at the bottom of the column of water. We offer several sources of simulations on YouTube and at this site from which we collect data and ask students to verify their model through parameter estimation. SPANISH

    https://www.simiode.org/resources/488

  16. 1-001-S-MandMDeathAndImmigration

    Modeling Scenarios 30 May 2015 Contributor(s): Brian Winkel

    We describe a classroom activity in which students use M&M candies to simulate death and immigration. Students build a mathematical model, usually a linear first order, difference or differential equation, collect data, estimate parameters, and compare their model prediction with their actual data. We describe a number of different faculty

    https://www.simiode.org/resources/132

  17. 1-015-T-Torricelli

    Modeling Scenarios 3 Jun 2015 Contributor(s): Brian Winkel

    We help students develop a model (Torricelli's Law) for the height of a falling column of water with a small hole in the container at the bottom of the column of water. We offer several sources of simulations on YouTube and at this site from which we collect data and ask students to verify their model through parameter estimation. SPANISH

    https://www.simiode.org/resources/463

  18. 1-001-T-MandMDeathAndImmigration

    Modeling Scenarios 30 May 2015 Contributor(s): Brian Winkel, Norma Louise Miller, Gabriel Nagy

    We describe a classroom activity in which students use M&M candies to simulate death and immigration. Students build a mathematical model, usually a linear first order, difference or differential equation, collect data, estimate parameters, and compare their model prediction with their actual data. We describe a number of different faculty

    https://www.simiode.org/resources/116

  19. 1-005A-T-OilSlick

    Modeling Scenarios 31 May 2015

    https://www.simiode.org/resources/200

  20. 1-005A-S-OilSlick

    Modeling Scenarios 31 May 2015

    https://www.simiode.org/resources/198

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