The course targets anyone who aims at developing or using numerical methods applied to partial differential equations and is seeking a practical introduction at a basic level. The mathematical aspects are complemented by a basic introduction to wave physics, discretization, meshes, parallel programming, computing models.
COMPUTER SIMULATION HOW TO
You will be provided with strategies how to ensure your solutions are correct, for example benchmarking with analytical solutions or convergence tests. The emphasis is on illustrating the fundamental mathematical ingredients of the various numerical methods (e.g., Taylor series, Fourier series, differentiation, function interpolation, numerical integration) and how they compare.
COMPUTER SIMULATION CODE
In a unique setup you can see how the mathematical equations are transformed to a computer code and the results visualized. The mathematical derivation of the computational algorithm is accompanied by python codes embedded in Jupyter notebooks.
COMPUTER SIMULATION SIMULATOR
On the test on a high-fidelity patient simulator, the EG trained with a multimedia computer screen-based simulator performed significantly better than the CG trained with traditional exercises and practice (16.21 versus 11.13 of 23 possible points, respectively p<0.001).Ĭomputer screen-based simulation appears to be effective in preparing learners to use high-fidelity patient simulators, which present simulations that are closer to real-life situations.Interested in learning how to solve partial differential equations with numerical methods and how to turn them into python codes? This course provides you with a basic introduction how to apply methods like the finite-difference method, the pseudospectral method, the linear and spectral element method to the 1D (or 2D) scalar wave equation. Performances with both simulators were scored on a precise 23-point scale. The CG was then also tested on the high-fidelity patient simulator for CA2, after which it was asked to perform CA1 using the computer screen-based simulator. Both groups were given the same amount of practice, exercises and trials. LMC is generally used for educational purposes as it models a simple Von Neumann architecture computer which has all of the basic features of a modern computer. While the EG was learning to perform CA1 procedures in the computer screen-based learning environment, a control group (CG) actively continued to learn cardiac arrest procedures using practical exercises in a traditional class environment. This LMC simulator is based on the Little Man Computer (LMC) model of a computer, created by Dr.
An experiment group (EG) was first asked to learn to perform the appropriate procedures in a cardiac arrest scenario (CA1) in the computer screen-based learning environment and was then tested on a high-fidelity patient simulator in another cardiac arrest simulation (CA2). Just before the end of the traditional resuscitation course, we compared two groups. We tested the benefits of learning cardiac arrest procedures using a multimedia computer screen-based simulator in 28 Year 2 medical students. In this area, as yet, there has been no research on the effectiveness of transfer of learning from a computer screen-based simulator to more realistic situations such as those encountered with high-fidelity patient simulators. New computer screen-based multimedia simulators have fewer constraints than high-fidelity patient simulators. What is the best way to train medical students early so that they acquire basic skills in cardiopulmonary resuscitation as effectively as possible? Studies have shown the benefits of high-fidelity patient simulators, but have also demonstrated their limits.