Learning Computational Methods for Partial Differential Equations from the Web

A course has been developed to learn computational methods from the web1 and has been tested with postgraduate students from remote universities. Short video conferences or video recordings provide an overview and introduce more detailed studies with numerical experiments in Java-powered course notes. This enables every participant to work at his own pace and to develop his intuition for finite differences, finite elements, Fourier, Monte-Carlo and Lagrangian methods. Assignments are carried out in a regular web browser and are compiled into web pages where the students explain with their own words, equations and programs how to derive, implement and run computational schemes. Our experience shows that the technology is rapidly acquired from templates, using practical examples for the advection, diffusion, Black-Scholes, Burger, Korteweg-DeVries and Schrödinger equations.

Authors and Affiliations

1. Alfvén Laboratory, Royal Institute of Technology, SE-100 44, Stockholm, Sweden

   André Jaun, Johan Hedin & Thomas Johnson

2. Center for Educational Development, Chalmers, SE 412 96, Göteborg, Sweden

   Michael Christie

3. Unit for Pedagogy and Didactics, University, SE 412 96, Göteborg, Sweden

   Lars-Erik Jonsson

4. Electromagnetics, Chalmers Institute of Technology, SE 412 96, Göteborg, Sweden

   Mikael Persson

5. CRPP, Ecole Polytechnique Fédérale, CH-1015, Lausanne, Switzerland

   Laurent Villard

Editors and Affiliations

1. School of Computer Science, Cybernetics and Electronic Engineering, University of Reading, Whiteknights, P.O. Box 225, Reading, RG6 6AY, UK

   Vassil N. Alexandrov

2. Innovative Computing Lab, Computer Science Department, University of Tennessee, 1122 Volunteer Blvd, Knoxville, TN, 37996-3450, USA

   Jack J. Dongarra

3. Computer Science Department, California State University, Chico, CA, 95929-0410, USA

   Benjoe A. Juliano  & René S. Renner  & 

4. School of Computer Science, The Queen’s University of Belfast, Belfast, BT7 1NN, Northern Ireland, UK

   C. J. Kenneth Tan

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