Using numeric simulation in an online e-learning environment to teach functional physiological contexts. Issue 127 (April 2016) - Christ, Andreas; Thews, Oliver
Highlights: The system uses complex numerical simulations in an online e-learning environment. Complex calculations are performed on the Web server as a CGI application. The user enters simulation parameters on the browser which are sent to the server. The simulation result is re-transferred as a graphical representation. Two examples were realized: glucose-insulin homeostasis and basic neurophysiology. Abstract: Background and objectives: Mathematical models are suitable to simulate complex biological processes by a set of non-linear differential equations. These simulation models can be used as an e-learning tool in medical education. However, in many cases these mathematical systems have to be treated numerically which is computationally intensive. The aim of the study was to develop a system for numerical simulation to be used in an online e-learning environment. Methods: In the software system the simulation is located on the server as a CGI application. The user (student) selects the boundary conditions for the simulation (e.g., properties of a simulated patient) on the browser. With these parameters the simulation on the server is started and the simulation result is re-transferred to the browser. Results: With this system two examples of e-learning units were realized. The first one uses a multi-compartment model of the glucose-insulin control loop for the simulation of the plasma glucose level after a simulated meal or during diabetes (including treatment by subcutaneous insulin application). The second one simulates the ion transport leading to the resting and action potential in nerves. The student can vary parameters systematically to explore the biological behavior of the system. Conclusions: The described system is able to simulate complex biological processes and offers the possibility to use these models in an online e-learning environment. As far as the underlying principles can be described mathematically, this type of system can be applied to a broad spectrum of biomedical or natural scientific topics.