i'm a student on the Coursera Bioelectricity course and now in the second week, learning about the way cell membranes create action potentials by selective diffusion of ions. There is a connection with the talking boat project where direct brain input would be fun.
The course has 12,000 enrolled students and the forum is very active with questions about the material and queries about the lecture material and quiz. I'd be among the many who are finding this course quite challenging if it wasnt for a background in maths, physics and chemistry and its fun to dredge up old learning and learn new stuff - whee - I'm learning science again!
Inevitably perhaps, I've been expressing the various models introduced as progams, in my newly adopted Python, with the code in GitHub. I hope this is helpful to some. Certainly writing the code and getting the test scripts working gives me confidence that I've understood at least the computational part of the material. But by publishing the code am I spoiling the chance for others to learn this way?
I also want to create a kind of semantic network to relate the concepts, dimensions, units and relationships. A core set of concepts in bioelectricity are Maxwell's equations and the analytic modelling of specific configurations, such as an electic dipole, and I want to include these equations in the network, but such functions are not easily modelled with triples. As with programming, the benefit may be more for the creator undertaking the task of structuring the knowledge than to the reader who has not been through that cognitive exercise.