# ElViS Lesson

# ElViS Lesson

## Goal

Rheologic models consisting of combinations of linear elements, such as springs and dashpots, are widely used in biophysics to describe the mechanical and, in particular, the viscoelastic behavior of proteins, cells, tissue, and soft matter.

Even simple arrangements with few elements often suffice to recapitulate the experimental data and to provide biophysical insights, making them an ideal subject for educational purposes.

To provide students with an intuitive understanding of the mechanical behavior of spring and dashpot models, we describe a computer simulation tool, elastic viscous system simulator (ElViS), written in the JavaScript programming language for designing viscoelastic models via a graphical user interface and simulating the mechanical response to various inputs.

As an example application, we designed a virtual laboratory course using ElViS that teaches the basic principles of viscoelastic modeling in a gamelike manner.

## Challenge

The project first originated as a playground tool, I build, to investigate spring-dashpot models. I quickly realized
that this had a great educational potential. Unfortunately, shipping out this **python** based tool was not very smooth,
so I created a **javascript** version instead that could be shared using a link.

The initial implementation used an iterative **Runge-Kutta** method to solve the differential equations for the
arbitrary combinations
of springs and dashpots. But as we use the models in the over-damped limit, e.g. a spring "jumping" to its destination,
these infinities quickly lead to instabilities. Therefore, I derived a matrix-based **analytic solution** to solve the
spring-dashpot system for any given point in time.

To actually use the tool in an educational setting, we quickly realized that just having a playground to create an
intuition of spring-dashpot systems is not enough, we needed a more **guided way**. Therefore, I came up with the concept
of short lessons where the student needs to derive an equation by **experimenting** with a given spring-dashpot setup.

The equation is evaluated against some "test-cases" to give the student feedback for their solution. This more
**challenging** way to teach content proved to lead to longer lasting memorisation of the concepts.

## Improved Learning

We then surveyed 50 undergraduate students of a 1-semester course in biophysics who participated in the virtual laboratory course. Students felt that the course was a helpful addition to the lecture and that it improved learning success.