Web-based applications

(how) to motivate students to become enthusiastic data scientists and modelers?

Thomas Petzoldt and Johannes Feldbauer

2024-09-17

Have you ever experienced something like this?

Hooray – We have got a new project!

Funding Decision
Digital learning and teaching 2023

Dear …

Thank you for your application to the Digital Learning and Teaching Fund for the 2023/2024 funding period.

We are pleased to announce the funding of the project “SimBiose - Simulation of biological processes - digitally supported teaching and learning in specialist and teacher training programmes”. …

For the realisation of the project: ….. euros are available to you.

Please note that …

Qualified People?

Search for qualified students who are interested in ecology and modeling

Current Situation

\(\Rightarrow\) Modeling and data science became an important part of limnology.

Demand in Research and Engineering

people who can use computers
people who can understand models
people who are able to develop models

School Experience

mathematics is complicated
programming is something for nerds
differential calculus is rocket science

Domain knowledge

limnology, of course 😉

Approach it from two sides

Ecologists \(\leftarrow\) modeling

Data scientists \(\leftarrow\) ecology

Introduce ecology and modeling early
Reduce barriers: success experience – respect but no fear
Use a playful approach and motivate for more:
- Link back to the scientific fundamentals of ecology / modeling.
- Motivate to find the right depth level, from “interested” to “professional”

Let’s speak about 1+2 first.

Example 1: Lake Profile Plotter

developed for COVID online teaching
Multiparameter probe data
- Complex interactions between temperature, light, algae, oxygen, pH, conductivity
- Excel data structures, plotting, trend line, colors, … distract from content
- Limited time

https://weblab.hydro.tu-dresden.de/app/lakeplot/

\(\Rightarrow\) Has also passed its acid test in field courses.

Example 2: Climate Data Explorer

Visualisation of climate data and trends
Direct access to data from the German Weather Service
Used in teaching and for public outreach

https://weblab.hydro.tu-dresden.de/app/dwd-trends/

Example 3: Reservoir Management with GOTM

1D hydrophysical model provided as web service
Predefined scenarios
Quick performance
Results can be downloaded

https://weblab.hydro.tu-dresden.de/app/talsperre/

Cinema is not enough!
Focus on Processes

Which kind of description is the simplest?

Differential equation

\[ \begin{align} \frac{dN}{dt} &= r_{max} \cdot N\cdot \left(1 - \frac{N}{K}\right) \end{align} \]

intuitive understanding of mechanisms, needs numerical solver

Closed-form integral solution

\[ N_t = \frac{K N_0 e^{r t}}{K + N_0 (e^{r t}-1)} \]

can be plotted with Excel, mechanisms difficult to see

Jay W. Forrester: System Dynamics

“… students can deal with high-order dynamic systems without ever discovering that their elders consider such to be very difficult.” (Forrester 2009)

System Dynamics

\[ \begin{align} \frac{dN}{dt} &= \mbox{birth} - \mbox{death}\\ &= b \cdot N - d \cdot N\\ \frac{dN}{dt} &= r \cdot N\\ \end{align} \]

Implementation

Exponential growth

\[ \frac{dN}{dt} = r \cdot N \]

Logistic growth

\[ \frac{dN}{dt} = r \cdot N \cdot \left(1-\frac{N}{K}\right)\\ \]

Exercise

Run the code.
Modify it to simulate logistic growth.
Play with the parameter values.

Outlook: Growth Model Dashboard

https://weblab.hydro.tu-dresden.de/app/wachstumsmodelle/

Conclusions

Possibilities

Evolving technologies for data analysis and modeling
Server-based or on local computer
Numerical libraries, visualization, reporting … freely available

Challenges

Technical approach is not enough.
Graphics design and formulation of texts.
Avoid “cinema mode” and encourage further studies to dig deeper.

Thank you!

Funded by the Digital Learning and Teaching Fund of TU Dresden (\(\rightarrow\) Fonds DLL)