Information
Participants were able to explore the "Principles of the Digital World" in a school workshop organized by the "Institute for the Digital Transformation of Application and Living Domains" (IDiAL) on 15 and 16 April 2025.
The workshop was led by Prof. Dr. Sabine Sachweh with the support of Marcel Mitas, Philipp Heisig and Arkadi Braun.
First day
The pupils alternated between learning interesting facts in a presentation and doing an exercise on these topics:
"Data":
- Things to know: What are data and information? How can data be collected (via sensors, observation, etc.), processed (e.g. sorting, removing incorrect data, putting it into a uniform format such as a table, etc.) and analyzed (e.g. classifying it in a diagram and recognizing correlations, as is the case with a weather forecast or video recommendations in social media)?
- Exercise: The students are accompanied to a nearby parking lot and collect data about the cars, e.g. color, drive type, car make, model or body type. They then answer questions about the collected data, such as the most common color, conclusions about the drivers' earnings, conclusions about where they live, work or spend their free time.
"Networking / Internet of Things":
- Things to know: What is IoT? What does networking between different devices mean? Types of data transmission (wired, wireless), overview of different communication protocols (Bluetooth, 4G/5G, LoRaWAN, etc.)
- Exercise: Slips of paper with different symbols of devices and objects are laid out, e.g. alarm clock, toaster, airplane, smartphone, robot. Pupils develop their own scenarios/stories around these pieces of paper about which devices are connected and for what purpose. Example developed: A dog is equipped with a GPS device and a beeper. Both devices are connected to the smartphone via WIFI and the mobile network. If the dog moves too far away from the owner's smartphone, the smartphone asks for the GPS position from the GPS device and displays the position. The smartphone also sends a signal to the beeper, making it easier to find the dog.
"Automation and AI":
- Things to know: What is automation? What are embedded systems that allow devices to do things automatically and become "smart"? What is artificial intelligence, machine learning and deep learning? How does an AI learn (supervised, unsupervised)?
- Exercise: Students sort balls of different sizes and colors into groups of their own devising. Then, with the help of "Google Teachable Machine", they create their own artificial intelligence that can distinguish balls based on their colors. To do this, finished images of red and yellow balls were sent to "Google Teachable Machine" and the artificial intelligence was trained on these images at the touch of a button. As a result, the AI was able to distinguish red balls from yellow balls. As an additional task, the students independently trained the same AI with images of yellow wires so that it could distinguish yellow wires from yellow and red balls.
After the stations and a lunch break, the students played through an escape room.
Second day
To kick things off, the pupils learned interesting facts about algorithms, i.e. step-by-step instructions. In a related exercise, they navigated virtual robots through Minecraft labyrinths. This was followed by an introduction to the "senseBox", an environmental measurement system with plug-in sensors and displays that is controlled with the help of a programming language; as an exercise, "senseBoxes" provided were converted into an environmental measurement station.
The final task was to build and program an automated greenhouse. This involved taking a large plastic box and growing plants such as tomatoes or radishes in it. Sensors and devices from the "senseBox" such as a humidity sensor, soil moisture sensor, brightness sensor and a controllable LED were attached to the inside of the box. The "senseBox" was connected to a small water pump, which was located in a water bucket. It was connected to the greenhouse via a water hose. The sensors were connected by cable to the "senseBox" outside the box. The sensor values were recorded using a block-based programming language and shown on a display. The "senseBox" was also supposed to do the following:
- If the soil moisture is too low, the water pump is switched on for a short time and the greenhouse is watered.
- If the brightness is too low, the LED switches on.
- If the brightness is too high, the LED switches off.