Presented By: Christiane Bauer
We talk a lot about machine learning and AI and how this works. I'm interested in the way humans learn, how every individual can be understood, and how every person can find ways to explore and reflect on her own best access to learning.
One aspect of Logo and Snap_!_ today is to learn about learning, a thought and idea that resonates a lot with me and has inspired experimenting more with Snap_!_ as a tool to find your own learning triggers.
For a couple of years, I have observed how young thinkers begin Computer Science with Snap_!. Most of them get inspiration through different learning modules relating to Art, Biology, Media, Math, or Words or pure learning around the big ideas of Computer or Data Science.
Almost all learners like a playful approach and interaction with peers. Some learners just get started by logging into Snap!_ and experimenting on their own without any pre-instruction. Can we use Snap_!_ as a tool to give ourselves a hint about our own preferred way to learn?
What if the reflection about the piece of code you created, the topic you used, the issues you had, or the things you found specifically easy or appealing tells you a lot about your own learning preference? What if it gives you access to your subconscious preferences and learning sweet spots?
This talk will share first experiences around learning with Snap_!_ including first steps in 100% virtual setups. We will then open up for a lively discussion to exchange experiences.