Teacher workshop at the 14th Informatics Day Berlin-Brandenburg
The promotion of data and AI skills in schools is increasingly being discussed, to the point of adapting computer science curricula. But how can complex topics such as AI or Data Science be taught in a sound way to students at the secondary level I and II?
A current TrainDL training session was held as part of the 14th Informatics Day Berlin-Brandenburg 2022 at the University of Applied Sciences (HTW). On this day, Berlin school counselors, Brandenburg subject counselors for computer science and ITG, and external lecturers offered various workshops on some key topics of computer science teaching and media education. In the individual workshops, the teaching areas were comprehensively elaborated, always with reference to practical lesson design. The program of the day can be found here. All interested computer science teachers from Berlin and Brandenburg could register for the training session.
In the workshop, the participants learned about proven approaches and teaching materials for AI and Data Literacy. Through hands-on exercises, they learned how to first introduce their students to the basic workings of various AI methods through unplugged activities and then have them model real-world data sets in Orange3, a data analysis tool. Then, they discovered machine learning techniques to process the datasets and extract new information. The workshop was wrapped up by insights into other perspectives on the sound teaching of AI and data literacy in computer science classrooms. In the spirit of the "didactic double-decker", the workshop was also suitable for participants who have little prior experience on these topics. As usual, all participants were asked to contribute to the final survey at the end of the workshop.
Overall, 12 computer science in-service teachers participated in the six-hour-long teacher education session, where they not only learned about AI and Data Literacy in German schools, but were introduced to supervised, unsupervised, and reinforcement learning, the data lifecycle and data analysis with Orange3 in a hands-on approach.
