Teacher workshop held at the Vilnius University
On Saturday, December 10, the Vilnius University (VU) hosted an all-day workshop for teachers on "Artificial Intelligence and Data Mining in Computer Science Classes". The main aim of the workshop was to learn about Artificial Intelligence (AI) methods that are subtly entering and shaping school life, students' learning activities and everyday life. The seminar was led by Viktoriya Olari, a researcher from Berlin, assisted by PhD student Vaida Masiulionytė-Dagienė and Prof. Valentina Dagienė from the VU.
Every day, students use AI-based applications and share their data consciously or unconsciously. Increasingly, debates are held about promoting data and AI literacy in schools and including these topics in the curriculum. But how should complex topics such as AI and data science be taught to students in upper secondary school? What topics can be conveyed to lower grades and even to primary students?
The workshop shared methods and teaching materials for AI and data literacy that have been tested in Germany and Austria. Topics such as classic AI, reinforcement learning, and the key differences between supervised and unsupervised learning were discussed. The TrainDL experts presented many practical exercises for the teachers to test, and discussed with them how students could be introduced to the basic principles of different AI techniques.
When the call for the workshop was issued, close to 90 teachers applied to participate. As not all of them could be accommodated, only 35 were contacted and accepted 35.
The teachers who attended the workshop had the opportunity to try out a number of simple methods for teaching AI. Real datasets were modeled using the data analysis software Orange3. They were also introduced to machine learning techniques, discussing how to process datasets and extract new information and insights. The stages of the data lifecycle were explored and practical applications for analyzing datasets were given. To wrap up the workshop, the team initiated a discussion on perspectives for teaching AI and data literacy in computer science classes.
