Shaw-IAU Workshops by the OAE

We present an unplugged educational activity to teach how AI works through galaxy classification. Using a card game, students simulate unsupervised and supervised learning by creating their own classification algorithms. Each card shows one or more galaxies, and students in two groups define parameters based on visual features. After classifying their cards, they exchange and classify a mixed set with the same rules, testing algorithm consistency and generalization. The classification aims to approximate the Hubble sequence, enhancing understanding of galaxy morphology. The activity introduces AI concepts in a playful way. Cards will be freely available on the Play INAF platform.

Biography:

Maura Sandri is a technologist and journalist at the National Institute for Astrophysics (INAF). She is actively involved in scientific outreach and innovative education, coordinating INAF’s national activities related to coding, making, and educational robotics, and promoting new teaching methodologies in schools. She is the administrator of the Play INAF platform, the INAF website for innovation in education. Additionally, she serves as editor-in-chief of the magazine Universi and is a member of the editorial team of Media INAF, contributing to science communication and facilitating public engagement with astrophysics and space technology topics.