Exploring Galaxy Morphology Through AI and Playful Learning

This is a poster presented at the 7th Shaw-IAU Workshop on Astronomy for Education, organised by the IAU Office of Astronomy for Education (OAE, https://astro4edu.org/shaw-iau/7th-shaw-iau-workshop/). Title: Exploring Galaxy Morphology Through AI and Playful Learning Presenter:Maura Sandri (National Institute for Astrophysics (INAF)) 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. About the 7th Shaw-IAU Workshop:The 7th Shaw-IAU Workshop took place 18 - 21 November 2025. The Shaw-IAU workshops focus on astronomy education for primary and secondary school students and teacher training both in universities and in service. This year's Education focus session on Teaching with authentic data and the Science focus is on Galaxies.More details can be found on: https://astro4edu.org/shaw-iau/Keep up to date with future Shaw-IAU Workshops and other opportunities at the IAU Office of Astronomy for Education by joining our mailing list https://astro4edu.org/mailing-list/ Follow the IAU OAE on Bluesky and Facebook under @astro4edu

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-04
DOI
https://doi.org/10.5281/zenodo.17808530
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploring Galaxy Morphology Through AI and Playful Learning

Maura Sandri
Zenodo (CERN European Organization for Nuclear Research)
Galaxies: Formation, Evolution, Phenomena
article

Exploring Galaxy Morphology Through AI and Playful Learning

Maura Sandri
article en

Abstract

This is a poster presented at the 7th Shaw-IAU Workshop on Astronomy for Education, organised by the IAU Office of Astronomy for Education (OAE, https://astro4edu.org/shaw-iau/7th-shaw-iau-workshop/). Title: Exploring Galaxy Morphology Through AI and Playful Learning Presenter:Maura Sandri (National Institute for Astrophysics (INAF)) 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. About the 7th Shaw-IAU Workshop:The 7th Shaw-IAU Workshop took place 18 - 21 November 2025. The Shaw-IAU workshops focus on astronomy education for primary and secondary school students and teacher training both in universities and in service. This year's Education focus session on Teaching with authentic data and the Science focus is on Galaxies.More details can be found on: https://astro4edu.org/shaw-iau/Keep up to date with future Shaw-IAU Workshops and other opportunities at the IAU Office of Astronomy for Education by joining our mailing list https://astro4edu.org/mailing-list/ Follow the IAU OAE on Bluesky and Facebook under @astro4edu

Zenodo (CERN European Organization for Nuclear Research)
National Institute for Astrophysics (IT)
Quality Education
Openalex Percentile: Top 24%
Galaxies: Formation, Evolution, Phenomena
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