Author: Michael Gregory
The European Physical Society (EPS) is at the forefront of
integrating innovative technologies into education with Discovery Space
teacher training including AIMLOW: Artificial Intelligence and Machine
Learning Online Workshops. These initiatives aim to inspire educators,
equip them with modern pedagogical tools, and provide students with
engaging learning experiences rooted in inquiry and critical thinking.
Discovery Space: A Gateway to Exploratory Learning
Discovery
Space is an ambitious EU-funded project designed to facilitate
students’ inquiry-based learning using an online Enhanced Learning
Environment. Students are guided through differentiated pathways
tailored to students’ progress. Learning scenarios engage learners in a
variety of physics and non-physics topics, from genetics to
astrophysics and everything in between. Discovery Space seeks to
transform traditional education by placing students in active
problem-solving roles while leveraging AI as a guiding tool.
EPS
project officer Michael Gregory is in charge of the Discovery Space
Teacher Training Academy, providing professional development online and
across Europe. In-person workshops have already taken place in Bulgaria
and Spain, with more planned for 2025 there, in France and across
Europe. Keep an eye on the Discovery Space website: https://discoveryspace.eu/ or contact the author to be informed of when there are upcoming workshops near you!
Training
sessions are planned and executed in collaboration with local partners,
and the specific contents adapted to local needs and requests.
Workshops last anywhere between 1.5 hours and a whole day, and either
focus exclusively on Discovery Space or often include more general
sessions on AI in the classroom and low-cost experiments. These
sessions introduce educators to the platform’s features, and
differentiated learning scenarios like “The Magic of Refraction” and
"Zookeepers of the Galaxy."
Discovery Space Learning Scenarios
“The Magic of Refraction”
is a learning scenario that kicks off with live demonstrations inspired
by the popular Science on Stage webinar series “It’s not magic, it’s
science you don’t see”, (https://www.science-on-stage.eu/event/webinar-its-not-magic-its-science-you-dont-see-part-7)
followed by guided experimentation with simulations, collaborative data
collection, and differentiated analysis to explore Snell’s Law and
refraction. The scenario’s emphasis on whole-class data fosters a
collaborative learning environment. Students analyze results with
varying levels of complexity, from reviewing individual data points, to
taking averages, to linearizing data to plot trend lines - the
experience is adapted to the learning needs of each student. This
differentiated approach to analysing whole-class generated data was met
with considerable enthusiasm - when piloted at the National Science and
Mathematics Gimnazija in Sofia, Bulgaria, students asked to stay late on
Friday evening to continue their analysis and discussions.

Michael
presenting Discovery Space scenario “The Magic of Refraction” at
National Science and Mathematics Gimnazija, Sofia, Bulgaria.
(Photo
taken by Nasko Stamenov)
“Zookeepers of the Galaxy”
is a versatile learning scenario that blends astrophysics and
artificial intelligence, offering teachers a novel way to make complex
topics engaging and interactive. First piloted during the final session
of AIMLOW, then further developed for various workshops across Spain -
in Cuenca, Burgos and Espinosa de los Monteros. Its dual focus—covering
key curriculum concepts like the known universe while introducing
machine learning—has been enthusiastically received and highlights the
growing need for resources that bridge 21st-century skills with
traditional science education.
Students begin by categorizing
galaxies based on visual patterns, foreshadowing the creation of a
machine learning model in later phases. The scenario progresses with
adaptable activities to extract a dataset of images from the Zooinverse
dataset (www.zooniverse.org),
then guides learners to use their dataset to train Google Teachable
Machine to classify galaxy images. Through experimentation, they explore
how dataset size and training parameters impact the success of their
models. Reflection phases encourage critical thinking, with learners at
varying levels discovering the balance between accuracy, training time,
and resource use. By combining astrophysics with cutting-edge AI
concepts, “Zookeepers of the Galaxy” empowers students and teachers
alike, sparking curiosity and building essential skills for the future.

Student view in the “Zookeepers of the Galaxy” Learning Scenario
Several
more learning scenarios are already available on the Discovery Space
Enhanced Learning Environment, with even more in development, and the
possibility for teachers to copy, modify and create their own scenarios
adapted for their own classrooms! Topics currently covered range from
evolution, genetics, astrophysics, seasons and electricity. Topics in
the works include taxonomy, microscopy, modern physics and more!
AIMLOW: Artificial Intelligence and Machine Learning Online Workshops
Complementing
the Discovery Space initiative is AIMLOW, a six-week online course that
introduces educators to the world of artificial intelligence and its
practical applications in teaching. Spearheaded by Michael Gregory of
EPS and Kalina Dimitrova from Sofia University, AIMLOW is a hands-on
course that demystifies complex AI concepts and showcases their
relevance to the classroom.
Kalina works on creating AI algorithms
for particle physics experiments and takes interest in explainable AI
methods. She used her expertise to create our own simplified language
model, image classifier and image generator for AIMLOW to explain how
all of these aspects of AI work. To learn more about these, see the
AIMLOW course outline: https://discoveryspace.eu/join-the-aimlow-courses-and-empower-your-teaching-with-ai/ and the recordings of the sessions on the EPS YouTube channel: https://www.youtube.com/@EuroPhysSoc.
Throughout
the course, AIMLOW shared the focus on a theoretical foundation of how
AI works and applications to classroom practice, with sessions focused
on language models, image classification and image generation. The
final two sessions were more focused on classroom applications, with one
session on sharing best practices and teacher resources, and the final
session took teachers through the Discovery Space learning scenario
“Zookeepers of the Galaxy”, which guides students to create an image
classifier using Google Teachable Machine, while learning about galaxy
classification and Hubble’s Tuning Fork.
Fostering a Community of Innovative Educators
A
key outcome of Discovery Space and especially AIMLOW has been the
creation of a vibrant community of educators eager to embrace technology
as a transformative force in education. Workshops and training sessions
often serve as a platform for collaboration, with educators exchanging
ideas and sharing best practices.
Feedback from AIMLOW
participants has been especially positive, with teachers reporting
increased confidence in using AI and a deeper understanding of its
potential. With the fast-pace with which AI is becoming increasingly
present in society, teachers are hungry to learn more - both to help in
their work, and to teach students about this constantly evolving
technology. Following the enthusiasm for “Zookeepers of the Galaxy”,
more Discovery Space learning scenarios are being developed to combine
areas of the science curriculum with basic AI skills.

Michael
presenting Discovery Space at “Un Viaje en el Espacio” teacher training
day at Museo de las Ciencias de Castilla la Mancha, Cuenca, Spain.
(Photo by Jose Luis Olmo Risquez)
Discover the future of education with EPS—where curiosity meets innovation.
Discovery
Space professional development for teachers will continue to take place
online and in-person across Europe. For information on upcoming
workshops, check the Discovery Space website: https://discoveryspace.eu/ or contact the EPS Project Officer Michael Gregory: michael.gregory@eps.org.