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.
