Julia Chatain

Senior Scientist at the Singapore-ETH Centre, building the Future Embodied Learning Technologies (FELT) programme, and interested in math education, HCI, XR, AI, and embodiment.

Embodied & Causal

Aug 2024

This project is founded by the Jacobs Foundation 2023 Young Scholar grant.

Adaptivity requires that learners appropriately generalize their knowledge across contexts: They must recognize which concepts are stable, rather than situation specific, and how they apply to novel problems. Human learners are highly adept at generalizing causal knowledge, readily extracting and extending the abstract principles that govern the relationships between events. However, learners typically struggle with generalizing abstract mathematical principles beyond the specific situations seen during classroom exercises, severely undermining mathematical literacy. We propose to design digital, embodied learning environments where to-be-learned mathematics govern the system’s causal relationships, thereby leveraging students’ natural abilities as learners to achieve adaptive mathematics knowledge.

Description of causal and non-causal environments. In the non-causal environment, a box is depicted with a sign saying stars only. Similarly, a student is manipulating a set A outside of a set B, next to a rule saying that A should be included in B. In the causal environment, the box now only includes a star-shaped opening. And the student cannot manipulate the set A outside of the set B because the set B has physical borders that prevent movement towards the outside.

More information coming soon...

Team