Tracing Carbon: Can Adaptive Visualization Facilitate Systems Thinking in Science Education?

The catastrophic threat of global warming requires comprehensive societal understanding of earth as a system, a fundamental skill that is challenging for learners.

This 4-year project investigates the influence of adaptive visualization on year 7-9 pupils’ learning of systems thinking in the context of the carbon cycle.

In addition to expanding research on personalised learning environments, the outcomes are applicable for educational practice.

Phase 1 of the project involves conceptualisation and design of an adaptive visualization based on canonical representations of cyclical earth systems.

As pupils interact with the visualization it adopts an artificial intelligence (AI) architecture to adaptively select appropriate tasks based on a systems thinking framework.

In Phase 2, the process and outcome of 10 pupils’ engagement with the visualization will be explored by qualitatively analysing think-aloud tasks, eye-tracking, data logs, and questionnaires.

Results will inform Phase 3 which will investigate the influence of the adaptive feedback in an authentic school context by comparing ca. 100 pupils’ learning from either the adaptive visualization or a version with fixed tasks. Questionnaires and interaction data will be analysed quantitatively using statistical methods.

The project combines science education, educational psychology, interaction design and AI, in close collaboration with a teacher panel. Gender perspectives are considered methodologically and analytically.