Students' interaction data from learning environments has
an inherent temporal dimension, with successive events
being related through the ``next event'' relationship.
Exploratory learning environments (ELEs), in particular, can
generate very large volumes of such data,
making their interpretation a challenging task.
Using two mathematical microworlds as exemplars,
we illustrate how modelling students' event-based interaction data as a graph can open up new querying and analysis opportunities.
We demonstrate the possibilities that graph-based modelling
can provide for querying and analysing the data,
enabling investigation of student-system interactions
and leading to the improvement of future versions of
the ELEs under investigation
