One of the main differences between novice and expert problem solving
in physics is that novices mostly construct problem representations fr
om objects and events in the experimental situation, whereas experts c
onstruct representations closer to theoretical terms and entities. A m
ain difficulty in physics is in interrelating these two levels, i.e. i
n modelling. Relatively little research has been done on this problem,
most work in AI, psychology and physics education having concentrated
on how students use representations in problem solving, rather than o
n the complex process of how they construct them. We present a study t
hat aims to explore how students construct models for energy storage,
transformation and transfers in simple experimental situations involvi
ng electricity and mechanics. The study involved detailed analysis of
problem solving dialogues produced by pairs of students, and AI modell
ing of these processes, We present successively more refined models th
at are capable of generating ideal solutions, solutions for individual
students for a single task, then models for individuals across differ
ent tasks. The students' construction of energy models can be modelled
in terms of the simplest process of modelling - establishing term to
term relations between elements of the object/event 'world' and the th
eory/model world, with underlying linear causal reasoning. Nevertheles
s, our model is unable to take into account more sophisticated modelli
ng processes in students. In conclusion we therefore describe future w
ork on the development of a new model that could take such processes i
nto account.