With these definitions in mind, we define model-based learning as the construction
of mental models of phenomena.We believe that the user in response to a
particular task constructs mental models, then evaluates and revises them as
needed. While it is impossible to know precisely the nature and content of mental
models, even our own, we can as researchers draw inferences about the nature of
one’s mental models based on the types of reasoning learners are able to do with
the knowledge they possess. Model formation, we assume, is the construction of a
model of some phenomenon by integrating pieces of information about the structure,
function/behaviour, and causal mechanism of the phenomenon, mapping
from analogous systems or through induction. Use and evaluation of the model
may lead the learner to reject their model and begin again or may trigger revision
or elaboration. Model revision involves modifying parts of an existing model so
that it better describes or explains a given situation. Model elaboration might
involve combining or making additions to existing models by processes such as
embedding a model in a larger system or adding more parts to the model (Clement
1989, Stewart and Hafner 1991).