Paulo Salles and Bredeweg, 2002.
A case study of collaborative modelling:
building qualitative models in ecology.
Proceedings of the International workshop on
Model-based Systems and Qualitative Reasoning for Intelligent
Tutoring Systems, pages 75-84, San Sebastian, Spain,
June 2nd, 2002, B. Bredeweg (editor).
(PDF)
Abstract
Modelling is seen as a learning activity in itself and
qualitative modelling environments start to play
a role in this respect. However, building (qualitative)
models is not an easy task. It is therefore necessary
to develop support for teachers and students. This paper
describes an experience in which Artificial
Intelligence (AI) undergraduate students from the
University of Amsterdam and graduate ecology
students from the University of Brasilia were
engaged in a collaborative model building activity. The
objective was to build qualitative models about the
carbon cycle and the greenhouse effect in GARP.
A questionnaire was used to obtain the students
opinion about different aspects of the modelling
effort. Almost all the students (94%) reported an
increase in their understanding of the ecological
problems after the modelling activity, (an observation
that supports the idea of modelling as a learning
activity in itself). In certain aspects, being an
ecologist (and therefore possessing relevant domain
knowledge) made some parts of the model building activity
easier. For example, global identification of
the processes involved. Contrary, the AI students
found it easier to construct typical AI representations,
such as subtype hierarchies. The most difficult task
for both groups was to build a library of model
fragments. Identifying quantities and their quantity
spaces were also mentioned as difficult.
In order to improve the performance of the qualitative
modelling environments the QR community
has to put effort in developing authoring tools
with explanatory facilities. The study reported here
provides some insights on how to scaffold such model
building tools.