We developed a system dynamics model for a simple, but
important stock and flows task where the objective was to
control the water level in a tank within an acceptable range of the
goal, over a number of time periods, in the presence of an
unknown environmental inflow and outflow. We also report how
this model accounts for human behavior, using behavioral data
we collected from human subjects in the task. This exercise
helped us understand the strategy and mechanisms our
participants used in the simple stock and flows task and develop
a model on the task. The model provides an integrated
explanation on how the variation in the parameters of the model
affects the performance and learning for the participant’s task.
Finally, we present the model’s validity and predictions derived
by looking into how the human data fits different learning
conditions.