The potential of learning from erroneous models: comparing three types of model instruction

Learning from computer models is a promising approach to learning. This study investigated how three types of learning from computer models can be applied to teach high‐school students (aged 14–17) about the process of glucose–insulin regulation. Two traditional forms of learning from models (i.e. simulating a predefined model and constructing a model) were compared to learning from an erroneous model. In this innovative form of learning from computer models, students are provided with a model that contained errors to be corrected. As such, students do not have to engage in the difficult task of constructing a model. Rather, they are challenged to work with and correct the model in order for the simulation to generate correct output. As predicted, learning from erroneous models enhances learning of domain‐specific knowledge better than running a simulation or constructing a model. Copyright 2016 System Dynamics Society