The role of prescriptive models in learning

Abstract

The main research question in this article concerns the added value of a prescriptive model in a simulation/gaming environment: KM Quest. KM Quest is meant to support students in the acquisition of both declarative and procedural knowledge in the domain of Knowledge Management (KM). The prescriptive model (KM model) embedded in the KM Quest environment describes the different steps that need to be taken while solving Knowledge Management problems. The main assumption is that because of the KM model, students more easily acquire knowledge about KM and that they need to use their metacognitive skills to a lesser extent since the KM model partly takes over regulation of learning in a new domain. These hypotheses are investigated in an experiment with two conditions: a no-model versus a model condition. The results of 46 students (23 in each condition) show that students in both conditions acquire declarative and procedural knowledge. Students in the model condition acquire more procedural knowledge and more KM model-specific procedural knowledge than students in the no-model condition. The model condition students also outperform the no-model condition students on a transfer test. However, students in the model condition spent much more time in the learning environment than the students in the no-model condition. Some exploratory evidence is presented that suggests that the inclusion of a prescriptive model changes the nature of the regulation: it appears that students in the model condition spend much time on regulating the use of the KM model, while the regulation activities of the no-model students concerns the domain of KM itself.