Problem solving and cognitive skill acquisition
Foundations of cognitive science
KADS: a modelling approach to knowledge engineering
Knowledge Acquisition - Special issue on the KADS approach to knowledge engineering
Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
The Architecture of Cognition
KM QUEST: a collaborative internet-based simulation game
Simulation and Gaming - Special issue: Simulation & gaming
KM QUEST: a collaborative internet-based simulation game
Simulation and Gaming - Special issue: Simulation & gaming
Group mirrors to support interaction regulation in collaborative problem solving
Computers & Education
Simulation and Gaming
Added value of a task model and role of metacognition in learning
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Why Simulation Games Work-In Search of the Active Substance: A Synthesis
Simulation and Gaming
Serious Games, Debriefing, and Simulation/Gaming as a Discipline
Simulation and Gaming
A meta-analytic review of the role of instructional support in game-based learning
Computers & Education
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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.