Computer simulation

Draft

Definition

According to the What do we know about computer simulations, common characteristics of educational computer simulations are:

• Model Based: Simulations are based on a model. This means that the calculations and rules operating the simulation are programmed. These calculations and rules are collectively called "the model", and it determines the behavior of the simulation depending on user actions.
• Interactive: Learners work interactively with a simulation's model to input information and then observe how the variables in the simulation change, based on this output.
• Interface driven: The value changes to the influenced variables and the observed value changes in the output are found in the simulation's interface.
• Scaffolded: Simulations designed for education should have supports or scaffolds to assist students in making the learning experience effective. Step by step directions, or small assignments which break the task down to help students, while they work with a simulation, are examples.

See also simulation (list of other types)

Software

• SimQuest (Note there is also a commercial SimQuest system for BioMedical Simulation)

References

Tutorials

Kaleidoscope Network of Excellence for Technology Enhanced Learning (2007). What do we know about computer simulations ?, PDF (based on a Dutch brochure written by Ton de Jong and Wouter van Joolingen).

Academic

• De Jong, T. (2006a). Computer simulations: Technological advances in inquiry learning. Science, 312, 532-533.

• De Jong, T. (2006b). Scaffolds for computer simulation based scientific discovery learning. In J. Elen & R. E. Clark (Eds.), Dealing with complexity in learning environments (pp. 107-128). London: Elsevier Science Publishers.

• Gijlers, H. (2005). Confrontation and co-construction; exploring and supporting collaborative scienti�%Gfi�%@c discovery learning with computer simulations. University of Twente, Enschede.

• Hickey, D. T., & Zuiker, S. (2003). A new perspective for evaluating innovative science learning environments. Science Education, 87, 539-563.

• Jackson, S., Stratford, S., Krajcik, J., & Soloway, E. (1996). Making dynamic modeling accessible to pre-college science students. Interactive Learning Environments, 4, 233-257.

• Ketelhut, D. J., Dede, C., Clarke, J., & Soloway, E. (1996). A multiuser virtual environment for building higher order inquiry skills in science. Paper presented at the American Educational Research Association, San Francisco.

• Swaak, J. (1998). What-if: Discovery simulations and assessment of intuitive knowledge. Unpublished PhD, University of Twente, Enschede.

• Swaak, J., Van Joolingen, W. R., & De Jong, T. (1998). Supporting simulation-based learning; the effects of model progression and assignments on definitional and intuitive knowledge. Learning and Instructions, 8, 235-253.

• Van Joolingen, W. R., & De Jong, T. (1991). Characteristics of simulations for instructional settings. Education & Computing, 6, 241-262.

• Van Joolingen, W. R., & De Jong, T. (2003). Simquest: Authoring educational simulations. In T. Murray, S. Blessing & S. Ainsworth (Eds.), Authoring tools for advanced technology educational software: Toward cost-effective production of adaptive, interactive, and intelligent educational software (pp. 1-31). Dordrecht: Kluwer Academic Publishers.

• Van Joolingen, W. R., De Jong, T., Lazonder, A. W., Savelsbergh, E. R., & Manlove, S. (2005). Co-lab: Research and development of an online learning environment for collaborative scientic discovery learning. Computers in Human Behavior, 21, 671-688.

• White, B., & Frederiksen, J. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition and Instruction, 16, 3-118.