Computer simulation

Draft

Definition

“[Computer] simulation is defined as having the following two key features:

1. There is a computer model of a real or theoretical system that contains information on how the system behaves.
2. Experimentation can take place, i.e. changing the input to the model affects the output.

As a numerical model of a system, presented for a learner to manipulate and explore, simulations can provide a rich learning experience for the student. They can be a powerful resource for teaching: providing access to environments which may otherwise be too dangerous, or impractical due to size or time constraints; and facilitating visualisation of dynamic or complex behaviour.” (Thomas and Milligan, 2004)

See also simulation (list of other types)

Simulation in education

Simulations can be considered a variant of cognitive tools, i.e. they allow students to test hypothesis and more generally "what-if" scenarios. In addition, they can enable learners to ground cognitive understanding of their action in a situation. (Thomas and Milligan, 2004; Laurillard, 1993). In that respect simulations are compatible with a constructivist view of education.

The inquiry learning perspective

“Inquiry learning is defined as "an approach to learning that involves a process of exploring the natural or material world, and that leads to asking questions, making discoveries, and rigorously testing those discoveries in the search for new understanding" (National Science Foundation, 2000). This means that students adopt a scientific approach and make their own discoveries; they generate knowledge by activating and restructuring knowledge schemata (Mayer, 2004)). Inquiry learning environments also ask students to take initiative in the learning process and can be offered in a naturally collaborative setting with realistic material.” (De Jong, 2006).

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.

Software

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

• [JeLSIM] - Java eLearning SIMulations.Jelsim Builder is a tool for the rapid production of interactive simulations (Jelsims).

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, Ton (2006) Computer Simulations: Technological Advances in Inquiry Learning, Science 28 April 2006 312: 532-533 DOI: 10.1126/science.1127750

• 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.

• de Jong, Ton; van Joolingen, Wouter R. (1998). Scientific Discovery Learning with Computer Simulations of Conceptual Domains, Review of Educational Research, Vol. 68, pp. 179-201.

• Gijlers, H. (2005). Confrontation and co-construction; exploring and supporting collaborative scientific 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.

• Laurillard, D. (1993). Rethinking University Education: a framework for effective use of educational technology, Routledge.

• Mayer, R. E. (2004), Should there be a three strikes rule against pure discovery? The case for guided methods of instruction. Am. Psych. 59 (14).

• National Science Foundation, in Foundations: Inquiry: Thoughts, Views, and Strategies for the K-5 Classroom (NSF, Arlington, VA, 2000), vol. 2, pp. 1-5 HTML.

• 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.

• Thomas, R.C. and Milligan, C.D. (2004). Putting Teachers in the Loop: Tools for Creating and Customising Simulations. Journal of Interactive Media in Education (Designing and Developing for the Disciplines Special Issue), 2004 (15). ISSN:1365-893X http://www-jime.open.ac.uk/2004/15

• 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.

• Van Joolingen, W.R. and King, S. and Jong de, T. (1997) The SimQuest authoring system for simulation-based discovery learning. In: B. du Boulay & R. Mizoguchi (Eds.), Artificial intelligence and education: Knowledge and media in learning systems. IOS Press, Amsterdam, pp. 79-86. PDF

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