Iterative+Simulations

Iterative Simulations
Clayton Mark

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Simulation software can be traced back to World War II, yet it did not reach mass appeal until the early 1980s. Its uses span across many occupational and educational settings. From flight simulation to weather forecasting, from stock market crashes to car crashes, from preschoolers to pre-medical students, simulations have the ability to help just about anyone with the creation of real world situations on a computer screen. Educators are continually seeking ways to implement simulation software. It’s an opportunity to bring the outside world inside the classroom. It does not, however, happen by chance. Which begs the question: What potential lies within the use of iterative simulation software inside the classroom?======

media type="youtube" key="vCTRWD3DFsA" height="385" width="480" We've come a long way.

Iterative simulations allow the learner to run scenarios multiple times. As the simulation is run over and over, the learner is able to change variables in order to see what happens. These software programs also have the ability to eliminate time. What once took days to observe is condensed to a matter of seconds. The cycle of the moon can be observed in one sitting, or a veterinarian can see the long-term effects of a treatment on a patient in moments. Time can be sped up, slowed down, or paused. The learning objectives are unclear. The learner explores and gradually constructs knowledge from repeated trial and error situations (Alessi & Trollip, 2001).

Iterative simulation software allows students to engage in real-life situations without a variety of concerns. In a study by Trundle and Bell (2010), a moon cycle software simulation was shown to release students from the restrictions of geographical hindrances, bad weather, and being out in unsafe neighborhoods at night. Similarly, Wilson (2005) described an ability for students to create rocket designs that they might not have ever been able to attain to gravity, air pressure, and cost concerns. The ability to create events that students might never otherwise be able to experience is an amazing benefit that iterative simulations provide (Henderson, et al, 2000).

Perhaps the most important factor that these software programs control is the variable of time. The students who observed the moon in the Trundle and Bell (2010) study were able to accomplish in one day what the control group did in twenty eight days. Other studies showed likewise the ability of students to practice safely on medical patients and see the results of their treatments over a long period of time (Holzinger, et al, 2009, Rawson, et al, 2009). From there, students were able to see their success or learn from mistakes by rerunning the simulation. Check out a brief example of how time is not a factor below:

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The best way to understand is to try one out. This is the original software program that got me excited about iterative simulations. Check it out!



Science itself is an iterative process. The scientific method calls for evaluation and assessment of ideas, changing hypotheses, and testing again to see if these new ideas work. Iterative simulations are an ideal match for these thought processes (Schwarz, 2009). Experimentation (Rawson, et al, 2009), variable control (Wilson, 2005), and classification (Henderson, et al, 2000) were all shown to be evident in students. This is possible in our own classrooms!

Henderson, Klemes, and Eshet (2000) also studied higher level cognitive outcomes that went beyond science. Their study of second grade students using an iterative archaeology simulation called "Message in a Fossil" revealed that students were showing use of sequencing skills, inference, and cause and effect. By traveling to a location that could not have physically been visited by this classroom, the students were able to internalize and make meaning of the content. One teacher described their learning by stating:

==“It’s just not the same, reading about and looking at fossils and doing it. And they really did it. They felt like they were paleontologists and that’s what made the big difference because they had so much ownership of it.” (Henderson, et al, 2000, p. 121). ==



As seen in the paleontology study, the students were highly motivated. Malone’s theory of motivation centers around four different aspects: challenge, curiosity, fantasy, and control. Iterative software has the ability to give the user all four of these. By creating that which cannot be readily available, students’ motivation can be heightened by the unknown and their learning can be more meaningful.

Wild and Braid (1996) also saw cooperative grouping as a benefit of computer simulation software. Using a ship navigation software, students had to work together to navigate and properly steer their ship around Australia. The data showed that students were engaged in higher-level, cognitively oriented conversation. In a similar study, collaboration during iterative software lessons allowed students to show evidence of verbalization of ideas, peer teaching, and risk-taking (Henderson, et al, 2000).

The uses of iterative software are numerous, but they do not solve all of our educational woes. Simulations need to be incorporated into an already integrated curriculum for a substantial period of time. Simply running a simulation once will not bring about adequate learning (Henderson, et al, 2000). Also, students require feedback based on their simulation experiences. The educator’s responsibility is to help usher the student through the simulation in order to give the deepest understanding of the underlying principles (Rawson, et al, 2009). Educators also need to find software that they are excited about. This excitement and passion for the topic will also carry over into the students’ success (Schwarz, 2009).

Finally, students should be given the opportunity to reflect upon their learning (Trudle & Bell, 2010). Looking back on what has been learned from iterative simulation experiences and applying new content to their own lives is what will make it deep and meaningful. This transfer of learning is what will take the content off the screen and into our students’ lives. Iterative simulations have the potential to create situations that our students might never experience, yet in a fraction of the time. The possibilities are infinite!

References Alessi, S. & Trollip, S. (2001). Multimedia for learning: Methods and development. New York: Allyn and Bacon. Henderson, L., Klemes, J., & Eshet, Y. (2000). Just playing a game? educational simulation software and cognitive outcomes. Educational Computing Research, 22, 105-129. Holzinger, A., Kickmeier-Rust, M., Wassertheurer, S., & Hessinger, M. (2009). Learning performance with interactive simulations in medical education: Lessons learned from results of learning complex physiological models with the HAEMOdynamics SIMulator. Computers & Education, 52, 292-301. Papageorgiou, G., Johnson, P., & Fotiades, F. (2008). Explaining melting and evaporation below boiling point. Can software help with particle ideas? Research in Science & Technological Education, 26, 165-183. Rawson, R., Dispensa, M., Goldstein, R., Nicholson, K., & Vidal, N. (2009). A simulation for teaching the basic and clinical science fluid therapy. Advances in Physiology Education, 33, 202-208. Schwarz, C. (2009). Developing preservice elementary teachers’ knowledge and practices through modeling-centered scientific inquiry. Science Education, 93, 720-744. Trundle, K. & Bell, R. (2010). The use of a computer simulation to promote conceptual change: A quasi-experimental study. Computers & Education, 54, 1078-1088. Wild, M. & Braid, P. (1996). Children’s talk in cooperative groups. Journal of Computer Assisted Learning, 12, 216-231. Wilson, S. (2005). Design software gives rocketry a boost in the classroom. Tech Directions, 64, 17-20.