Software Simulations in Science Courses
by Dana Encheff


Today's science educators increasingly utilize technology as a means to deliver science content and as a way to provide opportunities for students to interact with the physical world and explore scientific concepts in ways they could not within the confines of the classroom walls. This technological innovation is dramatically changing the way students learn about this world--from the inside of cell to the mechanical underpinnings of a car engine, students can see in virtual reality what they cannot in real life. This wiki reports on various studies that have been conducted by researchers that demonstrate the unique ways in which educators have attempted to use these innovative science simulations within their classrooms. This wiki tries to show both the pros and cons educators have discovered when using simulations, as well as other factors one must consider when using simulations. It is my hope that this report on the results of these studies may help inform the selection and implementation of science simulations in your classroom.

Definition of simulation and simulation design principles:

Our course text defines a simulation as, "A model of some phenomenon or activity that users learn through interaction with the simulation" (Alessi and Trollip, 2001). The word "model" refers to something (in this case the computer software program) that represents a real thing. A basic model of the solar system, for example, might include the nine planets (yes, I'm including Pluto), other bodies, like asteroids and moons of the planets, and a programmed function that controls the orbiting pattern and speed of the planets. As one uses this model, he or she would consciously or subconsciously think about how well this model represents the real thing. Therefore, an important factor to consider about models is how close they come to representing reality. Alessi and Trollip refer to this as fidelity. A model that comes close to replicating reality has high fidelity; the opposite is true for low fidelity programs. Alessi and Trollip also point out that not all models need to have high fidelity--it really depends on the purposes of the simulation activity and the characteristics of the learners. Another factor to consider is how much simulations allow the learner to control variables. The extent to which a simulation program allows one to change parameters, determines often how much learning one can do from a program. I will refer to some of these design principles through the report of research in order to bring to light the important elements of the simulations being discussed in the research.

An example of a cutting-edge science simulation program:

Many of the features of the E-Cell simulator above make it an ideal type of simulation software program. It will become apparent from the research findings below why this is so. As you read my report on the research, please compare the findings with your observations of this E-Cell program.

Approaches to using and designing simulations: What does the research say?

Simulations combined with another activity

Jaakkola and Nurmi (2008) tested the effectiveness of using both simulation and regular lab activities in an inquiry-based elementary science class. They found that using simulations and real lab experiments together to learn complex science content has positive effects on science achievement and conceptual understanding (p.271). Researchers stated that complex science content consists partially of abstract principles (in this study, Ohm's law working within electrical circuits) (pg. 272).Alternatively, the researchers found that simulations or regular lab experiments by themselves, do not alone have a significant affect on student achievement as much as the combination method.

Providing support during simulation activities

In a qualitative study of three separate college courses that used three different types of simulations, Blake and Scanllon (2007) noted what made these simulations successful for students. The researchers accomplished this by surveying students and professors and by observing students working on simulation activities. First, the researchers noticed that simulations sometimes need some sort of worksheet, notes, or questions to guide thinking. Not all simulations have help features. Also, because simulations usually expose complex science concepts, it is important that teachers supplement simulation activities with something that helps students develop their understanding in a linear or at least organized fashion. One way to accomplish this is to give students notes that guide them through simple steps first then complex ones later. The notes this teacher in the study used also provided explanations for phenomenon, so students could reference them if something confusing came up in their simulation. Another way this professor helped students was to give them the parameters to set within the simulation. Then students were asked to explain the patterns, differences, or similarities they observed under different conditions. In the second simulation activity, the professor took great care to directly teach the in-and-outs of the simulation software. The professor stressed the importance of guiding the students through the purpose, use, and settings of the simulation activity by using teaching strategies like direct instruction, guided instruction, independent instruction, and assessment. Some students who participated in this simulation wrote that they felt the pre-simulation instruction helped them understand more about the simulation and were able to use it more effectively. In the third simulation program, the researchers focused on the built-in guidance within the software itself. This third software program had pop-up explanations, help-buttons, and prompts within the program. This type of guidance, though not teacher-initiated, still had a positive impact on students' perceptions of the simulation. Students explained that it helped them focus and figure out problems on their own.

The role of teacher: directing students' thoughts and misunderstandings from limited simulations

Many simulations do not sufficiently explain the scientific concepts they represent in a way most students can easily understand. It is possible for students to navigate their way through a simulation, know generally what it's about, but yet not learn anything at a conceptual level from it. Because some simulations lack clear conceptual explanations, teachers must play an active role during the students use of some simulations. Neulight et. al (2007) found this to be the case. Using a program on Whyville (an avatar based three-dimensional social site for kids) called Whypox, students engaged in an activity that represented the effects of the spread of a virtual epidemic. Knowing this simulation could be used to help students understand the causes, terms, effects, and real-world examples associated with natural infectious diseases, the teacher decided to implement a couple strategies that would help scaffold learning for her students. First, she decided what concepts she wanted students to understand from the program (she created objectives). Then, she picked key vocabulary for this topic, and held daily discussions and writing activities with her students, to get a feel for their developing understanding from using the program (she used formative assessment). The researchers found that the use of the simulation, coupled with whole-class discussions and a clear set of learning objectives, the students developed a greater conceptual understanding of diseases. Students used appropriate vocabulary to discuss diseases--both in the simulation and from examples in the real world. However, researchers found that Whyville did not help students in understanding the microscopic level of disease spreading. Most students thought avatars contracted diseases from being near someone who was sick or by touching another avatar. Though this is true, students may falsely attribute touch and physical proximity a common way to contract diseases. In reality, the spread of natural infectious diseases is much more micro-biological. As students developed misunderstandings, it was extremely important for the classroom teacher to hold discussions and clear up misunderstandings.

Summary of key findings regarding science simulations:

  • Teachers may need to do the following to ensure the simulation helps students accomplish learning goals:
    • set observable objectives you want students to achieve by using the simulation
    • directly state the purpose of the simulation software and how it will be used to accomplish the learning goals to the students
    • provide students with notes, insights, and explanations in conjunction with the software (especially if the software doesn't include its own feedback feature) also commonly referred to as an auxiliary worksheet.
    • choose simulation activities that are easy to navigate, visually appealing, and clearly represent what they are supposed to be modeling
    • include interaction with real phenomenon to the extent that it is realistically possible (i.e., couple the simulation with a real lab activity)
    • think about and discuss with students the limited nature of the simulation and how it compares to reality (e.g., many other variables are usually at work in reality that affect the outcome of situations).
  • Software should have the following features:
    • Quality in fidelity (e.g., planets look like planets, data comes close to real amounts, etc.)
    • Option to slow and speed up time (real time vs. enhanced)
    • Option to set parameters
    • Feedback and help
    • The ability to see graphical representations or alternative perspectives during the simulation (e.g., as you enter parameters for disease in a population, you see a graph depicting how much of the population is infected, rather than just a bunch of characters on the screen looking ill).

Some science simulation examples:

Very basic examples of simulation activities can be found at these websites below. Note that these simulations do not necessarily contain the most effective simulation features mentioned above. However, it is a good idea to get a feel for how simple simulations work before moving on to advanced ones:

More advanced and free examples. Note that most of these were designed for higher education, but can still be useful for elementary students as long as proper support is provided by the teacher and clear learning goals can be achieved from the use of such simulations.

Professional simulation design information:


Blake, C. & Scanllon, E. (2007). Reconsidering simulations in science education at
a distance: features of effective use, Journal of Computer Assisted Learning, 23, 491-502.

Jaakkola, T. & Nurmi, S. (2008). Fostering elementary school students’ understanding of simple electricity by combining simulation and laboratory activities, Journal of Computer Assisted Learning, 24, 271–283.

Neulight, N., Kafai, Y., Kao, L., Foley, B., & Galas, C. (2007). Children's participation in a virtual epidemic in a science classroom: making connections to natural infectious diseases, Journal of Science and Education Technology, 16, 47-58.