Computer simulations in science education

Definition of a computer simulation

Simulations are computer programs that contain a simplified model of a system or process. Scientific numerical simulations are based on the implementation of theoretical models and are used to study the operation and properties of a modeled system as well as to predict its evolution. Alessi and Trollip (1991) describe simulations in an educational context:

ā€œA simulation is a powerful technique that teaches about some aspect of the world by imitating or replicating it. Students are not only motivated by simulations, but learn by interacting with them in a manner similar to the way they would react in real situations. In almost every instance, a simulation also simplifies reality by omitting or changing details. In this simplified world, the student solves problems, learns procedures, comes to understand the characteristics of phenomena and how to control them, or learns what actions to take in different situations. "

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Types of simulations

  • Experimental simulations are used to place the cognitive or affective stage for possible learning. The use of these programs precedes the formal presentation of the learning material (for example: BioLab, MtnSim)

  • Informing simulations are used to communicate information to the student. However Thomas and Hooper (1991) have shown that simulations are not an appropriate way for knowledge transfer when they are used without teacher support, but that they must be integrated in a supportive environment of the teacher. regular student work in class or in the laboratory.

  • Reinforcing simulations, again according to Thomas and Hooper (1991), can be used to reinforce very specific learning objectives. The most common format for a reinforcement simulation is performance and practice. In such a simulation, a sequence of stored or produced exercises, to be completed, is presented to the student. These simulations are designed to adjust the student's level of knowledge and to track his progress.

  • Integration simulations seem more promising in science education. In fact, students learn the knowledge and effective principles required and use simulations to apply this knowledge:
    "The use of integrating simulations seems to be most prevalent for the acquisition of diagnostic skills. In these studies, the students first learned the required factual information and principles and then used the simulations to relate and apply that knowledge ā€(Thomas and Hooper, 1991).
    => These simulations provide students with a contextual environment in which they take place and play roles (eg exploring the Nardoo, Bioworld).



Contribution of simulations to science education

  • Simplify the real systems studied

Real systems, studied in science education, are complex and dynamic. They are often presented in a simplified manner in order to allow students to focus on the critical information or skills to be developed, and therefore to facilitate their learning.

  • Present an alternative to inaccessible experiments

According to Mintz (1993), one of the most promising computer applications in science education is the use of simulations to develop teaching materials suitable for experiments that we cannot perform by conventional laboratory experimentation in the classroom.

  • Activate and develop skills

According to Roth and Roychoudhury (1993), simulations can activate basic procedural skills in science students such as observing, measuring, communicating, classifying, predicting, as well as procedural skills built into the scientific process, such as controlling variables, formulating hypotheses, interpret data, experiment and formulate models (Padilla et al., 1990).

  • Present itself as a tool for scientific investigation

Mintz (1993) studied computer simulations as a tool for scientific inquiry, considered a fundamental principle for science learning (National Standard Science Education, 1996). The scientific investigation process includes making hypotheses, performing experiments, observing and recording data, and writing conclusions. He reported that simulation can increase and improve classroom work. Simulations, as an investigative tool, improve motivation and interest.

  • Visualize the phenomena and multiply the forms of representation

Since non-verbal representations stimulate brain activity (Clements & McMillen, 1996), simulation multiplies the forms of representation (images, animations, graphics, digital data) (Cholmsky, 2003). By leaving to the learner the choice of the representations he prefers, it allows learning to be individualized and opens the door to an analysis of the pupil's ways of thinking: by observing the choice of his representations at the same time. 'screen, through metacognitive tools and evaluations.

  • Simulation as a complementary tool to real experiences

The question asked: can simulation be as efficient as the conventional laboratory or replace it? The answer would be that it depends on the concept or the situation. For example Choi and Gennaro (1987) compared the effectiveness of simulated computer experiments versus manual laboratory experiments in teaching the concept of volume displacement to middle school students. They found that simulated computer experiments were as effective as manual lab experiments.

  • Simulation as an intermediate state in theory and practice

Generally, the teaching of science suffers from a lack of interactions between the theoretical world where the student manipulates notions and concepts, the practical world or the student manipulates concrete devices and objects. Simulation can be considered as an intermediate level between theoretical models and the physical manifestations of the phenomena studied (Richoux, Saveltat and Beaufils, 2002)

=> Research also shows that simulations can:

  • contribute to conceptual change (Windschitl and Andre, 1998);
  • providing open experiences for students (Sadler et al., 1999);
  • provide tools for scientific inquiry (Windschitl, 2000) and problem-solving experiments (Howse, 1998)
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