Simulations in active learning

By Manon P.J. Penning (s0003751)

Abstract

With technology striving forward at a very quick pace, simulation has become quite the buzzword in education. How to develop such a simulation is a subject which is not very often addressed. Especially the educational aspects are underexposed eventhough without good guidance and support the learningexperience will become almost zero. In this study a number of approaches for designing a simulation (environment) are addressed as well as some possibilities to embed a simulation into an environment such as Intelligent Tutoring Systems and Virtual Reality. In the next few years simulations will probably become more sophisticated. It is very important that the educational focus is not lost in all the technical tours de force.

Simulations in active learning

A wide variety of definitions exist when it comes to simulations. Some define simulations as any representation of reality which is not reality itself, others define it as a program with a mathematical model inside with initial conditions and rules (Prensky, 2001). In this study Doyles defenition is used:

”Simulation refers to the artificial (and almost always simplified) representation of a complex realword process with sufficient fidelity to achieve a particular goal, such as in training or performance testing.” (Doyle, 2001, p.1)

Simulation dates back to the time of the Romans (Doyle, 2001). Back then warriors were trained with devices like the training-mill from the Zorro movie (The mask of Zorro, directed by Campbell and released in 1998), which is a simulation of an opponent in combat. This shows that contrary to what many people think, simulations do not need to be computer-based to be a simulation. Nowadays, simulation is a standard method for the training of professional people in occupations in which human errors would be costly and dangerous and this is done mostly by computer-based simulations (Launonen, Kinnunen, Kuusisto & Vainikainen, 1996). The most common examples of simulations are to be found in aviation (in the form of flight simulators), medicine and nuclear power plants (Doyle, 2001; Hill & Semler, 2001; Prensky, 2001). This study will focus mainly on computer-based simulations, of which there are a number of different types (Doyle, 2001):

Espcially the screen-based graphical simulators are addressed throughout this study as well as Virtual Reality trainers, which are just beginning to gain populairity (Doyle, 2001).

Since ”Simulation” is quite a buzzword these days, it is portrayed as being the ultimate solution for all problems (Prensky, 2001). It is beyond any doubt that there are advantages as well as disadvantages to everything, as is the case with the use of simulations. A list of major advantages and disadvantages is shown below. Advantages:

Disadvantages:

Figure 1: Conversational Framework

Figure 2: Kolb’s experiential learning cycle

Prensky (2001) speaks, in this context, of ”low fidelity” and ”high fidelity” simulations, where low fidelity simulations are less real and only a very limited representation of reality. High fidelity simulations attempt to model reality as closely as possible and thus are less boring to expert students due to their multi-faceted nature. Also these simulations are more extended and accuurate to represent reality more closely. Prensky (2001) concludes that it is not necessary for a simulation to be a perfect representation of reality, neither does it have to be totally engaging, but elements of both are needed to make a quality simulation.

Developing simulations and active learning

The current view on instructional theory is constructivism. The main issue in this view is that each individual constructs knowledge through interpretation of new facts in coordination with their own experience, framed by social interaction (Sujo de Montes et al., 2002). When looking at simulation (and discovery learning) from the constructivist perspective, scientific simulation-based learning also involves the activation of prior knowledge, the interpretation of problem situations, the explanation of experimental outcomes and the modification and integration of conceptual understanding. Computers should not replace the students’ thinking processes, but instead facilitate them (Zhang et al, 2000; Launonen et al., 1996). This is forgotten too often according to Launonen et al. (1996). They warn not to overlook the cognitive aspects when designing something according to new technical considerations. The constructivist theory emphasizes practical application in education, but the higher a student climbs in the tree of education, the more they get removed from experience, and the more the learning becomes abstract (Chee, 2001). Students are quite often able to solve highly complicated problems from their textbooks, but at the same time they have little ”feel” and understanding of the real aspcects behind the formulas. Therefore this ”higher order” learning should be rooted in students’ experiences, by means of real experiments or simulations of those experiments. An effective model to go with this statement is a model by Chee (2001) which is shown in figure 1. It shows operations on the conceptual level, operatioins on the ’real world’ level and the interaction between them as well as between instructor (teacher) and student. When one reflects upon the experience and creates his or her own abtract conceptualization of the subject, one can try to test this set of concepts and thus experience some more and reflect upon that. This resembles a model which has already been constructed in the 80s bij Kolb (1984) and is shown in figure 2.

Figure 3: SimPLE software architecture

In designing a simulation (environment) one of the most important aspects is the underlying model. As stated before, a simulation stands or falls with the quality of its model. According to Doyle (2001) there are two steps in developing a satisfactory model. Firstly one should develop a mathematical model and secondly one should translate the model into a programming language. Another major issue in simulations is the question of how to provide feedback (Doyle, 2001). The simulation itself can give feedback, but this should not be too harsh. For example in medical simulations, when something goes terribly wrong, normally a patient dies. Doyle (2001) states that might not be a good idea to start traumatizing the students with dying patients when they are only fresh students. The ability to re-enact simulations and compare the different learning experiences of students is likely to facilitate discourse that is of more reflective nature (Chee, 2001). Thus feedback in the form of a discussion after the simulaton with an instructor and possibly other students is verry useful. Most simulations are based upon principles of self-learning (Launonen, 1996). Self-learning, in other words learning where students take responsibility for their own education, is very suitable for students who bring life skills and increased reasoning ability to the classroom. Simulations are in turn very useful for learning and especially for this type of learning, since about 90% of the performed actions are remembered as opposed to about 10% of what is read (Gokhale, 1996). This self-learning also implicitly involves the different learning styles that students might have. According to Gokhale (1996) simulations that employ an array of media will help bridge the gap between learning styles of students and teaching styles of instructors (Gokhale, 1996). The aquisition of manipulative skills, for example, can only partly be achieved through self-learning with simulations. This is because physical operations really need to be performed physically. Thus simulations and real hands-on learning should be combined. As far as drill-and-practice items are concerned, there is no difference in performance when comparing simulation and traditional teaching (Gokhale, 1996). Some other issues exist in designing simulations as, for instance, the period for which the simulation remains interesting. Some simulations are interesting the first time, but no more. Others are always found to be boring, because they are number-based (Prensky, 2001). The learning and competing elements of for instance a flight simulator make the experience more engagin. Incorporating video in simulations is something to consider in this context since it is appealing to students, and it demonstrates the knowledge to the student which is an important aspect of a good course or training (Merrill, 2002) Developing a simulation is a very complicated thing, which is shown by the abovementioned points which should be addressed. Different tools and frameworks for constructing simulation-based learning environments exist, such as SimPLE (Simulated Processes in a Learning Environment) (Rose, Eckard & Rublo, 1998). SimPLE builds simulations consisting of two components: a graphical user interface an a application or model. The software-architecture which is used in the SimPLE environment is shown in figure 3. Even whole languages have been devoloped, such as VRML and OOCSMP a continuous simulation language with C-OOL as its own compiler (de Lara & Alfonseca, 2001).

Simulations, ITSs, games and VR

With the current technology and artificial intelligence it is now possible to construct expert systems for complicated processes with many variables (Launonen et al., 1996). However, if students are given unguided assignments, little is learned. In these situations, students are not certain where to start and what to do (Gokhale, 1996). In other words: simulation without accompanying instructions is quite useless. At the same time tutorial software is too specific and leaves no room for discovery learning. A sythesis of multimedia tutorial software and simulation holds a great promise for quality stand alone products in education (De los Santos Vidal, unknown). Still, a simulation-based learning environment can not guarantee e ective learning without sucient support (’scaffolding’) for discovery learning activities (Zhang et al., 2000). What might be usefull here, is the integration of simulations and an Intelligent Tutoring System (ITS). These systems provide helpfull guidance and replace a human tutor in contrast to tutorial software which usually lacks the amount of artificial intellingence needed (Taylor & Siemer, 1996). ITSs consist of four parts:

In stead of an ITS, one can also build a Simulation Game around a simulation to make it more guided. ”A Simulation Game is an active teaching/learning method for processing and solving practical problems by one or more teams. It allows experimental, competitive learning (action learning).” (Adelsberger Bick, Kraus and Pawlowksi, 1999, p.2) Simulation Games consist of:

After finishing a game, the instructor can discuss the performance and problems. Non-cognitive skills such as team work, communications skills and complex thinking skills are promoted implicitly. Simulation Games can be performed manually or computer-supported. These Simulation Games are, especially in combination with traditional learning for the basics, very effective (Adelsberger et al., 1999) Prensky (2001) also states that simulations are quite ideal to incorporate in games and that this is mutually benefitial. It keeps the boredom away from simulations and it gives a game more contents. Using Virtual Reality gives the opportunity to create first-person learning experiences and user-autonomy as well as control over their own learning experiences. In VR students get prompt feedback, which resembles the natural mechanism of seeing the effects of what one is doing (Chee, 2001). Most VRs are simulation-based or to be more precize, actually all VRs are simulation-based when looking at it from a strict perspective. A VR is always a (virtual) representation of reality, but it is one’s definition of concepts such as ”model” and ”simulation” which implies whether all VRs are simulation-based or not. The debate about this yields enough material for a whole new paper and thus is not in the scope of this one. Virtual environments are usually more extended than simulations with respect to their environment. This for instance allows students to collaborate on a whole di erent, and much more natural plain (Chee, 2001). When students are in a collaborative virtual environment, according to Chee they seem to ”find it very natural to ask questions of others who share the same virtual world at that time” (p.47).

Conclusions

Recent developments and current views about simulation were discussed, as well as ways to develop simulations. With the current speed at which tecnology progresses, simulations will probably become a lot more sophisticated in the next few years. The main issue which should not loose focus when designing according to the latest technical fasion is the didactical input. Whithout proper guidance and support the students might have a good time playing a Simulation Game, but do not actually learn. The environment in which the simulation is presented is thus very important, but it remains to be seen whether this is of any consequence to the technique or type of technology being used (tutorial-like software, intelligent tutoring systems, virtual reality). Different techniques offer different possibilities and with technological skills progressing at a quick pace, these techniques rapidly change. It thus depends on requirements at a certain moment which technique should be used.

References

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Enschede, 2003/2004; updated on the internet: july, 26, 2004