ICTs provide teaching tools that are found to be very effective in the learning process based on virtual platforms. In e-learning, virtual laboratories are particularly useful because of the aid they can provide students when they are carrying out practical activities. According to the UNESCO, a virtual laboratory is defined as a workspace for remote collaboration and experimentation aimed at doing research or similar activities, and at reporting and disseminating the results by means of ICTs (UNESCO, 2000). Some authors (Psillos & Niedderer, 2002) indicate that, by coordinating experimentation activities with simulation, the latter can serve as a cognitive bridge between theory and practice. For others (Marqués, 2000), virtual laboratories are virtual learning environments that take advantage of the capabilities offered by ICTs to create a teaching environment that is free from the constraints of time and space in presential education, capable of ensuring ongoing virtual communication between students and teachers.
Virtual laboratories are based on the simulation of real phenomena. They provide learning environments in which students can construct their own meaningful knowledge that is transferable to other phenomena having the same underlying physical principle. In this sense, simulation is a powerful computer tool of widespread use in all sectors of society, and its definition will naturally depend on the field in which it is applied. In our case, we are interested in the field of education, in which such simulation can be defined as a computer program that reproduces a real phenomenon, but in a simplified form designed to provide specific learning situations (Alessi & Trollip, 1991). Computer simulations that allow interaction on the part of the student can constitute effective virtual laboratories in their process of learning. This is principally because the students can study the actual system and investigate its behaviour in response to changes in some of its parameters by making measurements, etc. In this way, students will not be using the simulation mechanically, but will be immersed in a process oriented to producing meaningful learning through the use of virtual laboratories.
In physics teaching specifically, many authors have highlighted the nature of computer simulations as cognitive tools (Bryan & Slough, 2009; Chang et al., 2008; Finkelstein et al., 2005; Landau, 2006; Naps et al., 2003; Ronen & Eliahu, 2000; Trumper, 2003; Zacharia & Anderson, 2003), since their use is highly beneficial for conceptual development and change, and for understanding many physical phenomena in various areas of study, for example, in mechanics (Gorsky & Finegold, 1992; Tao & Gunstone, 1999), optics (Eylon et al., 1996; Goldberg, 1997; Tao, 2004), or across the curriculum in general (Zacharia & Anderson, 2003). However, the integration of simulations into the curriculum requires their effectiveness to be evaluated. Specifically, over the course of the last two decades the positive impact of computer simulations has been documented in different stages of the teaching and learning process. Some authors (Snir et al., 1995) affirm that, with computer simulations, the learning process is far more efficient and applicable to problems or situations of the real world. Other studies have shown their benefits for cognitive development, skills, conceptual understanding, etc. (Goldberg & Bendall, 1995; Goodyear et al., 1991; Gorsky & Finegold, 1992; Hewson, 1985; Kaput, 1995; Shin et al., 2003; Tao & Gunstone, 1999; Zacharia & Anderson, 2003). Many of these workers have shown that groups of students who have worked with computer simulations learn more successfully (Baily & Finkelstein, 2009; Finkelstein et al., 2005; Zacharia & Anderson, 2003), although other authors argue that the benefits of learning through simulations are ambiguous (Steinberg, 2000), or that the practices carried out in virtual environments are useful as an educational complement, but cannot replace the real laboratory (Aleksandrov & Nancheva, 2007).
The potential educational value of computer simulations in virtual laboratories lies in their ability to reproduce phenomena with varying degrees of complexity, so that they can be adapted to the students' cognitive level, or to attaining some given educational objective. The ability to interact with the software allows students to modify the conditions of the processes involved, and to analyze the changes they observe. This makes simulation an extremely useful tool in experimental work. Indeed, its possibilities of application seem limitless.
Our research group has a long experience in the development and use of computer simulations, from analogue simulations of more than 25 years ago before the boom in personal computers (Calvo & Pérez, 1983; Pérez et al., 1979a, 1979b; Pérez & Calvo, 1984), to the digital simulations we are working on now. Despite the repeatedly proven teaching effectiveness of simulations, one of the challenges we constantly have to face in developing a simulation is how to adequately reproduce the phenomenon in question. For example, experiments in virtual spaces offer a new approach to presenting the abstract concepts of a real phenomenon. We have often observed that, in the more applied areas of science, some students have serious difficulties in reliably identifying what they observe in the simulated model with reality. In the more theoretical areas, however, it suffices to present purely abstract constructions such as those provided by traditional computer simulations, while in applied areas it is important to include not only the properties characteristic of the basic phenomenon, but also a certain degree of reality in the experiment.
This conflict between the abstract or idealized and the concrete or real has been analyzed bysome authors. Goldstone & Son (2005) discusses the trade-off between the advantages of concrete simulations and the benefits of simulations with more idealized models. For Difanzo et al. (1998), a high level of detail by means of realistic representations of objects within the simulation can benefit students in their study of a particular phenomenon by increasing the similarity between the simulation and the real world. Indeed, most research on virtual reality has had the specific purpose of the realistic imitation of real-world phenomena (Grady, 1998). Other authors have argued, however, that relatively simplified and idealized representations are useful for distilling a situation to its essence (Goldstone & Sakamoto, 2003).
Thus, some authors stress the importance of the simplification of reality involved in simulations, of omitting or changing details, since they find the advantage to lie in focusing the students' attention on the development of certain skills (Alessi & Trollit, 1991; M. Grabe & C. Grabe, 1996). But others, taking a constructivist perspective, value the students' opportunity to perform complex tasks in scenarios that simulate real life (García & Gil, 2006; Lajoie & Azevedo, 2006). In this latter case, the simulations reflect the complexity of the real phenomena, allowing the students to develop cognitive skills and re-structure their mentalmodels when they compare the behaviour of the models with reality.
Schematic simulation, for example, is a dynamic, simplified representation of the behavior of a system. It allows students to manipulate data and examine the consequences, avoiding the confusion and insecurity that would be involved in a complex environment. It can enrich the constructivist approach to learning by enabling students to anchor their cognitive understanding in what they observed through their actions in a given situation (Harper et al., 2000).
While some authors have argued for the benefits of idealization as against the concrete for the acquisition of underlying abstract physical principles, the main objective of our simulations is to fill the gap the student has in realistic situations when faced with observing a real phenomenon after having studied it in a schematic simulation. In this regard, we must distinguish between simulations which "simulate the result", and those which "simulate the experience". Thus, schematic simulations in Java are useful to simulate results. For example, if we remove all the details, and focus schematically on the underlying foundation of the physical phenomenon, one can effectively transfer abstract phenomenon to other scientific fields (Goldstone & Son, 2005). In this regard, we consider that it would be very effective for our students' learning if they could also "simulate the performance of the experience", i.e., if we added to the simulation of the system a realistic visual output of the phenomenon being simulated. In the particular field of our area of education, Optics, the objective of our simulations is to "simulate the experience" – to show students what the abstract phenomenon simulated schematically in Java looks like in reality, creating a hyper-realistic simulation of the phenomenon in its entirety, i.e., the simulated experience.
In our research, we have focused on the development of a virtual environment with computer simulations that have a greater degree of reality than traditional ones. To implement these simulations, we used computer tools designed specifically for scientific environments, and which are freely available and aimed at users who are not programming specialists. Among these tools, we would highlight EJS and POV-Ray, both of free distribution. A common feature of these two environments is that they allow the user to concentrate efforts on the model of the system being studied, and greatly facilitate the entire process of creating the graphical interface and its connection with the model. This is a great advantage in preparing simulations, since one can focus on modeling the phenomenon or system without getting lost in programming the code. With our students, we use EJS which produces Java applets that are easily distributed, and POV-Ray which allows us to complement the Java applets by endowing them with hyper-realism. The result is a virtual learning environment that requires the active involvement of the student, and thus ensures deeper learning.
To summarize the above, interactive simulations facilitate deeper learning of concepts, since it is the students themselves who observe the physical phenomenon and can interact with the model to create mental structures from which to construct their own conceptual models of the phenomenon.
The computer simulations we have implemented form part of a virtual teaching approach using e-learning platforms. Specifically, we use the AVUEX virtual campus of our university with the Moodle platform. These platforms strengthen group work in the form of collaboration between teacher and students and among the students themselves, fostering a constructivist learning environment. Examples of these simulations can be found on our group's website: http://grupoorion.unex.es.
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