In addition, there are various factors that might affect a successful implementation of the modeling procedure in science teaching, that need to be taken under consideration. One of the factors that play an important role in the modeling process are the skills that students should acquire in order to respond effectively in this kind of teaching method. Even if there is no definitive agreement on specific skills that compose the skills involved in modeling (Constantinou, 1999; Schwarz and White, 2005), the importance of defining these skills is commonly recognized.
(Papaevripidou et al., 2006). In addition, when students are using models in science are “expected to develop particular abilities as part of their cognitive development; thus there are ages that students should not be expected to have and use particular thinking strategies” (cited in Louca, 2004, p. 14). On the other hand, students are thought to have a variety of thinking strategies that depend on several factors, such as context (Louca et al., 2002; Samarapungavan, 1992). Students present these differences from adults in thinking abilities since these abilities are developed by nature and young learners have not yet developed them (Kuhn, 1989).
Moreover, an effective modeling approach, in order to be successful in the science education, should be based on what students know and help them construct on this as well as to refine any fault assumptions they might have. As Laurillard (2002) underlines constructivism is considered valuable since it supports the understanding of how someone learns when interacting with the real world. Also, Carey et al. (1989) assume that scientists hold constructivist conceptions of knowledge in their field. However, is not clear which futures of constructivism are taken into greater consideration and if they are held by different groups of students (Grosslight et al., 1991).
Therefore, a pedagogical framework based on the constructivism should be obtained when a modeling-based approach is used in the science teaching. Modeling, when it is used properly, can easily support a constructivist approach through the construction, revision and improvement of a model, since students can express their ideas, hypothesize about a phenomenon, make observations, revise and improve their model continuously and finally resolve any misconceptions they might have. As a result, students will construct meaning through a continuous and active process, something vital in the science teaching (Gunstone, 1988).
Moreover, students become active participants in the learning process, refining their own learning goals and extracting meaningful relations through their experiences (Barab et al., 2000). As Jacobson and Wilensky (2006) underline “a central tenet of constructivist and constructionist learning approaches is that a learner is actively constructing new understandings, rather than passively receiving and absorbing “facts””. Hence, through the modeling process students actively make “connective webs of meanings in science learning”, by exploring and revising various models (Louca and Constantinou, 2002, p.3).
Furthermore, models are tools for finding relations between certain facts or processes, in order to explain the specific facts (Grosslight et al., 1991). Hence, modeling-based teaching depends on the tool used and it’s quality and functionality depends on what it represents and the natural phenomenon that examines (Louca and Zacharia, 2008). Also, the degree of how well students conceptualize natural phenomena varies according to the modeling tool used to construct and communicate a model to others (Papaevripidou et al., 2006). But “if there are different kinds of representation (analogies, idealizations, etc.), then there are also different kinds of learning” (Stanford Encyclopaedia of Philosophy, 2006). Consequently, an important factor that should be considered in a modeling-based approach is the modeling tool that will be used and the purpose that will serve.
Computer-based modeling in Science Education Previously, the importance of the modeling tool used in the science process was highlighted; therefore a lot of researchers and educators conducted studies in this field. Going through the literature, the most promising educational modeling tools revealed to be computer-based (Louca, 2004; Sherin et al., 1993; White and Fredriksen, 1998). Specifically as Louca (2004) supports computer program can be a model of a physical system, and modeling through programming may make the process more tangible.
Also, while modeling became important in society, many students will need to use computer-modeling technology in their lifetimes (Sabelli, 1994). Therefore, by recognizing the importance of computer-modeling in science education, “over the past 10 years, many researchers have developed computer-based modeling tools to support elementary and secondary school students in scientific modeling” [(e.g., Mandinach, 1989; Resnick, 1996; Schwarz, 1998; White ; Frederiksen, 1998) cited in Zhang et al., 2005, p.580].