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(2004)]. The use of complex system models makes the comparison with the real world data possible and provides the opportunity for revision and improvement of the modeling, based on the real world characteristics (Jacobson and Wilensky, 2006). Furthermore, modeling can help learners “express and externalize their thinking” and “help them to visualize and test components of their conceptual ideas, which may help them advance their thinking and develop subject matter expertise” (Schwartz & White, 2005, p.167).

Moreover, the models that students construct have to be considered as adjustment between the questions-experiences, they have and the explanations they give (Acher et al. , 2006). Consequently, as Jacobson and Wilensky (2006) add, by allowing students to involve with the modeling process through the representation of unobservable phenomena and express their thinking mistaken assumptions they might have can be revealed and so, later on revised and change.

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Penner (2001) argues that models can be “tools to think with and reflect upon”, since they represent features of physical and conceptual values that cannot be represented with real forms or be observed directly in the natural world (p. 2). Besides, models are valuable because they can have an important contribution in originating new ideas and developing the imagination (Pauling, 1983 cited in Glynn and Duit, 1995). Above and beyond, it is important for students not just to use models in their science teaching but also gain knowledge about the nature and purpose of scientific models (Grosslight et al, 1991, Van Driel and Verloop, 1999).

Moreover, learning to model should be a social procedure that involves discussion and negotiation of meaning, because this provides the best opportunity for each student to construct the desired knowledge (Harrison and Treagust, 1998). However, as a research suggests (Grosslight et al. , 1991), students should have more experience in using models as tools for learning and experience with discussions underlying the role of models in scientific concepts.

Wilensky and Reisman (2006) highlight the need for further experience with models in science education by saying that all students seek to understand science and the world around them. Besides, when students manage to accomplish modeling skills they can use them in novel situations in the domain of instruction (White, 1993, White and Frederiksen, 1990). The use of models in science education requires great effort and there are difficulties that not only students but also teachers need to overcome, in order to achieve meaningful and efficient use of modeling.

Teaching students about models and modeling has proven a quite challenging and difficult task (Schwartz & White, 2005). However, research showed that neither students nor their teachers possess efficient knowledge about the nature and purpose of scientific models (Van Driel &Verloop, 1999). Consequently, some students fail to understand the purpose of engaging with the modeling process (Barrowy & Roberts, 1999) and they also might not realize the nature of models or modeling, even if they are engaged in creating and revising models (Carey and Smith, 1993; Grosslight et al.

, 1991). On the other hand research has shown (Louca & Constantinou, 2002) that learning about models and modeling can be accomplished in early middle school ages by guiding students through a process of developing and refining models about natural phenomena. Therefore teacher’s role in teaching science through an efficient and successful modeling approach is important. Teachers should develop their knowledge in teaching scientific concepts and achieve self-efficacy in teaching and as Bandura (1981) argues self-efficacy can be enhanced through modeling.

Similarly, Enochs et al.(1995) support that in order for elementary teachers to achieve self-confidence, well planned and modeled based lessons are required. Also, when students are building models and using their own analogies, instead of those of teachers, will be more benefited (Harrison and Treagust, 1998) and this is due to the fact that students’ analogies are more familiar and easier to understand (Zook, 1991). On the other hand, students find it difficult to select appropriate analogies, so they expect from the teacher to give an analogy or a model, even if they have difficulties in mapping it (Harrison and Treagust, 1998).

Moreover, some difficulties that students find when trying to construct meaning in science are due to the fact that they don’t have efficient ability and knowledge in developing conceptual models of physical phenomena (Golin, 1997). Consequently, teachers should use analogies and models in their teaching through an approach that involves focus, action and reflection (Treagust et al. , 1998). Also, considering the importance of hand-on lessons, primary teachers should continuously improve their teaching methods especially in the area of hands-on activity planning (Dickinson et al, 1997).

Modeling teaching practices can be an appropriate and useful tool, since they promote teaching though practical demonstrations (Hudson, No date). Though, some times models that are used in physics only demonstrate the end product of physics to students (Steinberg, 2000), something that can limit students critical thinking and take from them the opportunity to observe and find out new phenomena by themselves. Factors that influence modeling-based teaching

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). Constructivism 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). Modeling tools 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]. When teachers design learning activities to help their students understand complex systems and the way they function and change, model-making activities with computers can play a supportive role since students can construct their own understandings through them (Riley, 1990).

As Osborne and Hennessy (2003, p. 23) claim “research suggests that using computer modeling and simulation allows learners to understand and investigate far more complex models and processes than they can in a school laboratory setting”. Moreover, researchers found that the use of computer models in educational subjects might provide opportunities for students to promote their understanding of unobservable phenomena in science (De Jong et al. , 1999; Stratford, 1997).

Additionally, computer modeling can make some scientific material more accessible and interesting (Papert, 1980), since computer simulations, along with other model-based teaching strategies could be a “powerful combination for supporting students’ visualization of unobservable phenomena” (Tray and Khan, 2007). Still, this visualisation of scientific concepts and complex systems is significant in science education since it enables students to resolve conceptual and reasoning difficulties.

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