Modeling complex phenomena

This is a qualitative study seeking to investigate two different modeling-based approaches in science education and how fifth graders, having their first experience on a modeling-based teaching environment, interact toward these approaches. The two approaches differ to the fact that one is based on a computer-based programming environment (Stagecast Creator) and the other is based on a non computer-based environment (models made with materials). Both approaches were designed having as a framework a constructivism approach, while students’ interactions are observed through students’ individual learning style (auditory, visual, and kinesthetic learners).

The main purpose of the current study is to identify which of the two approaches can support better students’ understandings when they are taught a scientific phenomenon, specifically how day and night occurs and how this depends on students’ individual characteristics. Also, it seeks to examine students’ motivation and engagement with the two modeling approaches. Findings of the study revealed that students’ understandings about the physical phenomenon were promoted through the two modeling-based approaches, while students were able to built or revise their prior knowledge, through the constructivist perspectives that were used. However, students’ modeling skills were enhanced more efficiently with the computer-based approach.

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Still, it was found that students’ individual needs had an impact on the two approaches since specific characteristics of the two modeling approaches seemed to support students’ understanding. Moreover, it was found that other factors could influence the two modeling approaches and their effectiveness on accomplishing students’ understandings about scientific phenomena. Therefore, suggestions for further research in the field of modeling in science are made.

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Models and the modeling process are widely recognized as vital part of the science education, since they can play a determine role on promoting scientific understanding and knowledge. Science education deals with physical systems that are usually complex and difficult to understand while they can’t be observed directly. So, for the acquisition of efficient knowledge about a specific phenomenon modeling process is considered valuable, since it seems to be “promising in scaffolding learners’ understanding of the complex processes of science through building, testing, revising and applying models” (Papaevripidou et al, 2006, p. 145).

By realizing the importance of the modeling process in science, understanding how to support students to gain knowledge on developing models has been one of the main challenges in science education. It is thought that through modeling-based teaching students are engaged in a process of using models as tools for discovering, synthesizing, predicting and as a final result constructing knowledge (Papaevripidou et al, 2006). In addition, as Penner (2001) supports, any experience that students have with modeling-based teaching gives students the opportunity to think and talk about natural in similar ways with those of scientists. In this context, it is thought that the development of efficient models leads to quality outcomes, that can’t be achieved through other educational processes (Harrison & Treagust, 1998). Consequently, modeling except helping students to explore and understand complex phenomena, it can also facilitate their understanding about the nature of science (Linn, 2003).

Besides, the rapid development of computers in education seems to have impact in the modeling-based teaching too, since a lot of researchers support that the most promising tools for modeling appear to be computer-based (Louca, 2004; Sherin et al., 1993; White and Fredriksen, 1998). There is a range of computer based programming environments that are used for the development of models about natural phenomena that are concerned to be valuable in the science teaching. Computer-based modeling appears to be so important since it is claimed to be suitable for investigating complex systems that can’t be observed directly in a science lab (Osborne and Hennessy, 2003; Tray and Khan, 2007)

Another important factor that seems to be important, not only in the filed of science education but generally in education is students’ individual learning style and needs. All of us have an individual way of attending learning, something that needs to be considered for the ease of gaining knowledge. Science teachers have the potential and should use a variety of activities in the science lab, in order to correspond to students’ needs. So the assignments and activities in a science lesson should be structured in order to be flexible and students can use their visual, auditory or kinesthetic strengths (Thomson and Mascazine, 2008). With that way the difficult challenge do gain scientific knowledge and not just receive information about a science phenomenon can be accomplished easier.

Even if the value of modeling-based teaching in science education as well as students’ individual needs concerned a lot of researchers and educators, few studies investigated how a modeling- based approach can support students’ understandings and which features can be helpful for students, according to their individual learning style. Most researches are based on computer-based modeling and how it helps the development of students’ modeling skills. There is a gap to be bridged on how a modeling procedure, either computer-based or non computer-based, can promote students’ understanding about scientific phenomena and how this might depends on different factors.

Consequently, the current study has as purpose to investigate two teaching approaches that are model-based; in order to identify which of the two can qualify better students’ individual learning styles. By taking into account the importance of modeling procedure in science education and the meaning of considering students’ individual needs in a learning process, two different modeling approaches, one computer-based and one non computer-based, were developed. It is believed that is interesting to investigate if learning styles can affect the modeling-based process in science teaching, since is a new approach in science education.

The research was conducted among Cypriot students at the middle school age, since is considered to be the age that students can gain knowledge about models and modeling when they follow a process of developing and refining models about natural phenomena (Louca ; Constantinou, 2002). Also, modeling process as well as the use of computers in science teaching are methods that are not used in science lesson in the Cypriot curriculum. So, I considered it essential to investigate if the use of a computer-based modeling approach would be more beneficial or more complex than a non computer-based approach for students that have no previous experience at this domain.

In addition, the two teaching approaches that are used were chosen to be as familiar as possible with students’ experience, that’s why in the computer-based approach a programming environment based on pictures and not in a complex programming language it is used, while in the non computer-based approach students use simple materials. Moreover, the current study considers constructivism as a central part of science education, so both approaches follow a constructivist approach. Consequently, another part of the current study that it is thought to be remarkable to be investigated is how constructivism is promoted through the two teaching approaches and how beneficial is this for students.

In the present paper a theoretical framework is provided in order to situate the current study in the research of science education through a literature review in the field of models and modeling. Also, the theoretical framework situates the study in the research of technology, since views on how computer-programming tools can be used for the development of models and modeling tools are presented.

Finally, research in psychology is another field that this study can be placed in, since students’ individual needs and how they can affect a modeling-based approach in science are investigated. By taking into consideration the above, the research questions that guided the study are presented. Next, the methodology that was followed in order to answer the research questions is described. Therefore, findings of the current research are presented through which the posed research questions are answered. In conclusion, suggestions for further research in the fields of science education, modeling and technology are pointed out.

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