Academic journal article Journal of Geoscience Education

Advantages of Computer Simulation in Enhancing Students' Learning about Landform Evolution: A Case Study Using the Grand Canyon

Academic journal article Journal of Geoscience Education

Advantages of Computer Simulation in Enhancing Students' Learning about Landform Evolution: A Case Study Using the Grand Canyon

Article excerpt

INTRODUCTION

Background

Computer simulations are computer-generated, dynamic models of the real world and its processes and often represent theoretical or simplified versions of real-world components, phenomena, or processes (Smetana and Bell, 2012). As such, computer simulations offer an environment for students to explore the phenomena of the real world and better understand the science behind the phenomena. A large body of literature exists on computer simulations in science education. Smetana and Bell (2012) recently provided a comprehensive and critical review.

Ideally, computer simulations are flexible, dynamic, and interactive and thus encourage inquiry-based exploration, in which students draw their own conclusions about scientific concepts and ideas by altering values of different variables and observing their effect (Windschitl and Andre, 1998; de Jong, 2006; Perkins et al., 2012). Most researchers agree that the interactivity of computer simulation and its ability to engage students are the keys to maximizing its advantages in improving student learning (e.g., Tversky et al., 2002; Day, 2012). Interactive computer simulations give students a sense of control and ownership of their exploration and discovery, and thus, it enhances their understanding and retention of information (Podolefsky et al., 2013). These simulations offer the opportunity to re-create and visualize processes/phenomena of the real world that would take too long (e.g., geologic processes) or might be too dangerous or too complicated for a conventional classroom/laboratory setting (Akpan, 2001). Simulations also allow students to focus on the essential aspects of a process or system while eliminating extraneous variables, promoting understanding of the causal relationships between events or variables (de Jong and van Joolingen, 1998). The learning-by-doing approach can also make abstract concepts more concrete (Ramasundarm et al., 2005). The interactive engagement and immediate feedback of simulations allow students to work at their own pace and easily repeat trials and thus promote conceptual reasoning and deeper understanding (Smetana and Bell, 2012). The use of computer-based technology in classrooms is now well established, especially simulation tools that are freely available over the Internet, such as the PhET collection developed by the University of Colorado (https://phet.colorado.edu/).

However, some previous studies also reported mixed or inconclusive results on the effect of simulations on enhancing students' learning (e.g., Anglin et al., 2004; Edsall and Wentz, 2007; Randy and Trundle, 2008; Scalise et al., 2011). Researchers found that traditional methods are just as effective and computer simulations alone are inadequate in helping students understand more-complex ideas because these more-complex simulations often require higher interactivity, which can potentially overwhelm students (Adams et al., 2008; Podolefsky et al., 2010a). Therefore, scaffolding is necessary to help students develop enough background knowledge so that they are not overwhelmed but are adequately equipped and ready to explore the phenomena in question (e.g., Khan, 2011; Schneps et al., 2014). There should be a balance between the level of guidance provided and the flexibility students have to explore on their own because a too strongly guided approach (i.e., step-by-step cookbook) can undermine the potential for exploration, and insufficient guidance can overwhelm students (Adams et al., 2008). Implicit scaffolding features, such as using sliding bars to limit the variable values, restricting the number of variables students can change, and setting default conditions with ideal variable values can keep students from becoming overwhelmed and forestall random interactions that may lead to confusion (Chen, 2010). Smetana and Bell (2012) concluded that "as with any other educational tool, the effectiveness of computer simulations is dependent upon the ways in which they are used" and suggested that "computer simulations are most effective when they (1) are used as supplements; (2) incorporate high-quality support structures; (3) encourage student reflection; and (4) promote cognitive dissonance. …

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