Online Scaffolding for Data Modeling in Low-Cost Physical Labs

Online Scaffolding for Data Modeling in Low-Cost Physical Labs

Wing-Kwong Wong (Department of Electronic Engineering, National Yunlin University of Science and Technology, Douliu, Taiwan), Tsung-Kai Chao (Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology, Douliu, Taiwan), Ching-Lung Chang (Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Douliu, Taiwan) and Kai-Ping Chen (Department of Electronic Engineering, National Yunlin University of Science and Technology, Douliu, Taiwan)
Copyright: © 2019 |Pages: 20
DOI: 10.4018/IJDET.2019100101
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There has been an ongoing debate of which physical labs or virtual labs are better. To resolve this issue, a remote lab provides an online lab that can do real experiments to obtain real data from a distant physical lab. Instead of relying on a remote lab, this article suggests that students collect experimental data locally with low-cost data loggers and then model the data with a web tool that provides scaffold support like a remote lab or virtual lab. In this study, 32 tenth-grade students ran physics labs and collected data with NXT, smartphones, and digital video recorder. This study investigates how a web tool assists in data visualization, hypothesis generation, hypothesis testing, and regulation of the discovery process. Results indicated the students became more sensitive in applying strategies of parameter tuning and backtracking. Questionnaire responses indicated the students found such physical labs to be satisfying.
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There has been an on-going debate for years about the relative benefits of physical labs, virtual labs and remote labs (e.g., Ma & Nickerson, 2006; Corter et al., 2007; Sauter et al., 2013). Physical labs provide several benefits to learners. First, when learners observe the real phenomenon, it is an authentic-concrete experience (National Science Teacher Association’s position statement on Second, learners sense certain characteristics such as the roughness or viscosity of a concreate object (Loomis & Lederman, 1986). Third, when learners manipulate concrete material and apparatus, they exercise certain motor skill (Zacharia & Olympiou, 2010). These experiences cannot be obtained from virtual labs.

On the other hand, there are plenty of studies found that students engaged in virtual labs performed better than or similar to students who worked with physical labs (e.g., Farrokhnia & Esmailpour, 2010; Colorado DOHE, 2012; Gorghiu et al., Gorghiu, Alexandrescu, & Borcea, 2009; Zacharia, Loizou, & Papaevripidou, 2012). Brinson (2015), in surveying the literature, found that most studies show equal or greater learning outcome achievement in virtual labs. With simulated data, a virtual lab often provides various support with cognitive tools, which assist students to visualize data, generate and test hypotheses, design experiments, and self-regulate the inquiry process (e.g., Veermans et al., 2000; Reid et al., 2003; Plass et al., 2009).

In virtual labs, as huge as our galaxy and as microscopic as a molecule can be visualized, and simulated data can be collected within a short time, which is very difficult, if not impossible, to achieve in physical labs. With much less cost on equipment and maintenance and more flexibility in organizing learning objectives and contents, virtual labs are becoming a more attractive alternative to educators (e.g., Gomes & Garcia-Zubia, 2007; Babateen, 2011; Liu et al., 2015).

One disadvantage of virtual labs is its lack of authentic data, since all data are simulated from equations and algorithms and so contain no noise. While the data collected from virtual labs are generally noise-free, noise can be introduced to simulated data with specific educational purpose in mind (e.g., Tomandl et al., 2015; Bumbacher et al., 2018). In response to the need for authentic data missing from virtual labs and to reduce the financial burden of maintaining a physical lab, remote labs are created so that students can access online virtual labs to control real apparatus to do experiment and obtain real data in a physical lab at a distant location (e.g., Hossain et al., 2017; Alves et al., 2016; De Jong et al., 2013; Borrero & Marquez, 2012; Elawaday & Tolba, 2009). Hence, students learn about the complications of the real world such as how to deal with measurement errors. A study by Jona et al. (2011) showed that many students preferred the authenticity of real equipment and real data to the simulation provided by a virtual lab. Other advantages of remote labs include safety issue and accessibility to expensive equipment. Labs involving radioactivity and expensive, high-precision equipment can be used without worrying about the safety of students nor about the need for a big budget. Debates on the comparison of physical, virtual, and remote labs can be found in Heradio et al. (2016), Brinson (2015), Ma & Nickerson (2006), Nickerson (2007), Corter et al., (2007), and Wiesner & Lan (2004).

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