Re-examining the power of video motion analysis to promote the reading and creating of kinematic graphs

One essential skill that students who learn physics should possess is the ability to create and interpret kinematic (the motion of objects) graphs. Concepts such as, position, velocity, and acceleration belonging to the kinematics - a topic which is a part of the first traditional high-school physics course - are commonly taught based on graphs (Mitnik, et al., 2009). However, it is well documented in the literature that students show difficulties in connecting graphs and physics concepts, as well as graphs and the real world (e.g. McDermott, et al., 1987; Beichner, 1994; Kozhevnikov, et al., 2007; Testa et al., 2002; Eshach, in submission). To address this difficulty, a variety of computational tools were offered and described in the literature. Microcomputer-based labs (MBL) are one such commonly used tool. With the use of a sonic ranger, the distance-versus-time graph of either an object’s motion or the student’s own motion are plotted in real-time on a computer screen (Friedler, Nachmias, & Linn, 1990; Svec, 1999; Thornton & Sokoloff, 1990). Computer simulations are another such tool which has been applied from high-school (Tao, 1997; Andaloro, et al., 1997) to university physics teaching (Schroeder & Moore, 1993). Another tool is computer modelingⁱ. That is, computer software that allows users to create and explore computational models without knowledge of a computer programming language (Araujo et at., 2008). For instance, Araujo et at. (2008) found that undergraduate students improved their performance in interpreting kinematic graphs after using computational modeling activities in Modellus (Teodoro, et al., 1997). Recently, Mitnik, et al. (2009) suggested using collaborative robotic instruction. The authors found that students who participated in such activities achieved a significant increase in their graph interpretation skills. Moreover, the authors found that such activities, when compared with other computer-simulated activity, proved to be almost twice as effective. Finally, the authors also reported that the students that participated in these activities were highly motivated to learn.

In spite of the significant contribution of the above computational tools to students’ graphing skills, I recommend to re-examine the yet unexploited, in my opinion, potential of video analysis. I do not argue that the tools that were briefly described above are not efficient. However, I feel that from a practical point of view we might “lose” many teachers who will not have the time to expose their students to working with the above tools. Moreover, as I will show in this article, video analysis is very easy to use and entails more benefits than the other tools. There is some old research that showed that video analysis is an effective tool (Beichner, 1996). However, it seems that this research did not really succeed in extending its influence even today when there are many technological developments in video analysis technologies. Thus, it is my belief that instead of another research showing how the use of the video analysis activities increases students’ achievement in reading and creating graphs, it is time for a thorough discussion of the power of this tool to enhance graphical thinking. This article aims at initiating this discussion which I hope will raise interest and lead to an increase in the use of video analysis in the physics classes.

The article is organized as follows: section 2 briefly discusses the importance of graphs in science and school science; section 3 describes students' difficulties in reading and creating graphs; and section 4 discuses the benefits of video analysis. To clarify the benefits described in section 4, section 5 provides an example of an activity with video analysis software and explains how these benefits are manifested. Finally, section 6 looks at the future of video analysis and recommends some new directions for development.