The learner characteristics, features of desktop 3D virtual reality environments, and college chemistry instruction: A structural equation modeling analysis
Highlights
► Science achievements can be improved at the college level using 3D virtual reality. ► We used statistical technique of structural equation modeling to test the model. ► 3D virtual environments indirectly support the development of spatial ability. ► 3D virtual environments indirectly support the enhancement of self-efficacy levels. ► 3D virtual environments indirectly improve the learning of chemistry concept.
Introduction
Many concepts in the field of science require the understanding of spatial relationships. For example, in the field of medicine, understanding human anatomy in a 3D perspective plays a critical role during surgery. In the field of chemistry, a chemist must visualize the arrangement of atoms in a 3D space to know the shape of molecules. Recent reviews indicate that lack of spatial instruction makes learning of a concept highly challenging for the students, which in turn, adversely affects their achievements (Gilbert and Boutler, 2000, Harle and Towns, 2011). Students’ difficulty in learning chemistry concepts may also influence their self-efficacy (House, 1993, Oliver and Simpson, 1988). Research reports suggest that self-efficacy acts as a catalyst in expediting the learning process (Lapan et al., 1996, Tymms, 1997). Therefore, embedding spatial training in chemistry instruction using desktop 3D virtual reality environments’ features can play a mediating role in enhancing students’ chemistry achievement.
Desktop virtual reality can be defined as a simulation of a real environment or a 3D representation of an abstract concept created using computer technology, wherein users have the ability to interact with the virtual environment in real time using various control devices (Ausburn and Ausburn, 2004, Slater and Usoh, 1994). Users can explore desktop virtual reality applications on a high resolution conventional PC using keys or a mouse for navigation (Simpson, 2003, WhatIs, 2005). With the massive increase in the computer processing power and rapid proliferation of the World Wide Web, many 3D virtual reality technologies are now commonly available (Dickey, 2005, McLellan, 2004). Educators are finding this technology useful to teach many academic concepts (Buchanan, 2003). Studies conducted to test the effectiveness of the 3D virtual reality learning environment have shown positive results. Therefore, researchers are attesting to the learning effectiveness of this environment in fields such as medicine (Riva, 2003), occupational and technical education (Ausburn & Ausburn, 2008), and engineering (Sorby, 2009).
One of the most vital and promising affordances of the virtual reality technologies is to provide spatial instruction. According to Moore (1995) “….by teaching the students to think in 3D using visualization techniques, their spatial cognition can be enhanced” (p. 5). Similarly, Hedberg and Alexander (1994) who emphasized the benefit of using 3D virtual reality environment stated, “As ideas are represented in a three dimensional world, three dimensional thinking can be enhanced, and the mental transformation of information from two to three dimensions can be facilitated” (p. 216). Dalgarno, Hedberg, and Harper (2002) propose that “If 3D environment is a metaphorical representation of abstract ideas, it may be that by developing an integrated database of two dimensional views of a three dimensional model of the concepts, we are better able to make sense of the concepts than through other instructional approaches” (p. 8). As espoused by these scholars, one of the critical features of 3D virtual reality environments is the ability to visually depict and interact with spatial representations of abstract concepts. Therefore, this feature of 3D virtual environments can be useful in providing instruction for developing spatial ability.
Many studies conducted to examine the effectiveness of virtual reality technologies in the field of chemistry have found positive effects (Barnea and Dori, 1999, Pribyl and Bodner, 1987, Urhahne et al., 2009). However, researchers must focus attention on analyzing the role of the mediating variables between the effects of 3D virtual reality technologies based instruction and chemistry learning. According to Waller, Hunt, and Knapp (1998), 3D virtual reality technology researchers should consider exploring perceptual and psychological variables that influence learning. Understanding the role of mediator variables can guide instructional designers, as they create learning tasks in response to the instructional need appropriately, utilizing virtual reality features. Lee, Wong, and Fung (2010) addressed this issue by developing a model of high school, biology students’ learning processes and testing it using structural equation modeling (SEM). Lee et al.’s study represents an important advancement in the field of virtual reality technology, but more research of this type is needed. Therefore, in this paper, we propose a model that will examine the underlying perceptual and psychological variables involved during 3D virtual reality-based instruction for learning chemistry and evaluate the model for an introductory college chemistry class using SEM analyses.
Many researchers have studied the impact of virtual reality technologies in chemical education because it is believed that students can form appropriate mental models of a concept by visualizing and interacting with the representation of the phenomenon (Antonoglou et al., 2011, Chiu and Wu, 2009, Phillips et al., 2010). A major contribution of this research is that it is the most comprehensive investigation to date of chemistry students’ perceptual and psychological processes while interacting with a desktop 3D virtual reality learning environment, encompassing perceived usability of the features of the environment, learners’ sense of presence in the environment, spatial orientation skills, and self-efficacy. In addition, an extensive search of the literature (Merchant, Goetz, & Cifuentes, 2011) did not reveal any studies of 3D virtual environments that used SEM analysis to study chemistry learning in 3D virtual reality environments. The understanding of the perceptual and psychological processes provided by a theoretical model such as the one proposed here may help to guide the design and development of 3D learning environments and the effectiveness of employing them in instruction.
Section snippets
Theoretical framework
The general model of virtual reality proposed by Salzman, Dede, Loftin, and Chen (1999), which highlights the importance of 3D virtual reality features, concept taught, and learners’ characteristics (i.e., learning and interaction experience) for learning outcomes in a virtual environment, served as a starting point for the development of our model. Using Salzman et al.’s (1999) model, Lee et al. (2010) developed a general model examining the underlying psychological processes of reflective
Method
The data presented here were collected as part of a quasi-experimental study evaluating the effects of the 3D virtual environment treatment described in this paper. Only the data from the group that received instruction using Second Life® were relevant for the analyses reported in this study.
Results
The descriptive statistics of all the variables included in the model are presented in Table 3. The fit of the hypothesized model was assessed using the SEM approach. SEM is considered a highly reliable technique for model testing because 1) measurement errors can be controlled using a latent factor model and 2) goodness of fit indices can be obtained to assess the relationship between the variables (Kline, 2010). Data were analyzed using MPlus Version 6.11 (Muthe’n & Muthe’n, 1998–2007). The
Discussion
This study explored the role of psychological and perceptual processes in the learning of chemistry concepts in a 3D virtual reality environment. A theoretical model was developed based on previous research and theory in the area and tested using structural equation modeling. The results supported the hypothesized meditational paths from 3D virtual reality features to the usability and from usability to spatial orientation, self-efficacy, and presence. This study also found statistically
Conclusions
This study supported the hypothesized model for how students interact with a 3D virtual reality environment, which consisted of perceived usability of the features of the environment, sense of presence in the environment, spatial orientation skills, and self-efficacy provided a good account of students’ performance on the chemistry test. However, all data were collected from students of Chem 101 course at the university where the research was conducted. Therefore, the results may not be
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