Elsevier

Computers & Education

Volume 59, Issue 2, September 2012, Pages 551-568
Computers & Education

The learner characteristics, features of desktop 3D virtual reality environments, and college chemistry instruction: A structural equation modeling analysis

https://doi.org/10.1016/j.compedu.2012.02.004Get rights and content

Abstract

We examined a model of the impact of a 3D desktop virtual reality environment on the learner characteristics (i.e. perceptual and psychological variables) that can enhance chemistry-related learning achievements in an introductory college chemistry class. The relationships between the 3D virtual reality features and the chemistry learning test as it relates to the selected perceptual (spatial orientation and usability) and psychological (self-efficacy and presence) variables were analyzed using the structural equation modeling approach. The results supported all the hypothesized relationships except one. Usability strongly mediated the relationship between 3D virtual reality features, spatial orientation, self-efficacy, and presence. Spatial orientation and self-efficacy had statistically significant, positive impact on the chemistry learning test. The results indicate that 3D virtual reality-based instruction is effective for enhancing students’ chemistry achievement. Overall, this study contributed a research model that can help increase the effectiveness of desktop virtual reality environments for enhancing spatial ability and science achievement. Moreover, this study provides insight to science educators, instructional designers, and multimedia developers who are interested in designing science-based instruction using instructional design principles.

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

References (79)

  • P.M. Bentler

    EQS: Structural equations program manual

    (1995)
  • G.M. Bodner et al.

    The Purdue visualization of rotations test

    The Chemical Educator

    (1997)
  • M.W. Browne et al.

    Alternative ways of assessing model fit

  • K. Buchanan

    Opportunity knocking: co-opting and games

    ALT-N

    (2003)
  • M. Burgess

    Optimal experience and reading achievement in virtual environments among college level developmental readers

    (2010)
  • M.M. Chemers et al.

    Academic self-efficacy and first-year college student performance and adjustment

    Journal of Educational Psychology

    (2001)
  • M. Chiu et al.

    The roles of multimedia in the teaching and learning of the triplet relationship in chemistry

  • R. Clark

    Reconsidering research on learning from media

    Review of Educational Research

    (1989)
  • B. Dalgarno et al.

    3D environments for spatial learning: the importance of learning task design

  • B. Dalgarno et al.

    The contribution of 3D environments to conceptual understanding

  • B. Dalgarno et al.

    What are the learning affordances of 3-D virtual environments?

    British Journal of Educational Technology

    (2010)
  • F.D. Davis

    Perceived usefulness, perceived ease of use, and user acceptance of information technology

    MIS Quarterly

    (1989)
  • M.D. Dickey

    Three-dimensional virtual worlds and distance learning: two case studies of active worlds as a medium for distance education

    British Journal of Educational Technology

    (2005)
  • R.B. Ekstrom et al.

    Manual for kit of factor referenced cognitive tests

    (1976)
  • J.K. Gilbert et al.

    Developing models in science education

    (2000)
  • J.F. Hair et al.

    Multivariate data analysis

    (2006)
  • R.H. Hall et al.

    Virtual terrorist attack on the computer science building: design and evaluation of a research methodology

    Presence-Connect

    (2004)
  • D.F. Halpern et al.

    Sex difference in visuospatial abilities: more than meets the eye

  • M. Harle et al.

    A review of spatial ability literature, its connection to chemistry, and implications for instruction

    Journal of Chemical Education

    (2011)
  • J. Hedberg et al.

    Virtual reality in education: defining researchable issues

    Educational Media International

    (1994)
  • J.D. House

    Cognitive-motivational predictors of science achievement

    International Journal of Instructional Media

    (1993)
  • L. Hu et al.

    Cutoff criteria for fit indexes in covariance structure analysis. Conventional criteria versus new alternatives

    Structural Equation Modeling: A Multidisciplinary Journal

    (1999)
  • D.L. Jackson

    Revisiting sample size and number of parameter estimates: some support for the N:q hypothesis

    Structural Equation Modeling

    (2003)
  • R.B. Kline

    Principles and practice of structural equation modeling

    (2010)
  • R. Kozma

    Will media influence learning? Reframing the debate

    Educational Technology Research and Development

    (1994)
  • R.T. Lapan et al.

    Efficacy expectations and vocational interests as mediators between sex and choice of math/science college majors: a longitudinal study

    Journal of Vocational Behaviour

    (1996)
  • E.A. Lee et al.

    How does desktop virtual reality enhance learning outcomes? A structural equation modeling approach

    Computers & Education

    (2010)
  • D.F. Lohman

    Spatial abilities as trait, processes, and knowledge

  • K. Mania et al.

    The effects of levels of immersion on memory and presence in virtual environments: a reality centered approach

    CyberPsychology and Behavior

    (2001)
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