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Volume 46 Number 3 2009 51
A CROSS-CASE ANALYSIS OF GENDER ISSUES IN
DESKTOP VIRTUAL REALITY LEARNING
ENVIRONMENTS
Lynna J. Ausburn, Jon Martens, Andre Washington, Debra Steele, and Earlene Washburn Oklahoma State University
Abstract
This study examined gender-related issues in using new desktop virtual reality (VR) technology as a learning tool in career and technical education (CTE). Using relevant literature, theory, and cross-case analysis of data and findings, the study compared and analyzed the outcomes of two recent studies conducted by a research team at Oklahoma State University that addressed gender issues in VR-based training. This cross-case analysis synthesized the results of these two studies to draw conclusions and implications for CTE educators that may assist in developing or implementing successful virtual learning environments for occupational
Dr. Lynna J. Ausburn is an Associate Professor and Program Coordinator for Occupational Education Studies at Oklahoma State University. She can be reached at lynna.ausburn@okstate.edu. Jon Martens is a Graduate Assistant and Doctoral student at Oklahoma State University. He can be reached at jonmartens@mac.com. Andre Washington is a Doctoral student at Oklahoma State University. He can be reached at awashington11@cox.net. Debra Steele is a Doctoral student at Oklahoma State University. She can be reached at dasteel@okstate.edu. Earlene Washburn is a Doctoral student at Oklahoma State University. She can be reached at earlenw@okstate.edu.
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training. The cross-study findings suggested that males and females may be differently affected by VR and that females may be less comfortable, confident, and capable in virtual learning environments, particularly when the environments are highly technical and visually complex. The findings indicate caution in the use of VR in mixed-gender CTE programs, particularly in programs that are heavily female-gendered.
Introduction to Desktop Virtual Reality
To maximize their instructional effectiveness, career and technical education (CTE) programs need to apply effective learning tools in their classrooms and laboratories. Recent literature reviews of published research (c.f., Ausburn & Ausburn, 2004, 2008a, 2008b; Ausburn, Ausburn, Cooper, Kroutter, & Sammons, 2007; Ausburn, Ausburn, Ashton, Braithwaite, Dotterer, Elliott, Fries, Hermes, Reneau, Siling, & Williams, 2006) have consistently documented the effectiveness of virtual reality (VR) as a learning tool in a variety of settings. The research has shown that many educational institutions, industries, and organizations are now turning to VR to provide effective and cost-efficient ways of teaching and career preparation and development. The field most actively reported in the VR literature is medical/dental, where large numbers of published studies have attested to VR’s benefits (Harb, Adams, Dominguez, Smith, & Randall, 2005; Imber, Shapira, Gordon, Judes, & Mitzgar, 2003; Jaffe & Brown, 2000; Jeffries, Woolf, & Linde, 2003; Mantovani, Gaggiolo, Castelnuovo, & Riva, 2003; Moorthy, Smith, Brown, Bann, & Darzi, 2003; Patel, Gallagher, Nicholson, & Cates, 2004; Riva, 2003; Seymour, Gallagher, Rorr, O’Brien, Bansal, & Anderson, 2002; Urbankova & Lichtenthal, 2002; Wilhelm, Ogan, Roehaborn, Caddedder, & Pearle, 2002).
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computers to model real … environments in a three dimensional space that allows people to interact with the environment in a fashion that is both natural and intuitive” (p. 3). Ausburn, Martens, Dotterer, and Calhoun (2009) viewed VR as simulation of locations that model for users the characteristics of the locations and allow them to “visit” and “… experience simulated locations with as much fidelity as possible” (p. 1). Di Blas and Poggi (2007) also emphasized the importance of “presence” in VR, which they identified as engendering in users a sense that they have actually been somewhere rather than just seeing it. In summary, virtual reality (VR) currently refers to a variety of computer-based experiences ranging from fully immersive environments with complex HMD gear and body suits, to realistic PC-based imagery environments. However, in all its forms, VR is basically a way of simulating or replicating a 3D environment through computer-generated imagery and giving the user a powerful sense of “being there,” taking control, and actively interacting with the environment and its contents (Ausburn & Ausburn, 2004, 2008b; Ausburn, Martens, Dotterer, & Calhoun, 2009; Beier, 2004; Brown, 2001). The newest form of VR is called non-immersive or desktop VR. It uses QuickTime, Java, or Flash technology to present high-resolution panoramic imagery on a standard desktop computer. Desktop VR “movies” are created by taking a series of digital still photographic images and then using special VR software to “stitch and blend” the images into a single panoramic scene that the user can “enter” and explore individually and interactively. The user employs a mouse to move and explore within an on-screen virtual environment as if actually moving within a place in the real world. Movements can include rotating the panorama image to simulate physical movements of the body and head, and zooming in and out to simulate movements toward and away from objects or parts of
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the scene. Embedded individual virtual objects can be “picked up,” rotated, and examined as the user chooses, and clickable “hot spots” can also be used to navigate at will (Ausburn & Ausburn, 2008b; Ausburn, Ausburn, Cooper, Kroutter, & Sammons, 2007). What characterizes these desktop VR movies and distinguishes them from traditional video is that the user chooses where, when, and how to move, explore, and examine rather than being controlled by the prior production decisions of a videographer (Ausburn & Ausburn, 2004). What is important about the recent major technical advances in desktop VR for CTE educators is that these technologies now bring the advantages of VR experiences within the fiscal and technical capabilities of most schools and instructors. Because of the recent dramatic improvements in the technical capabilities and features of desktop VR and its accessibility to schools, teachers, and organizations, this technology is emerging as an important new tool for CTE. The new desktop VR is the focus of the research and findings reported in this paper.
Gender and Virtual Environments: Theoretical/Conceptual Framework and Supporting Literature
While VR has repeatedly demonstrated positive learning outcomes, some research has also shown that this effectiveness has not been identical across genders. This research is especially relevant to educational settings that involve training for occupations that are highly gendered, such as the health and medical fields. Educators who use virtual reality in training for gendered occupations need to be cognizant of gender-related issues associated with virtual reality in order to effectively use this new technology. Research has identified several theoretical and conceptual areas that suggest reasons for differential effects of virtual
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Figure 1. Theoretical/conceptual framework for this study. This proposed framework for gender effects in technology- based learning environments applies specifically to virtual reality environments in the context of this study.
In the area of visual-spatial functioning , half a century of research history with paper-and-pencil and performance tests such as the Differential Aptitude Tests (Bennett, Seashore, & Wesman, 1973), the Cards Rotation Test , (Allen, 1974), the Generic Mental Rotation Test (Hakstian & Cattell, 1975), the Primary Mental Abilities- Spatial Relations Test, ( Keyes ,
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1983 ) and the Guilford-Zimmerman (1948) test of spatial orientation have revealed consistent gender differences in skill in mental rotation/manipulation of objects and spatial orientation, with females generally having lower skill and greater difficulty than males in these cognitive tasks. Numerous studies have documented this gender discrepancy. For example, Linn and Peterson (1985) and Voyer, Voyer, and Bryden (1995) both reported higher performance levels by males on mental rotation and spatial visualization tests. Terlecki and Newcombe (2005) claimed that facilitation of computer experience through training may have differential effects on men’s and women’s spatial performance, and reported that men not only perform at higher levels than women on tests of spatial and mental rotation ability, but also tend to have more spatial experiences. Research evidence has also suggested that the long-observed gender gap in mental rotational skills is exaggerated in virtual environments, and that men and women perceive virtual experiences quite differently, with men preferring more interactive environments than women (Space, 2001; University of Washington, 2001). Further, Waller, Knapp, and Hunt (1999) asserted that (a) understanding the spatial characteristics of virtual environments may be more challenging for women than for men, (b) in general, tests of mental visual manipulation and spatial orientation – in which females have typically been less skilled than males – are highly predictive of the ability to acquire accurate spatial information in a virtual environment, (c) gender-related differences in proficiency with a VR navigational interface are particularly important in determining ability to acquire spatial information, and (d) individual differences related to gender and cognitive ability account for more variance in performance on tasks requiring spatial knowledge acquisition from virtual environments than does the actual visual fidelity of the VR representation of the physical
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of males on a variety of performance measures (Waller, Hunt, & Knapp, 1998a, 1998b; Waller, Knapp, & Hunt, 1999). One possible explanation of at least part of observed male advantage in acquiring and using spatial configurational information in complex environments has been proposed by both Hunt and Waller (1999) and by Lawton (1994; Lawton, Charleston, & Zieles, 1996). The explanation proposed by these researchers is based in human wayfinding and navigation theory. This body of theory addresses how individuals know where they are in an environment, where important objects are in relation to them and to each other, and how to move from place to place. The proposed rationale for male advantage in spatial wayfinding is that it can be at least partially attributed to gender differences in specific strategies used during the “wayfinding” process. They proposed that males tend to use wayfinding strategies appropriate for navigation (e.g. bearing to landmarks), while females concentrate on strategies more suitable to tracking and piloting (e.g. describing control points and route cues such as street signs). Several researchers have taken quite different theoretical directions for discussing gender differences in performance in virtual environments. One approach has been to examine male/female differences in technology self-efficacy. Bandura’s well known theory (1994, 1997) defines the self- efficacy construct as belief or confidence in one’s ability to take appropriate actions to successfully perform a certain task. Bandura also asserted that one’s level of self-efficacy, regardless of its truth, could impact actual performance. Some researchers have discussed technology self-efficacy and identified it as an important factor in successfully using electronic technology (e.g. Eastin & La Rose, 2000; Kandies & Stern, 1999). This notion of technology self-efficacy raises the possibility that gender differences in success with learning
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from and in virtual environments may be related to different experiences and perceptions of digital technologies. The technology literature of the 1980s – 2000 period presented many studies showing that attitudes toward technology differed significantly between males and females, reporting that males had greater interest in and knowledge of technology, and that females perceived technology as more difficult and less interesting. Typical of the period were studies by Temple and Lips (1989) that found males generally reported more comfort and confidence with computers, and by Waller, Knapp, and Hunt (1999) that found gender-related differences in prior computer use accounted for considerable variance in performance on tasks requiring gaining spatial knowledge from VR. Also abundant over the last 15 years have been studies documenting female “technophobia” and computer anxiety (e.g. Gilbert, Lee-Kelley, & Barton, 2003; Rainer, Laosethakul, & Astone, 2003; Schumacher & Morahan-Martin, 2001; Todman & Day, 2006; Weil & Rossen, 1995; Whitley Jr., 1996). The American Association of University Women (AAUW) (2000) conducted extensive research examining the technology gap between girls and boys and concluded that teacher attitudes, public media, software manufacturers, and curriculum all had detrimental effects on gender technology self-efficacy deficits and lowered self-confidence of young girls about technology. Bain and Rice (2006-2007) recently reviewed the body of literature on gender and technology and then addressed the question of whether gender differences in perception and use of technology still existed. They found that the majority of females in their study did not perceive computers as being difficult and were using them more than in the past, but did not have the same level of confidence or technology self-efficacy as their male peers. In another recent study, Hogan (2006) documented the persistence of higher levels of technophobia
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masculine/feminine roles. The AAUW (2000) study cited above echoed this contention that the “computer culture has become linked to a characteristically masculine worldview” (p.
- which forces girls and women to make decisions whether to embrace technology or opt for culturally accepted views of themselves as feminine. Gannon (2007) asserted that the language, images, and concepts used to mass-market various forms of technologies to either women or men perpetuate cultural stereotypes of the nature of technology. Similarly, Heeter, Chu, Mishra, Egidio, and Lee (2005) supported the existence of gender differences and cultural stereotyping in gaming preferences. They found that boys liked game features such as weapons, fighting, challenging levels, complex controls, and navigating sharply through the game space using teleporting or warps; while girls liked game features such as story lines, multiple levels to accommodate varying skill levels, adequate instructions, collaboration and chat, and on-screen avatars representing females and appealing pets. The notion of gaming masculination was supported by Hess and Niura (1985). Their study found a significant amount of the computer videogame genre to be focused towards typically “masculine” interests, with emphasis on aggression or violence. This led them to conclude that because of this gender bias, females may be less likely to engage in spatially- related computer activities such as gaming. The relationships among the variables impacting the gender differences observed in research on learning technology have been well documented over more than two decades in the reported literature in educational technology, computing and information sciences, cognitive sciences, and sociology. This research history was synthesized by Cooper (2006) in an extensive review of 20 years of digital divide literature based on gender. In a psychological analysis of these variables, Cooper contended that the gender digital divide in technology
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self-efficacy and performance is fundamentally a problem of computer anxiety rooted in gender socialization interacting with stereotype of computers as toys for boys. For Cooper, this anxiety leads to, and manifests itself in, the differences in computer attitudes and performances that are frequently observed and reported in cross-gender computer studies (2006).
Virtual Reality Studies at Oklahoma State University
As desktop virtual reality began to improve technically and to offer CTE programs and instructors a cost-effective way to bring the benefits of virtual learning environments into educational settings, a research team at Oklahoma State University (OSU) launched a line of inquiry into this dramatic new technology. Prior to the OSU research, published VR studies had focused primarily on complex immersive VR technologies rather than on the more accessible new desktop alternatives (Ausburn & Ausburn, 2004, 2008b), and the few studies that did test desktop VR (e.g. Jeffries, Woolf, & Linde, 2003; LaPoint & Roberts, 2000; McConnas, MacKay, & Pivik, 2002; Scavuzzo & Towbin, 1997; Seth & Smith, 2002) were not focused on potential gender issues with emerging virtual technology. The desktop VR studies at OSU have taken a different approach from the anthropology or descriptive case study methodology that Moore and Kearsley (2005) contended has often defined and limited the usefulness of research on new technologies. Instead, the OSU studies have been quasi- experimental in design and grounded in both classic and contemporary instructional design theories such as media supplantation capabilities (Ausburn & Ausburn, 1978, 2003; Salomon, 1970, 1972), media concreteness theory (Dale, 1954), cognitive load theory (Sweller, 1988; Sweller, 1999; Sweller & Chandler, 1994), self-efficacy theory (Bandura,
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of the case under study. Stake identified collective case study technique as a way to build on an instrumental case by extending it to several cases. In collective case studies, two or more individual cases are selected for study because the researcher believes that examining them together will lead to a better understanding of an even larger collection of cases (2003). The two studies chosen for comparative analysis in the present research has several important similarities. Both addressed (a) the effectiveness of VR as a learning technology, (b) the interaction of gender and VR, and (c) learner outcomes based on both performance and perceptions. Both studies used similar quasi-experimental research designs and similar instrumentation. Comparing the nature of the VEs they presented and the differences in their learner outcomes in a collective instrumental case analysis allowed the researchers to advance understanding of gender differences in VR learning environments and the theoretical foundations of those differences. The methodology of comparing and synthesizing the two instrumental research cases has been termed cross-case analysis (Miles & Huberman, 1994) or cross-case synthesis (Yin, 2009). Miles and Huberman (1994) defined cross-case analysis as searching for patterns, similarities, and differences across cases with similar variables and similar outcome measures. Yin (2009) asserted that cross-case synthesis should involve at least two cases and that the selected cases could be conducted as independent studies authored by different researchers or as predesigned parts of a single study. In either situation, each case should be treated as a separate study in the cross-synthesis. The two previous OSU research studies selected as the source cases for the present cross-case analysis of gender in VR environments represent the former situation. The cross-case analysis conducted using the two OSU studies focused on comparing the goals, methodology,
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instrumentation, VE characteristics, and learner performance outcomes. The two source cases had strong similarities in research goals, instrumentation, and methods, as described below. The nature of the VEs they presented was quite different, as described below. The outcome synthesis for the cross-case comparison focused on (a) identifying key findings across the studies, (b) examining discrepancies in the major findings and their contributing factors, and (c) interpreting the outcomes in terms of relevant theories.
Case/Data Source # The purpose of the first OSU source study in which gender was a variable (Ausburn & Ausburn, 2008a, 2008b) was to compare the effectiveness of desktop VR with traditional still color images typically used in textbooks in presenting a non-technical environment to learners of both genders and two age groups. This quasi-experimental study addressed three aspects of learning outcome by comparing scores of learners who received a desktop VR presentation of the interior rooms of a house with the scores of learners who received still images of the same scene. The subjects were 80 representative adults drawn from the general population who were stratified by gender and age as follows: 20 males aged 18- 35, 20 males aged 36-60, 20 females aged 18-35, and 20 females aged 36-60. A limitation of this study was that no information was collected about the previous computer or VR experience or skill of the subjects and equality of the two experimental groups on these variables could not be verified. However, procedures were used to ensure that equal numbers of subjects from each gender and age group were randomly assigned to receive either desktop VR (e.g. interactive panorama movie with hot spots for navigation) or still imagery (e.g. 8 color photos) presentation of the house rooms. The two presentations were created with the same digital camera using
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( MVR = 10.95; MStill = 9.55; F = 5.51; df = 1,79; p = .02), detail recall ( MVR = 7.08; MStill = 5.35; F = 6.95; df = 1,79; p = .01) , and confidence ( MVR = 3.63; MStill = 3.03; F = 8.54; df = 1,79; p = .005) and for both genders and both age groups. According to Green and Salkind’s criteria (2005), all effect sizes were moderate (.11 < η^2 > .06) using the eta-squared statistic. Also important in this study were its findings related to gender and VR. Unexpectedly, and in contrast to the hypothesized outcomes based on theory and literature, in this familiar and non-technical scenic environment, the females performed significantly better overall than the males with moderate effect size in both scenic orientation ( MFemales = 11.18; MMales = 9.33; F = 9.62; df = 1,79; p = .003; η^2 = .11) and recall of details ( MFemales = 7.13; MMales = 5.30; F = 7.78; df = 1,79; p = .007; η^2 = .09). They also tended to be more confident overall about their understanding of the house scene than the males ( MFemales = 3.48; MMales = 3.18; F = 2.134; df = 1; p = .15) and to benefit more from the VR presentation than the males on both the orientation ( pinteraction = .16) and confidence ( pinteraction = .09) variables. Complete descriptive and ANOVA data were presented by Ausburn & Ausburn (2008b).
Case /Data Source # The unexpected gender-related results of the first study set the stage for a second study by the OSU team. In this study, gender effects in desktop VR were studied in the context of a highly technical environment in a strongly gendered occupation using a mix-method design. The subjects were 42 post-secondary surgical technology students at a large urban technology center. All testing took place in the technology center in a classroom or computer lab. Because of the gendered nature of the surgical technology occupational program, this sample was heavily gender-weighted, with 36
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females (85.7%) and only six males (14.3%). In the quasi- experimental part of the study, students were randomly assigned to receive one of two alternative VR presentations of a set of unfamiliar operating rooms. One VR presentation had only the standard panning and “hot spot” navigation features of desktop VR in which clicking on a “hot” item moved the user to another location or additional views of an item, while the other had an additional visual location and navigation mapping feature to assist users in orienting themselves and locating items relative to themselves. The VR scenes in both presentations were extremely complex visually, with many objects unfamiliar to the students, numerous labels and arrows, and complex navigation tools for moving around and examining objects. This VE was very different from the simple and familiar house environment presented in the first study. Dependent measures for this study were similar to those for the first source study/case reported above and included a similar multiple-choice test of scenic orientation, number of details correctly recalled in one minute, self-reported confidence on a five-point Likert-type scale, and self-reported perceived task difficulty on a five-point scale (not assessed in the first study). Using five-point Likert-type scales, data were also collected on the subjects’ self-reported computer skills, experience with video games, and experience with virtual reality. Level of visualizing skill was also assessed using Successive Perception Test 1 (SPT1), which is a video-based test that requires subjects to view complex figures behind a moving slot and mentally integrate the pieces to form and identify complete patterns. Using SPT1, subjects were classified as either high- or low-visual based on a median split. The two randomly-assigned treatment groups were similar on these skill and experience variables.
