Investigating the Factor that Influences the Implementation of Virtual Reality for Science Learning

doi:10.21203/rs.3.rs-2737402/v1

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Investigating the Factor that Influences the Implementation of Virtual Reality for Science Learning

https://doi.org/10.21203/rs.3.rs-2737402/v1

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published 29 Mar, 2024

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Intensively developed virtual reality (VR) has great potential in education and can be reliably integrated into the classroom, fostering authenticity to facilitate the rapid developments in science. This research aims to investigate the factor that influence the implementation of VR and the correlation between each dimension of the technology acceptance model that can lead to intentions to use VR. The structural equation modeling is performed that was tested on participants of preservice teachers who performed simulated science explorations in the weightlessness concept. The results show that most participants believe that VR is useful in many educational contexts, including immersion, authentic learning, motivation, and engagement. Moreover, the predicted model has good explanatory power to predict intention to use VR in the classroom (R² = 64.7%), influenced by usefulness, enjoyment, and absence of cybersickness. Educators and researchers should consider avoiding the 360-degree VR beyond the advantages of ease and economics, then adopt more comfortable and accessible graphics-based VR for implementation in the classroom, as well as the suitability of content for students to avoid any cybersickness.

360-degree VR

graphics-based VR

structural equation modeling

technology acceptance model

Meta has made the headlines of newspapers since the founder of Facebook changed Facebook’s corporate name to “Meta” and announced its new platform at the end of 2021, which potentially provides an infinite landscape of virtual worlds limited only by imagination, namely, the metaverse (Clark, 2021; Metz, 2021). Virtual reality (VR) is the closest term to the metaverse concept discussed by many technologists (Ratan & Lei, 2021; Sparkes, 2021). Many previous studies have revealed that VR, has massive potential for the educational field, for instance, learning benefits are shown in cognitive studies, especially where highly complex or conceptual problems require spatial understanding and visualization that often occur in teaching scientific topics such as biology or physics (Hamilton et al., 2021). VR can also turn abstract concepts into experienceable phenomena and present exciting opportunities to transform science education and public outreach practices (Kersting et al., 2021).

Another advantage of VR in the teaching-learning process is that it offers students the capability of learning authentic concepts. In science learning, for example, in physics and astronomy, learning is no longer restricted to imagination; students can explore the universe in a virtual world that resembles the real world (Kersting et al., 2021). Currently, fostering authenticity in the classroom is one of the greatest challenges faced by educators, instructors, and policymakers (Bhagat & Huang, 2018). Moreover, authentic learning also helps students immerse themselves in the learning environment to gain knowledge and skills through their own experiences (Chiu et al., 2018). Thus, authentic learning can be bridged using VR technology.

Although VR has shown great potential for modernization (Atli et al., 2021), active learning (Sams & Leither, 2021), better learning motivation, learning outcomes, and positive impacts on students’ achievement scores (Liou & Chang, 2018), it is still very rarely applied in the classroom and continues to face challenges that need to be overcome to ensure feasibility for schools (Holly et al., 2021). As classroom leaders, teachers may be wary of issues that circumvent wide implementation of VR, such as user complexity compared to desktops (Holly et al., 2021) and cybersickness (Sagnier et al., 2020).

Many researchers focus on VR research regarding its benefits for students, and the results are positive, indicating that VR can be widely used as a medium to increase motivation (Harris & Reid, 2005), presence (Selzer et al., 2019), engagement (Allcoat & Mühlenen, 2018), and learning outcomes (Merchant et al., 2014). However, few studies have focused on teachers' views, even though teachers have an enormous role in implementing technology in the classroom. Jones (2004) has reported that teachers’ lack of technical support, confidence, and realization of the advantages of using technology in their teaching has become a barrier to effective integration of technology in teaching and learning.

Therefore, identifying factor of teachers' implementation of this technology needs to be correctly ascertained. To identify teachers' views about VR implementation to support science teaching in the classroom, this research aims to investigate the factor that can lead to intention to use VR.

2.1. Virtual Reality in Science Concept

Explaining concepts without experiencing phenomena leads to students' images of the scientific or technological environments being superficial, unreal, and even incorrect (Scher & Oren, 2006). This problem can be overcome by using scientific demonstrations (Ahtee et al., 2011) or study tours to science and technology facilities (Scher & Oren, 2006). Currently, both approaches can be implemented in virtual reality experiences.

For instance, Mission: International Space Station (ISS), a virtual reality simulation, offers opportunities for students to not only learn about the space station but also to experience the conditions (Magnopus, 2019). Mission: ISS in VR (Meta Quest) is similar to ISS's actual conditions in real life; thus, students can explore many concepts. Students can experience almost the same conditions as astronauts working in space stations, even [feeling] touching a celestial object that can create physical immersion within an immersive environment (Suh & Prophet, 2018). In addition, the experience of scientific concepts related to astronomy can also be experienced using low-cost technology such as Cardboard VR (Bedregal-Alpaca et al., 2020; Calderon & Rivera, 2017; Sharhorodska & Iquira, 2019).

ISS represents the largest scientific and technological cooperative program in history, drawing on the resources of several nations (DeLucas, 1996). ISS is designed as a multifunctional research platform for conducting a wide range of physical and biological science investigations (Castro et al., 2004). It is designed to serve as a research facility for low-gravity experimentation in fundamental science and technology development. The acceleration environment on the station ranges from transient episodes of 0.01 g to quasi-steady levels below one-millionth of 1 g (Thirsk et al., 2009). As a rare condition simulated in this space station, this acceleration scenario provides the opportunity to perform high-value scientific research in a microgravity environment (DeLucas, 1996).

2.2. Teachers' Acceptance of Virtual Reality

The technology acceptance model (TAM) was developed by Davis (1989) as an adaptation of the theory of reasoned action that explains the main determinants of technology acceptance that lead to behavioral intention. The TAM framework is widely used for different purposes and technology. Consequently, many additional dimensions have been integrated into TAM; each improvement aims to increase the model’s predictive power (Chow et al., 2012).

The primary dimension of the TAM framework in this research consists of belief (perceived usefulness, perceived ease of use, and perceived enjoyment), behavioral intention (intention to use and intention to purchase), curiosity, attitude, and cybersickness. Table 1 presents each criterion as a main feature of TAM used in this study.

Table 1

The TAM framework in this study.
Criteria	Operational Definition
Perceived usefulness (PU)	The tendency to use or not use an application to the extent participants believe it will help them perform their job better (Davis, 1989).
Perceived ease of use (PEU)	The degree to which participants believe that using a particular system would be free of effort (Davis, 1989).
Perceived enjoyment (PE)	The extent to which the activity of using the technology is perceived to be enjoyable in its own right (Davis et al., 1992).
Intention to use (IU)	The degree to which a person has formulated conscious plans to use or not use some specified future technology (Venkatesh et al., 2008).
Intention to purchase (IP)	The degree to which a person has formulated conscious plans to purchase or not purchase some specified future technology (Venkatesh et al., 2008).
Curiosity I (C)	The desire to seek and obtain new information (Manis & Choi, 2019).
Usage attitude (UA)	The degree to which users expect the use of the VR device to be positive (Lee et al., 2019).
Cybersickness (CS)	The negative side effects because of a virtual environment (Sagnier et al., 2020).

First, beliefs are very influential to the teachers’ daily pedagogical decisions and serve as a primary source of their approach to pedagogy and student learning (Cross, 2009). The belief dimension in this research consists of perceived usefulness, ease of use, and enjoyment (Davis et al., 1992). According to Davis (1989), the “perceived” dimension is theorized from self-efficacy beliefs by Bandura to function as proximal determinants of behavior (p. 321). In this study, belief is used to predict behavior intention to implement VR in the classroom. Central beliefs are developed through experience, and therefore, reflection upon that experience is critical to belief change that can occur gradually in an incremental process; however, for an individual, belief change involves deserting the familiar for the unknown (Grootenboer, 2008).

Second, according to Manis and Choi (2019), behavioral intention theoretically represents an individual's consciously formulated plan to engage in a particular behavior and has a situationally specific dependence on a given research topic (p. 506), for example, intention to use (Davis et al., 1992) and intention to purchase (Manis & Choi, 2019). Moreover, the willingness of preservice teachers to use information technologies in their future teaching is associated with the concept of intention (Baydas & Goktas, 2016; Yildiz Durak, 2019). Studies have indicated that when teachers believe technology uses are valuable, they are more likely to incorporate those uses into their practices (Ottenbreit-Leftwich et al., 2010).

Third, of the external variables impacting perceived ease of use, curiosity emerges as the most powerful predictor relative to the other external variables; these findings represent the first attempt to integrate the TAM literature's inherent curiosity literature (Manis & Choi, 2019). Fourth, attitude (usage attitude), refers to the use of information technologies by preservice teachers in their future teaching and is affected by their prior experiences of these technologies and their attitudes toward intention in the future (Baydas & Goktas, 2016; Yildiz Durak, 2019; Zhou et al., 2012).

Finally, cybersickness has been discussed in VR studies. Much research has proven that cybersickness cannot be avoided in VR and that it negatively impacts intention to use (Sagnier et al., 2020) and may prevent using a particular technology again in the future (Diels & Howarth, 2013). These symptoms indicate the presence of motion sickness, but researchers have a different name to represent those symptoms (Rebenitsch & Owen, 2016); consistently, cybersickness (Sagnier et al., 2020) is used in the current research.

Therefore, the teachers' acceptance data for both VR intervention were analyzed to investigate possible correlations between the dimensions that led to VR intention, as shown in Fig. 1.

In summary, teachers must be pedagogically and technologically ready to integrate technology into instruction to support K-12 student-centered learning (Li et al., 2019). As new technologies emerge, teachers need training to ensure they can integrate technology into instruction in meaningful ways to support K-12 learning (Casey et al., 2021).

2.3. Virtual Reality Device

The VR experience consists of two related elements: devices and content. On the one hand, devices improve the VR experience with at least three main features (i.e., stereoscopic vision, head-mounted displays, and head tracking technology (Slater & Sanchez-Vives, 2016)). On the other hand, the content can be displayed in VR and generate the experience when using a VR device (i.e., computer graphics generated images (Slater & Sanchez-Vives, 2016)). The combination of these devices and content can generate the anticipated VR experience.

Several studies have categorized devices, referring to Cardboard VR as the low-end VR and Meta Quest (and related technology, such as HTC VIVE and Meta Rift) as the high-end VR (Elmqaddem, 2019; Selzer et al., 2019). Although Cardboard VR is far less capable than high-end VR devices, the extremely low cost shifted the VR market from the realm of technology enthusiasts to the common person (Boyles, 2017).

However, there is some discussion about whether 360-degree video, as has been used in some of the research and the classroom, is “really” VR. For example, Will Smith (2015) argued that systems such as 360-degree video, as might be seen through Cardboard VR, should not be called “VR,” the main argument being that the relationship between head moves and image changes is more likely to lead to simulator sickness in 360-degree video. However, mainstream media are already referring to 360-degree video as VR. The most detrimental implication is labeling “virtual reality” as poor because people have had disappointing experiences in 360-degree VR (Slater & Sanchez-Vives, 2016).

2.3.1. Graphics-based VR and 360-degree VR

The distinction between 360-degree VR and VR is quite complicated because many researchers use the 360-degree feature by using Cardboard and refer to it as VR (Calderon & Rivera, 2017; Fluke & Barnes, 2018). However, according to several studies (Arino et al., 2014; Slater, 2018; Slater & Sanchez-Vives, 2016; Suh & Prophet, 2018), VR refers to the main functions of devices that have specific main features (Table 2).

Table 2

The Main Features of Virtual Reality
Main feature	Definition	Reference
Stereoscopic	The two small displays are placed in front of the eyes and enable the user to see the images.	Arino et al. (2014); Slater (2018); Slater & Sanchez-Vives (2016)
Head-mounted display (HMD)	The display is mounted on the user’s head and delivers stereoscopic images.	Slater (2018); Slater & Sanchez-Vives (2016)
Head tracking	The image has the correct perspective computed for the participant's head position, direction, and orientation.	Slater (2018); Slater & Sanchez-Vives (2016); Suh & Prophet (2018)
Computer graphics generated images	The image-based computer model describes all the geometry, material properties, lighting, and dynamics of objects in the scene.	Slater & Sanchez-Vives (2016)
Hand tracking	Users are provided with the means to interact physically with virtual objects.	Slater (2018); Suh & Prophet (2018)

According to Slater and Sanchez-Vives (2016), the main differentiating feature of systems considered “really” VR and 360-degree VR is computer-generated images. On the one hand, a computer model allows participants to change their point of view to anywhere within the scene. On the other hand, 360-degree VR cannot allow participants the full range of movement through the scene (p. 35).

Moreover, graphics-based VR has haptic feedback because of the hand tracking feature. The emulation of haptic feedback is an important aspect of VR simulation (Våpenstad et al., 2013). The sensation of touching a virtual object to feel its texture has enabled users to examine, search for, and manipulate objects visually (Huang & Liao, 2017); therefore, physical and mental engagement is created within an immersive environment (Suh & Prophet, 2018). Haptic imagery is a feature provided for participants by systems that are considered “really” VR (Våpenstad et al., 2013; Wang et al., 2019).

Although several researchers initiated the Cardboard version based on 360-degree video as immersive VR (Calderon & Rivera, 2017; Fluke & Barnes, 2018), the most appropriate terminology proposed by Wagler and Hanus (2018) used immersive 360-degree video using a VR headset as the term to distinguish both categories. Furthermore, Slater and Sanchez-Vives (2016) also distinguished the possibility of two categories (i.e., graphics-based VR and 360-degree VR) and concluded that computer graphics-based VR and 360-degree VR are different possibilities within the domain of “virtual reality”. The correlation between a device and its content for both types of VR is presented in Fig. 2. In the current study, according to relevant research (Slater & Sanchez-Vives, 2016; Wagler & Hanus, 2018), the distinction between graphics-based VR and 360-degree VR is used to determine the appropriate approach for science education instruction in a case study of astronomy concepts to explore ISS.

3.1. Participants

The sample consisted of 71 students (25 males and 46 females) who were Taiwanese preservice teachers. Participants were required to provide informed consent to participate in this study, which was categorized by gender (25 males and 46 females), level (8 freshmen, 25 sophomores, 15 juniors, 10 seniors, and 13 graduate students), and VR use (44 participants never used VR, and 27 participants used VR less than an hour).

However, after checking the validity of the participants' data, nine participants were excluded due to the outlier data. In particular, participants in this research are teachers college students in Taiwanese university which identified as preservice teachers, who will become future teachers (Trumper, 2001; Yildiz Durak, 2019). DiPaulo (2022) identified preservice teachers as undergraduate students enrolled at a university that is preparing to teach students in both public and private schools. Other researchers, such as Romanowski (2021), also identified preservice teachers as education students in one university.

3.2. Procedure

The structural equation modeling (SEM) is performed that was tested on participants of preservice teachers who performed simulated science explorations in the weightlessness concept. First, participants willing to join the study were asked to fill out letters of consent, agreeing to voluntary participation and anonymous use of their information for research; Before the intervention, the participants were then selected according to the criteria and received the invitation to do VR experience is specific schedule; the variation of students' technology savvy was very diverse and random. Purposive random sampling was performed to divide the participants into two experience (360-degree VR (E1) and graphics-based VR(E2)) to ensure the diversity of VR acceptance so that both experiences had the same initial condition.

Second, two VR interventions were prepared for participants. In the first experience, the virtual simulation implemented Cardboard and was modified from a 360-degree video of the Home – VR Spacewalk developed by BBC Media Applications Technologies (2017). The second experience implemented Meta Quest and was entitled Mission: ISS and was developed by Magnopus (2019). To avoid motion sickness, a mat on the floor was used with a fan in the vicinity to create airflow so that participants could detect directions (ThrillSeeker, 2020), as shown in Fig. 3.

It was also necessary to reduce the time spent using the virtual helmet due to the dizziness experienced by students, especially for the experiment involving Cardboard (Bedregal-Alpaca et al., 2020). In this experiment, participants experience 12 minutes for 360-degree VR and approximately 12–15 minutes for graphics-based VR.

Moreover, virtual environments typically cannot provide all information but give users insufficient information, especially in the learning process. Nevertheless, text or audio can fill the information gap to build an information-rich virtual environment (Bowman et al., 1999; Chen et al., 2007). Thus, audio was added to 360-degree VR, and for graphics-based VR, the instructor assisted participants in translating the audio into the first language of participants since some simulations only provide the English language.

Finally, after the VR intervention, participants completed teachers’ technology acceptance model and open-ended questions. The paper-based questionnaire and open-ended questions were conducted to assess teachers’ perceptions and verify teacher engagement.

3.3. Questionnaire

The main reason for the TAM framework in this study was supported by many studies (Akar, 2019; Camilleri, 2014; Teo, 2009) that have concluded that TAM can be the best measurement of a technology implementation, extending to attitudes toward adaptation and change in the classroom. Furthermore, the greater the TAM scores of teachers, the greater the possibility that some kind of technology can be applied in the classroom. Therefore, the questionnaire in the study was adapted from Manis & Choi (2019), Sagnier et al. (2020), and Lee et al. (2019) regarding TAM specialized in VR (Appendix A).

The open-ended questions were translated from previous research about attitudes toward using VR hardware by Lee et al. (2019). The open-ended questions for teachers’ attitudes were almost identical among the five items and designed to trigger teachers to be more expressive about their experience. Then, all open-ended answers were collected and coded based on the four themes related to teachers' acceptance in quantitative data to support the quantitative analysis, including (1) perceived usefulness (theme 1), perceived ease of use (theme 2), perceived enjoyment (theme 3), and intention to use (theme 4).

4.1. Validity

Validity and reliability are important components of quantitative measurement (Jordan & Hoefer, 2001). The validity and reliability of the data were measured using principal component factor loading with varimax rotation that aims to uncover the latent structure (dimensions) of a set of variables and reduces the attribute space from a larger number of variables to a smaller number of factors (Garson, 2013). Cronbach’s alpha, composite reliability, and the average variance extracted (AVE) were also measured with the minimum value according to Fornell & Larcker (1981).

After the Kaiser-Meyer-Olkin (KMO) value reaches the standard (KMO = 0.885), several tests were performed for content validity, convergent validity, and discriminant validity to assess the overall validity in the SEM approach. First, content validity was achieved using previously tested scales and standard procedures for scale adaptation (Lee et al., 2019; Manis & Choi, 2019; Sagnier et al., 2020). Second, convergent validity was assessed by calculating Cronbach’s alpha, composite reliability, and AVE values, which were greater than the minimum values (Fornell & Larcker, 1981), as presented in Table 5.

Table 5

Validity of Constructs
Construct	Items	Factor loading (≥ 0.7, min 0.5)	Cronbach’s alpha (≥ 0.7)	Composite reliability (≥ 0.7)	AVE (> 0.5)
PU	PU1	0.83	0.93	0.95	0.79
	PU2	0.90
	PU3	0.93
	PU4	0.88
	PU5	0.89
PEU	PEU1	0.91	0.90	0.94	0.83
	PEU2	0.90
	PEU5	0.93
PE	PE1	0.94	0.95	0.97	0.88
	PE2	0.93
	PE3	0.93
	PE4	0.94
IU	IU1	0.93	0.96	0.97	0.92
	IU2	0.98
	IU3	0.97
UA	UA1	0.93	0.91	0.94	0.84
	UA2	0.93
	UA3	0.89
CS	CS2	0.30*	0.87	0.88	0.40*
	CS4	0.67
	CS5	0.51
	CS6	0.82
	CS8	0.47*
	CS9	0.80
	CS10	0.57
	CS11	0.84
	CS12	0.56
	CS13	0.32*
	CS14	0.80
	CS15	0.60
Note: *Exclusion

Several items with factor loadings of less than 0.5 were deleted (i.e., curiosity, intention to purchase). However, cybersickness items with validity values of less than 0.2 were deleted (i.e., CS1, CS3, CS7), while cybersickness items with factor loadings of more than 0.3 were retained (see Sagnier et al. (2020)). Cybersickness items were retained because previous studies (Israel et al., 2019; Sagnier et al., 2020) revealed that it has a significant influence on VR technology, although it has an improper scale and will be discussed in the limitation section.

Third, the first discriminant validity test was implemented with the Fornell-Larcker criterion. For satisfactory discriminant validity, the square roots of the AVE values (in bold) should be significantly higher than the off-diagonal elements in the corresponding rows and columns (Fornell & Larcker, 1981). The results of the Fornell-Larcker criterion were satisfied because the square roots of the AVE values were greater than other correlations (Appendix G). The second discriminant validity test was the heterotrait–monotrait (HTMT). The HTMT ratio of correlations evaluates the average of the heterotrait–monotrait ratio, which must be below the threshold of 0.85 or 0.90 (Henseler et al., 2015). In all constructs, the HTMT correlation values in the data reach the standard (Appendix G).

4.2. Hypothesis Testing

The proposed research model was tested with SmartPLS 3.3.5 (Ringle et al., 2015). A complete bootstrapping procedure with bias-corrected and accelerated (BCa) bootstrap was implemented, and 5000 subsamples were used to estimate path significance. Since the intention to purchase and curiosity were not valid, the dimensions and hypotheses related to the dimensions were excluded from the modeling. Figure 4 shows the results of the structural model. The model explained 30.8% of the variance in perceived usefulness of VR, 71.2% of the variance in usage attitude, 64.7% of the variance in intention to use VR, and 33.9% of the variance in perceived enjoyment. If the research model reaches more than 50% of the total variance, it implies that the model has a good level of predictability and explanatory power (Chin, 1998).

Based on the R² value (also called the coefficient of determination), perceived enjoyment has a low-level prediction, where 33.9% of the variation in the output variable (i.e., perceived enjoyment) is explained by the input variable (i.e., perceived ease of use). This finding indicates that perceived ease of use does not mean teachers have perceived enjoyment of VR in the classroom (only a 0.339 possibility to have enjoyment). Regarding behavioral intention to use VR, a 64.7% probability of true intention can be predicted by cybersickness, perceived enjoyment, and perceived usefulness. The hypotheses revealed from the structural model are presented in Table 6.

Table 6

Hypotheses testing
Hypothesis	Path	Path coefficient	t	p-value	Supported or not
H_1a	CS → IU	-0.19	2.11*	0.035	Yes
H_1b	CS → PU	-0.34	3.27***	0.001	Yes
H_2a	PEU → IU	0.12	1.02	0.308	No
H_2b	PEU → PE	0.58	7.76***	0.000	Yes
H_2c	PEU → PU	0.37	3.40***	0.001	Yes
H_2d	PEU → UA	0.13	1.92	0.055	No
H_3a	PE → IU	0.27	2.35*	0.019	Yes
H_3b	PE → UA	0.39	4.16***	0.000	Yes
H_4a	PU → IU	0.43	3.86***	0.000	Yes
H_4b	PU → UA	0.45	5.38***	0.000	Yes
H₅	UA → IU	-0.02	0.15	0.884	No
Note. p < 0.05; p < 0.01; **p < 0.001

The results reveal that cybersickness is negatively correlated with intention to use (p = 0.035) and perceived usefulness (p = 0.001); thus, H_1a and H_1b were supported, similar to Sagnier et al. (2020). Importantly, teaching aids for students should not induce dizziness, and careful consideration of cybersickness for VR tools is necessary to promote widespread use as pedagogical tools (Detyna & Kadiri, 2020).

Perceived ease of use impacts perceived enjoyment and usefulness, similar to previous research (Manis & Choi, 2019); thus, H_2b and H_2c were supported. However, perceived ease of use has no impact on usage attitude and intention to use (H_2a and H_2d were rejected), although other studies reveal a correlation with VR intention (Manis & Choi, 2019; Moreira et al., 2021). Moreover, perceived enjoyment positively correlates with the intention to use (H_3a). In addition, perceived enjoyment also positively correlates with usage attitude (H_3b), similar to previous research (Manis & Choi, 2019; Moreira et al., 2021).

According to Davis (1989), some theories argue that beliefs influence behavior intention only via their indirect influence of attitude, while other views stated that belief and attitude act as co-determinants of behavioral intention. However, in the current research, behavioral intention is apparently influenced by belief (PEU, PE, and PU) only via the indirect influence of attitude, whereas the usage attitude has no direct impact on intention to use (H₅ is rejected), although other studies indicate a co-determinant mechanism (Manis & Choi, 2019; Moreira et al., 2021). Furthermore, perceived usefulness correlates with the intention to use (H_4a) and usage attitude (H_4b) in the current research, similar to other research (Moreira et al., 2021; Sagnier et al., 2020).

4.3. Open-ended Question

Regarding perceived usefulness (Theme 1) of VR in 360-degree VR (E1) and Graphics-based VR (E2), preservice teachers expressed a positive attitude toward the usefulness, as shown in the opinions of some participants (P).

…can go through VR to places you've never been before (E1, P8).

Makes people feel immersive (E1, P16).

A novel experience that brings the world into the lens (E1, P21).

… the way you operate it is also interesting (E2, P11).

It's very immersive and authentic (E2, P15).

Teachers can experience places that they have never visited before (P8) and feel that they are in a virtual environment, also known as being immersed (Tibaldi et al., 2020; Tomlinson et al., 2019), as stated by P16 and P15. In addition, participants revealed that VR is a novel experience that brings the world into a lens (P21). A similar opinion is stated by Alfalah (2018): “VR is considered a novel option to add value to the learning journey” (p. 2633). Moreover, P15 was also mentioned VR as an authentic experience; this observation is similar to the findings of Yang and Goh (2022), who argued VR could simulate a realistic environment where the learners could perform authentic learning activities, for example, for medical, robotics, and other fields where practical knowledge and training are necessary. In addition, P11 on E2 stated that the mode of operation was interesting; it came from haptic feedback – a feature to experience the sensation of touch while in the virtual world (Huang & Liao, 2017).

In terms of perceived enjoyment (Theme 2), teachers experience discomfort problems especially in 360-degree VR, as shown in the opinions of some participants.

After watching a 10-minute video, my eyes find it difficult to focus (E1, P24).

There is only a very low level of discomfort (E2, P18).

P24 which doing E1 revealed that discomfort appears after watching a 10-minute video; the future study is needed consider the limit time for using 360-degree VR for science content to provide an optimal experience in science classes. Contrary with 360-degree VR, when experiencing graphics-based VR participants perceived more enjoyment as shown in the opinion of some participants; only a few expressed their discomfort and said that they were slightly dizzy or had a low level of discomfort (P18).

One of the remaining weaknesses of E2 is in term of ease of use (Theme 3), while participants in E1 completely consider it is easy, as shown of some participants opinion.

Although it was a little confusing at first how to use it, it was finally completed (E2, P13).

The first time you use the device, you do not know much about it, and you need someone to assist you (E2, P25).

According to previous studies, graphics-based VR devices (e.g., Meta Quest) involved complex procedures in order to be used in the classroom, similar to the opinion of P13; thus, a teaching assistant was recruited to support the participants in this experience. According to Fransson et al. (2020), some teachers even warned about a “backlash when implementing VR technology if it was too complicated to use; thus, student support and ideally two teachers in the classroom is recommended” (p. 3394). The use of assistants who helped to process the VR intervention in this study was proven to positively impact participant attitudes regarding the ease of use of VR devices (P25). This process serves as a recommendation so that either students or assistant teachers can assist educators in implementing VR in the classroom.

In terms of intention to use (Theme 4), experiencing either 360-degree VR or Graphics-based VR showed their intention to use VR in their teaching process, as shown in the opinion of some participants.

… used in teaching students; must be very interesting (E1, P2).

Novelty increases students' motivation to learn (E1, P3).

It can be applied to teaching (E2, P9).

Suitable for teaching (E2, P17).

You can learn by doing it (E2, P20).

Some of the participants revealed that using VR in their teaching will be very interesting (P2), it increases students' motivation to learn (P3), it can be helpful for both teachers and learners (P8). The argument of preservice teachers is also similar to previous research that reveals that VR as a tool makes the lesson more interesting (Kamińska et al., 2019), it can promote students’ motivation (Ho et al., 2019), as well as it helps both teachers and students as a visualization aid for complicated three-dimensional objects (Song & Lee, 2002)

Specifically in graphics-based VR, some participants stated that VR could be applied (P9) and is suitable (P17) for the teaching process. There are significant potential benefits of using VR technology to improve learning outcomes and students’ motivation, overcome school-based and test anxiety, influence empathy, and ensure students focus on teaching content (Stojšić et al., 2019). A participant also stated that VR could propose “learn by doing” (P20). In addition, graphics-based VR could potentially develop into a hands-on activity and learning by doing, which cannot be developed in 360-degree VR. Moreover, Radianti et al. (2020) believed that the true potential of VR did not lie in better teaching of declarative knowledge but in offering opportunities to ‘‘learn by doing,’’ which is often very difficult to implement in traditional lectures (p. 23).

The study accomplishes determining the influence of VR experiences perceived by preservice teachers and shows that these influential insights can lead to intention to use VR in their teaching processes. The findings were achieved by examining empirically in incorporating technology acceptance model elements into a predictive model to explain VR acceptance in the classroom setting.

The results presented in this research reveal that highly perceived usefulness, levels of enjoyment, and the absence of any cybersickness for teachers will generate more intention to use VR. This is consistent with previous research that states perceived usefulness is a key variable in the intention to use innovative devices such as VR (Moreira et al., 2021; Sagnier et al., 2020). Perceived usefulness also provides evidence to support a predictive role in intention to adopt VR applications in education, similar with previous study in university to quickly implement digital pedagogy applications (Moreira et al., 2021).

The qualitative also reveal that most participants believe that VR is useful in many educational contexts, including immersion, authentic learning, motivation, and engagement. Participants also state VR is a novel experience, but some discomfort appears after watching a 10-minute in 360-degree VR which not recommended for further study. In addition, participants proposed that VR could propose “learn by doing” which graphics-based VR could potentially develop hands-on activity and learning by doing.

The current study's findings also reveal that the ease of use of VR has no significant effect on teachers’ attitudes and intention to use VR, although other studies reveal a significant effect (Manis & Choi, 2019; Moreira et al., 2021). Two factors could explain these phenomena. First, based on the analysis, the framework of VR research conducted by other studies, such as the study of Manis and Choi (2019) using only a prior condition approach (participants’ past use), reveals a limitation because acceptance was only measured without defining the type of VR implemented. Thus, all participants were subjected to a VR intervention with different VR devices in the current research. Second, in the current research, the differences between the two experiments (ranging from the low-end to the high-end systems to represent the current market offerings) in terms of ease of use are quite significant, making the ease-of-use factor incapable of being used as a predictor in implementing VR in the classroom. The VR research with different VR devices (i.e., head-mounted display (HMD) and the Cave Automatic Virtual Environment (CAVE)) also reveals that perceived ease of use does not correlate with the intention to use (Sagnier et al., 2020).

Finally, according to Davis (1989), attitude does not fully have an immediate effect of perceived usefulness and ease of use on behavior intention (e.g., intention to use). It should be emphasized that PU and PEU are human subjective appraisals of performance and do not necessarily reflect objective reality. However, if technology objectively improves performance and users do not perceive it as useful, they are unlikely to use it. This rationale explains why teachers' behavioral intention is a necessary factor to implement VR in the classroom regardless of the need to perform empirical research on student performance.

The cybersickness questionnaire in this research is the same as that used in previous research, which is not yet appropriate (Sagnier et al., 2020). Future research is needed to identify alternative procedures for measuring cybersickness, for example, using brain waves that can be measured using an electroencephalogram (EEG) and providing empirical data on which part of VR content can trigger cybersickness.

Theoretically, this research is the first study that focuses on how VR can have implications for VR implementation in the classroom since the subject is future teachers and their behavioral intention to use VR. Previous studies on VR adoption mainly focused on specific VR in different fields, for example, VR for manufacturing processes (H. Yang & Han, 2021) and VR for training (e.g., flight training) (Fussell & Truong, 2021). No studies have tested the acceptance model on preservice teachers or inservice teachers who are responsible for implementing technology in the classroom. Second, the mixed method, consisting of structural equation model and qualitative study can provide a holistic perspective of the VR experience. This study is the first empirical study to investigate the strengths and weaknesses of low-end and high-end VR devices available in the current market using the same research framework and providing a new empirically derived research model that has good explanatory power to predict behavioral intention (R² = 64.7%).

Furthermore, since VR is currently more comfortable and accessible (Elmqaddem, 2019), using graphics-based VR is recommended for implementation in the classroom. To provide a case comparison, in the current research, a good quality Cardboard VR was purchased for approximately $36 per device to facilitate 29 participants in a class ($1044 in total); at the same price, 3 devices of graphics-based VR can be purchased for the whole class ($299 for each). Regarding the number of devices, the comparison is non sense; however, in terms of usefulness, enjoyment, and absence of cybersickness, the devices of the graphics-based VR are better for the learning process. A similar suggestion was also provided by Holly et al. (2021) that recommends graphics-based VR to enable interaction with the virtual world with a high level of immersion while achieving an increased learning effect and avoiding motion sickness.

Moreover, teachers and researchers must deploy more forward-looking educational programs that accommodate the nature of these technologies and fulfill the learner's needs. When applied properly, these technologies can enhance contemporary educational environments and enrich learning opportunities for students (Elmqaddem, 2019). For example, using VR laboratories instead of traditional laboratories can reduce laboratory equipment costs and allow learners to perform expensive experiments within the virtual world that can provide a similar degree of immersion with unlimited repetition (Holly et al., 2021).

Finally, knowing how to use technology hardware and software is insufficient to enable teachers to use the technology effectively in the classroom. Teaching with technology requires teachers to expand their pedagogical practices across multiple aspects, such as knowing how to develop plans for teaching software to students, selecting appropriate technologies to meet instructional and learning needs, and managing computer hardware and software (Ertmer & Ottenbreit-Leftwich, 2010). For VR development, it is also necessary to consider that educators are focused on applying the products and do not need to be directly involved in making computer graphics model VR.

Conflict of Interest statement

The authors declare no conflict of interest, financial or otherwise.

Consent to participate

No clinical investigation is carried out on humans and animals.

Consent for publication

Not applicable.

Acknowledgments

This work is supported by the National Science and Technology Councils of Taiwan, under grant MOST 110-2511-H-415-002 and MOST 109-2511-H-415-004.

Data Availability

The data supporting the findings of this study, including all code for data analysis associated with the current submission, are available at https://doi.org/10.17605/osf.io/eu4ry. Derived data supporting the findings of this study are available from the corresponding author Dr. Chih-Hung Lin on request.

Ethics declarations

Ethics approval

All participants in the research were purely voluntary and understood the process in which they were to be engaged. The participants’ data were anonymized and kept confidential in the research.
All quantitative and qualitative data sets of this research, which are anonymized, can be made available by individual application directly to the authors. The applicant should clearly describe where and how they will use the data sets in their contact letter. The applicant should also cite the source of the data sets in their ongoing papers.
As an expert scientist and along with co-authors of the concerned field, the paper has been submitted with full responsibility, following the due ethical procedure, and there is no duplicate publication, fraud, plagiarism, or concerns about animal or human experimentation.

Author contributions

Dadan Sumardani: Conceptualization, Methodology, Software, Data curation, Writing- Original draft preparation. Chih-hung Lin: Investigation, Supervision, Validation, Funding acquisition, Writing-Reviewing and Editing.

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No competing interests reported.

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Investigating the Factor that Influences the Implementation of Virtual Reality for Science Learning

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Abstract

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1. Introduction

2. Literature Review

2.1. Virtual Reality in Science Concept

2.2. Teachers' Acceptance of Virtual Reality

2.3. Virtual Reality Device

2.3.1. Graphics-based VR and 360-degree VR

3. Method

3.1. Participants

3.2. Procedure

3.3. Questionnaire

4. Data Analysis And Results

4.1. Validity

4.2. Hypothesis Testing

4.3. Open-ended Question

5. Discussion And Conclusion

6. Implications For Educators And Limitations

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