Extended Reality Vocational Training’s Ability to Improve Soft Skills Development and Increase Equity in the Workforce

1.1.

What are XR learning methods and why are they used?

The implementation of digital, online, and XR learning methods has dramatically increased over the past decade. In particular, due to the COVID-19 pandemic, many schools, educational organizations, and businesses were forced to adapt rapidly to at-home learning needs to provide services to their homebound students. While digital and online learning approaches have demonstrated benefits, recent studies have highlighted immersive learning approaches, such as XR learning methods, as potential game changers in education. One can currently define the ever-expanding umbrella of XR learning methods as virtual, augmented, and mixed-reality educational approaches. These methods support the delivery of educational and training course materials through interactive computer simulations in immersive environments, which can sense positioning and responses, and provide feedback [4, 5]. Standard features include an immersive learning environment facilitated by essential hardware (e.g., Meta Quest 2 [6], HP Reverb G2 [7], Valve Index [8], Sony Playstation VR [9], HTC VIVE Pro 2 [10], etc.) and online learning modules. These modules facilitate individually-paced learning through lessons incorporated into a learning program with instructional objectives and a data analytics system, which assesses student progress and development, such as Talespin’s immersive soft skills programs focused on conflict resolution, cognitive bias, and active listening and inquiry [11].

Regarding XR learning methods, immersion involves the quality of experience, mental absorption, and perceptual and cognitive engagement a simulation offers in a digitally-generated space [5, 12, 13]. Burdea and Coiffet [14] maintained the three most important properties of immersive technologies like VR are the 3Is, imagination, immersion, and interaction. Immersion through simulated learning, such as XR learning methods, can increase engagement, memorization, skills acquisition, and knowledge transfer through situational understanding [12, 15]. These immersive learning approaches and hardware are beginning to evolve how organizations offer training and educational opportunities to their students and employees, providing accessible on-demand learning as a substitute for limited face-to-face alternatives. These learning experiences offer exposure to challenging situations in safe, controlled environments and simulate complex, detailed interpersonal engagements and situations, allowing users to gain and improve skills while applying them in real-life scenarios [16–19]. Multiple studies noted K-12 and higher education VR-based instructions were effective in improving learning gains [12, 20]. As organizations evolve with changing needs for the future of work, employers identified soft skills as an area of deficiency in potential employees and workforce-entering graduates [21–23]. Few essential soft skills and related competencies include communication, critical thinking, intercultural competency, leadership, teamwork, and time management. Employers often consider these skills more critical than undergraduate majors because today’s workplaces need critical perspectives and diverse viewpoints [22] to face and solve real-world problems [24].

While multiple studies demonstrated the effectiveness, satisfaction, and quality of XR learning methods [16], wide adoption in educational organizations is still a work in progress, requiring further investigation of XR development and adoption process. A 2020 TechRepublic survey of tech executives noted that 56% of businesses implemented mobile AR/VR technology, and another 35% considered doing so [25]. However, only 26% used it for training and professional learning purposes. Though multiple XR hardware options exist, some of the most popular models suffer from key drawbacks, including high cost, mediocre controls, space and tether cable requirements, and low-quality resolution [26]. Additionally, XR-based learning design and development is often guided by intuitive and common-sense approaches rather than a well-researched educational affordance analysis, potentially impacting the learning effectiveness and outcomes [12, 27, 28]. Failed XR learning adoption cases can relate to users’ technology literacy deficiencies, including lack of VR experience, need for technical support and comprehensive onboarding [29], misconceptions of learners’ benefits and effectiveness, especially for specific industries such as healthcare and medicine [17].

3.1.

Motivation to adopt

Motivation to adopt new technologies and learning methods at organizations can vary but often focus on several key aspects, including business value, cost, learning speed, overall quality and learning value, and exploring new technologies [16]. A joint study led by Price Waterhouse Coopers (PwC) [35] on Talespin [36], an XR vocational training firm, and its VR learning methods emerged from interest and inspiration generated while viewing a Talespin VR demonstration in 2018 at Boston’s Emerging Technology conference. The PwC team viewed the learner demo as “an immersive, engaging and emotional experience” and a “game changer” [16, p. 10–11]. PwC sought to investigate if VR soft-skills training was more effective regarding learning and cost than traditional methods (i.e., classroom, e-learning). The motivation to adopt and trial within PwC occurred as a top-down, authoritative organizational decision. It related to the relative advantage the new VR learning could provide to the leadership, its compatibility within the organization, and the potential questions trialability could answer and implications it could have for PWC and broader organizational training.

In another study, Palmas, Cichor et al. [18] examined the effectiveness of VR public speaking training with 44 participants. The primary decision to adopt the technology in the study related to positive benefits attributed to VR applications related to presence, noted as the concept of ‘being there’ and having the opportunity to experience learning corresponding to real-world scenarios [18, 37, 38].

During COVID-19’s first six months, Young and Aquilina [39] detailed how Virti, a United Kingdom (UK) based training and development company, conducted a feasibility trial of on-demand VR learning support to National Health Service (NHS) organizations and fifty healthcare professionals across the UK and United States (US). The decision to adopt this test program rapidly related to the need for training hundreds of thousands of healthcare workers, with face-to-face options unable to meet the demand. VR learning methods delivered via headsets and smartphones provided the relative advantage of rapid scalability at a low cost. They also matched the compatibility and complexity of the large-scale crisis, on-demand needs. The adoption also offered product trialability before wide-scale adoption and observability of potential key benefits, barriers, and needs.

Ke and colleagues [12] adopted VR-based learning to investigate the simulated environment’s affordances, benefits, and constraints regarding providing teaching training for university graduate teaching assistants related to goal-based scenarios and learning support design. The study engaged seventeen graduate teaching assistant participants in a multiple-case study with OpenSimulator. This open-source virtual environment platform provided a simulation-based teaching training program focused on their engagement in a virtual classroom with interactive, non-player characters (NPCs). They specifically examined the design aspects that enhance and improve the educational affordance of an intentionally-designed VR learning environment with university students. The motivation to adopt related to relative advantage for the graduate assistants, compatibility with a higher education learning environment, the complexity of training soft skills related to teaching, and trialability of a new technology learning method.

3.2.

Decision to adopt

Rogers [1] detailed three types of decisions associated with the decision to adopt an innovation: (1) it is “optional,” and an individual may adopt or reject it, (2) the collective group decides to adopt or reject, or (3) an authority figure or body makes the decision for the group. At PwC, Talespin’s VR learning methods were first employed in 2020 for ten months as a top-down, authority-innovation decision. It was associated with trialing and exploring the learning and cost benefits of training with the new technology with internal staff compared to more traditional classroom and e-learning approaches [16].

Like PwC’s study, Palmas and colleagues [18] employed a top-down researcher decision to test the public speaking VR learning approach but only implemented it for a single short training session. As participants were selected from multiple contexts, no clear decision to adopt was identifiable for particular organizations. However, participants noted a high barrier to social diffusion in individual contexts due to management resistance.

Young and Aquilina [39] described a similar top-down authority body decision process in their study. Virti needed to align with funding from NHS in the UK and top health providers in the US to implement the VR healthcare learning trial. Participants were randomly selected for the control and intervention groups, giving them zero insight into the adoption decision process.

Following a pattern with the other detailed studies, Ke and colleagues [12] also noted a top-down authority body decision regarding the adoption process in their research, acting as the sole deciders for its implementation. The authors recruited seventeen graduate teaching participant volunteers from various disciplines, including computer science, chemistry, physics, biology, psychology, philosophy, and modern language.

3.3.

Adopter categories

Eckert and Mower [16] did not specifically identify the involvement of the adopter categories at PwC. However, the PwC Emerging Technology team noted its lack of knowledge regarding the psychology and science behind the novel learning technology. As a result, it partnered with PwC’s Learning and Development group to investigate two key research questions. Therefore, the study involved innovators trialing a new organizational training potential tool.

The public speaking VR training study by Palmas and colleagues [18] also did not explicitly identify adopter categories. However, as many participants highlighted its innovative nature compared to their rather conservative-minded organizations regarding training, it most likely involved the innovator adopter category.

Following a trend with previous articles and due to its novel nature, Young and Aquilina [39] also did not identify specific adopter categories. However, based on the trialability factor of the VR healthcare training, it once again described the innovator adopter category, with the idea that successful implementation would diffuse through social influence from top NHS and US provider officials and participating administrators, doctors, and healthcare professionals.

Recruits for the VR learning affordance study with Ke and colleagues [12] were graduate student volunteers across multiple disciplines actively engaged in teaching other university students. Considering the voluntary aspect of the recruitment, the student also describes the innovator category, with participants interested in engaging and learning through a new technology method.

3.4.

Implications of the adoption process

Several studies highlighted key implications for the adoption process. In the PwC study on Talespin, Eckert and Mower [16] highlighted several measurable outcomes of the VR learning experiment. The authors noted Talespin’s VR training was more efficient at training soft skills concepts and was more cost-effective than classroom and e-learning approaches. The study also highlighted that participants were 275% more confident about concepts learned, four times more focused than e-learners, learned four times faster than in the classroom, and possessed 3.75 times stronger emotional connection to their learning [16]. The authors maintained eight key considerations and insights for the VR learning method adoption process: (1) onboard new VR learners effectively, (2) create compelling learning content for VR, (3) collaborate cross-functionally, (4) reinforce learning through debriefing, (5) create templates to support scaling, (6) include VR as a part of a blended learning curriculum, (7) invest in the learning modality suited to the learning objective, and (8) VR is ready to scale in the enterprise.

Palmas and colleagues [18] noted that while participants found the training engaging and 80% highlighted it as beneficial for their organizations, the majority felt multiple sessions versus a single session was required to be more effective for learning. A critical implication and potential barrier related to the adoption of VR learning methods highlighted by the participants related to the viewpoints and acceptance of their organizations. Participants described that the approach could not be effectively implemented in their organizations due to “conservative decision makers and skepticism” regarding the technology [18, p. 369].

In their literature review examining gamification, serious games, simulations, and immersive learning environments in knowledge management initiatives, Ahmed and Sutton [40] described higher education and organizational training as experiencing significant disruption in today’s workforce to meet 21st century challenges. To meet the demands of this disruption, the authors maintained teaching and learning initiatives need to integrate more experiential learning, which gamification, immersive learning, serious games, and simulations provide (2017).

Immersive VR training methods can also provide large-scale adaptive training quickly [39]. The authors highlighted multiple additional potential use cases in health and social care beyond emergency COVID-19 protocols, “including accelerating care certification, refresher and re-certification training, and more soft skill based modalities including but not limited to: roles and responsibilities; whistleblowing; equality, diversity and person centred values; telephone support and communication; pain and discomfort; infection prevention and control; food safety; fluids and hydration; health and safety and stress management” [39, p. 142]. The study concluded that immersive learning approaches could offer learner growth coupled with convenient, on-demand access to a wide variety of learning opportunities along with data insights to improve reflective feedback and maximize performance [39]. In addition, financial data revealed significant savings regarding training costs and return on investment for VR immersive training.

Ke and colleagues [12] maintained that a well-designed VR-based learning environment fosters participants’ effectiveness in interactive teaching and demonstrative instruction. They also claimed it trains them to identify and attend to students’ actions and reactions during the instruction process, allowing them to provide more effective support. While there is no agreed upon definition of a ‘well-designed’ VR-based learning environment, the author suggests the critical 3Es — engagement through immersion, elevation of instructional interaction, and effective support. As Robert Sternbert noted, “the major factor in whether people achieve expertise is not a fixed prior ability but purposeful engagement” [41, p. 14]. In XR, purposeful engagement involves effective immersion in a simulated environment, which offers a high-quality experience, mental absorption, and perceptual and cognitive engagement [5, 12, 13]. Elevation of instructional interaction points to complex interactions with the virtual environments and NPCs, allowing for conceptual absorption of effective practices. Finally, effective support notes the need for onboarding, ongoing training, and technical support [29] to ensure an efficient learning process. Additionally, Ke and colleagues [12] described the graduate participants demonstrating a more precise understanding and application of the embedded teaching knowledge by leveraging the situated learning in the simulated environment [12]. It also maintained evidence of the effectiveness of engagement with NPCs. However, multi-way interactions and multiple graphical presentations in the VR environment limited participant interaction, and the lack of reciprocal engagement from limited NPCs reduced the cognitive impact of the teaching scenarios. The study highlighted that physical reality maintained advantages over the virtual environment due to the limited functional intelligence of NPCs, as added intelligence and engagement could overwhelm real-time processing constraints. The authors recommended a potential design strategy to overcome this challenge. This approach involved integrating “a choice-based interaction interface that enables the user to interact with virtual agents through semi-structured (e.g., multiple-choice) responses during a simulated scenario, thus reducing the need for text or nonverbal action processing” [12]. Finally, the authors noted the simulated virtual environment offered an absence of maneuverability and complex interactions between the users and the environment compared to a real classroom.

3.5.

Adoption process of XR learning methods

Several studies analyzed the adoption process of XR learning methods within different contexts [12, 16, 18, 39, 40]. These studies described various reasons connected to Rogers’ [1] diffusion of innovation theory that adopters initially embrace an innovation. As Rogers highlighted, adopters fall into five different categories: (a) innovators, (b) early adopters, (c) early majority, (d) late majority, and (e) laggards. In all studies reviewed, adopters fell primarily into the innovator category with little long-term diffusion described due to study lengths and the relative novelty of the technology. Rogers [1] detailed the adoption process flow aligning with a standard bell curve as more individuals in a social system embrace its use. Rogers also maintained adoption followed five key stages, including knowledge, persuasion, decision, implementation, and confirmation, starting with the initial introduction and use. The studies reviewed only showcased the knowledge and persuasion stages, as long-term adoption was not examined. These initial studies highlighted fundamental knowledge and persuasion points that social champions within their organizations could use to engage others to implement XR learning methods.

Due to the short longevity of the studies and technological novelty, social pressure could not be adequately analyzed. However, the very investigation and introduction of the novel technology for examination highlighted the engagement of innovators and potential champions to promote its use. In this case, researchers filled the role of introductory change agent, with the beneficial results potentially working to further the early adoption process to disseminate the XR learning innovations amongst other organizational trainers, learners, and leaders. However, further investigation is required to determine if this had an actual impact. This description aligns with Frank and colleagues’ [2] social capital-infused theoretical diffusion model within organizations. This model identifies change agents as essential for the influential and practical introduction and exchange of ideas within the social network of a given organization. In this case, the researchers acted as the change agents within the community, with further champions required to facilitate the diffusion process effectively. Social exchange through a network of influential colleagues, trainers, and organizational leaders is crucial for rapidly adopting new technology. This aspect requires further, long-term analysis in future studies focusing on the comprehensive adoption process contexts implementing XR learning methods.