Everett Rogers's book Diffusion of Innovations1 is one of the best-known works of sociology of all time. The reader is probably familiar with the S-curve model of diffusion, which maps out the saturation of an innovative object or practice in society or in a group over time, as well as the five categories of adopters (innovators, early adopters, early majority, late majority, and laggards). Diffusion theory also identifies the characteristics that make each adopter category more or less likely to adopt an innovation and strategies to help persuade potential adopters to adopt an innovation. This study relied heavily on Diffusion of Innovations for the frameworks used here to discuss adoption of XR by institutions of higher education.2 

Adoption of an innovation is a multistage process: adopters must first learn about the existence of an innovation, then collect information about it, then make the decision to adopt it (or not). These stages are, of course, in the past for the institutions participating in this study: they all obviously decided to adopt XR technology.

After the decision to adopt an innovation comes the implementation—and this is where things often get complicated, particularly in higher education, where institutions contain multitudes: campus units have different scopes, budgets, risk tolerances, and stakeholders. Furthermore, faculty act in some ways like independent operators (though more at some institutions than at others) and may implement an innovation prior to their unit's doing so; or they may even reject an innovation that their unit has adopted.

Diffusion theory identifies two broad categories of adoption decisions: collective decisions, whereby the community of interest comes to consensus through some means, and authority decisions, whereby the adoption decision is imposed from the top down. Institutions of higher education, of course, possess mechanisms for collective decision-making, such as faculty senates and other such institutional committees. This is not, however, generally how XR technologies were adopted at the institutions participating in this study.

The research question for this project was: What factors influence institutional deployment of XR technology? In other words, what leads to the decision to adopt XR technology on campus? And after the adoption decision, what influences institutional decisions about how XR technology is to be deployed on campus? For institutions participating in this study at least, two overarching factors influenced the adoption of XR.

First, the method by which XR technology comes to campus affects the process of implementation. Technologies frequently come into institutions of higher education under the radar, as it were, through individual innovators and early adopters, outside of any institutional support. While this report is concerned with institutional deployment rather than individual adoption, this is how XR first came to several participating institutions prior to the start of this study: individual faculty members using various XR technologies for their own teaching or research. This method may lead to institutional adoption: Yale University, Syracuse University, Columbia University, and the University of Pennsylvania are notable examples,3 but it is a slow ramp-up because a critical mass of individual users must generally be reached before the institution even takes notice of the technology in question (as is currently happening at Syracuse University). Implementation nearly always goes faster when the adoption decision is made by institutional leadership (e.g., the board of trustees or the CIO, as at Wake Technical Community College and the Foothill-De Anza Community College District). This is especially true when institutional leadership accompanies the adoption decision with resources, e.g., small project grants, additional staff, and the like.

At other participating institutions, adoption was motivated from above. At these institutions, XR technology was imposed by institutional leadership, such as the institution's board of trustees. Having been instructed to deploy XR technology, institutions then had to figure out how to make it so. Mostly, that implementation fell to the institution's CIO or the equivalent position (vice chancellor for technology, etc.).4 At the North Carolina School of Science and Math, for example, the XR technology was provided to a specific department (biology) for which instructors had a clear and preexisting use case (to teach genetics and molecular biology). At Wake Tech, the CIO identified a handful of interested faculty and use cases through workshops and brainstorming sessions. In the Foothill-De Anza Community College District, the CIO took both of these approaches.

The other overarching factor that affects the process of implementation is the existence of institutional infrastructure to support technology. This institutional infrastructure is both technological and organizational; for XR technology to be implemented, there must be a place for it on campus. At Florida International University (FIU), for example, XR technology has been implemented on a large scale in the College of Communication, Architecture + The Arts' Miami Beach Urban Studios (MBUS), a facility that supports 3D printing and scanning, along with other XR technologies. Likewise, at North Carolina State University (NCSU), XR technology is integrated into the library's well-established technology lending program. Bucks Innovate at Bucks County Community College, added XR to an existing set of training programs on offer. These examples demonstrate that some campus unit must take responsibility for XR technology deployment. Hamilton College provides our final example: the XR initiative at Hamilton is managed by Library and Information Technology Services, a single administrative unit that combines the technology expertise of campus IT with the user focus of the library.

There is a middle ground between individual adoption and having it dictated from on high. Some of the institutions participating in this study began their deployment of XR technology with projects rather than individual courses. At MIT, for example, the Collaborative Learning Environments in Virtual Reality (CLEVR) project is a research effort within the Scheller Teacher Education Program aiming to develop VR simulations for classroom use. For another example, the Morgan State University, School of Community Health and Policy, Nursing Program is seeking research grant funding for a curriculum development project that uses XR technology. Importantly, at both of these institutions, XR technology is being deployed as the centerpiece of an applied research project. In both cases, XR is framed as something that can potentially benefit teaching and learning, and the projects that have deployed it are exploring how to use the technology most effectively as an educational methodology. Further, both of these institutions are deploying these projects at the level of specific academic units; in neither case has this deployment been taken up by other academic units or by a campus-level unit such as central IT or a center for teaching and learning. Perhaps in time the MIT Scheller Teacher Education Program and the MSU Nursing Program will integrate XR technology into their curricula at large, but at present this technology is still framed as applied research.

Another institution at which XR is being deployed at an intermediate scale—that is, within a campus unit—is Bucks County Community College. Bucks Innovate offers corporate training programs on a variety of topics. One of the newer offerings from Bucks Innovate is an XR technology showcase and hands-on demo event for CEOs and other corporate leaders, addressing the question of how organizations can benefit from XR. Because the unit is relatively new at Bucks, it is not yet clear how the deployment of XR by Bucks Innovate will impact the rest of the institution. But, as at MIT and Morgan State, XR is being deployed at Bucks to explore the potential benefits of the technology for teaching and learning.

All of the institutions of higher education that participated in this study have obviously deployed XR technology in some way or would not have been a part of this study. The campus unit with primary responsibility for this deployment varies across participating institutions. The important point here, however, is that at most participating institutions, a single campus unit had primary responsibility for implementing some set of XR technologies for some set of users. This campus unit may be a degree-granting unit such as the Newhouse School of Public Communications at Syracuse University or the Nursing Program at Morgan State University. What was more common among the participants in this study, however, was that the campus unit was not a degree-granting unit: a library, as in the Foothill-De Anza Community College District; a makerspace, such as the Miami Beach Urban Studios at Florida International University; a research center, such as The Education Arcade within the MIT Scheller Teacher Education Program; or an interdisciplinary initiative, such as the Emerging Technologies Consortium at Columbia University. Furthermore, the set of XR technologies were implemented for some set of users, for some set of use cases. Mostly, these use cases were for teaching, as in the Morgan State University Nursing Program, though some were a combination of both teaching and research, as in the MIT CLEVR project. The important thing in the context of this study is that a decision to deploy some set of XR technologies had already been made by one or more campus leaders with some degree of budgetary control within a unit at the institution, and that the deployment and management of these technologies had been undertaken by a campus unit.