Reconsidering the Middle Ground in Emerging Technology Adoption

OpenAI (2024) Illustration generated by ChatGPT.
During this season of my educational journey, I have been working with BUILDS analysis and Implementation plans for emerging technologies like wearables, emotional recognition, and smart textiles. These technologies are poised to transform the technological foundations of modern educational environments. As I reflect on the best pathway forward for the organizational adoption of these tools, I am reconsidering my comfort level and trust in emerging technologies.

This fall began with a self-assessment in light of the Diffusion of Innovation Curve, placing me in the Early Majority due to my pragmatic approach to adopting new technologies. Emerging technologies like smart textiles and wearables can indeed be implemented in a manner that promotes stability and supports efficacy in educational settings (Cruz-Garza et al., 2024). However, this semester has highlighted how critical a well-designed implementation plan is for integrating new technologies into existing systems, which allows me to adopt innovations responsibly while minimizing risks.

Rooted in the Early Majority, my strategic adoption is driven by the demand for proven and stable technologies before widespread application. This cautious approach ensures that new implementations are beneficial and sustainable within professional environments (Cook et al., 2024). Emerging technologies, by definition, require additional deployments to be fully understood. As a learning designer, I determine which innovations can be integrated thoughtfully without squandering organizational resources, aligning new tools with long-term strategic goals.

Considering the role of smart textiles and wearable technologies has opened up exciting possibilities for enhancing interaction and data-driven insights in educational practices (Cruz-Garza et al., 2024). With any emerging technology, there is a need for additional deployments that are successful and adequately evaluated.  A properly evaluated implementation should be published since it contributes to a broader industry understanding of emerging technologies. The challenge, however, lies in our ability to contribute to the industry's understanding of these technologies through strategic deployments without sacrificing the integrity of the learning environment. By participating in carefully planned pilot projects, we can explore these technologies' potential benefits and pitfalls in a measured, insightful manner.

This semester’s exploration of emerging technologies like wearables, smart textiles, biometrics, and emotional recognition has reinforced my cautious but open approach to new tech. Each new tool's adoption is predicated on a BUILDS analysis that describes tangible benefits that justify its integration into our current systems (Udell & Woodill, 2019; Cook et al., 2024). Despite the empowering effect of new evaluation strategies and perspectives on emerging technology, I maintain my Early Majority position on the curve. 

These analysis and implementation approaches assist the learning designer in predicting the impact and value of emerging technology on the organization they serve. As this predictive toolkit brings the future into focus, the learning designer can count the cost to the organization and better assess the likelihood of success. Pragmatism endures alongside these tools, ensuring that any adopted technology has a clear, beneficial impact on organizational practices, balancing the innovative against the practical.

The Early Majority mindset promotes a more thorough understanding of new technologies' potential risks and rewards, emphasizing the necessity for a methodical and informed approach (Cruz-Garza et al., 2024). It is about moving forward with innovations backed by solid planning and real-world applications, ensuring that our advancements in educational technology are both significant and strategically sound. It is also about leveraging other organizations' costly failures to support a successful implementation of our own. The Early Majority mindset rests on the middle ground between Innovators and Laggards (Rogers, 1962). The value of this middle-of-the-road approach can be understood by looking at extremes, exemplified by NASA and SpaceX in modern rocket development.

OpenAI (2024) Illustration generated by ChatGPT.
NASA's reluctance towards reusable rockets such as SpaceX's Falcon 9 is rooted in a traditional outlook that equates reliability with prior flight successes. This conservative “Laggardly” stance, costly in both time and resources, emphasizes risk minimization and views new technology as a potential hazard rather than an advantage. By comparison, SpaceX’s “Innovator” approach has proven the economic and operational benefits of reusable rockets, albeit at considerable cost, including a launch pad explosion in 2016 and an in-flight failure in 2015, contributing to the $1 billion development cost of the Falcon 9. These costly incidents were necessary to refine the technology and ensure safety and reliability (Space.com, 2021).

Interestingly, China continues to unveil new rocket designs “inspired” by SpaceX designs (Space & Defense, 2023). Their rocket development curve follows that of SpaceX but is predictably behind. The question must be asked, “What are the cost and time-to-develop savings associated with China’s ruthless approach to copying Western designs?” We may find China’s approach predatory, but no one can argue with its pragmatism from a resource perspective. This is the value of Early Majority, or perhaps Early Adopter thinking.

As we look to the future, detailed implementation plans are critical tools for learning designers advocating the adoption of new technologies and expanding our collective knowledge within the industry (Cook et al., 2024). Strategic planning is central to advancing our understanding without overextending our resources, making change sustainable and impactful.

Reflecting on this semester's experiences, the value of my position on the innovation curve has only been reinforced, ensuring that my professional engagements and technological adoptions are deliberate and impactful (Cruz-Garza et al., 2024). As an Early Majority thinker, I will continue to navigate the evolving landscape of educational technology, ensuring that each step forward is as informed as it is innovative.


References

Cook, R., Kent, A., Fisher, T., & Braithwaite, N. (2024). Understanding the Adoption of Smart Textiles: Insights from Innovation Theory and Interpretative Phenomenological Analysis of Interactive Experiences. MDPI. https://doi.org/10.3390/engproc2023052023

Cruz-Garza, J. G., Ramírez-Moreno, M. A., & Lozoya-Santos, J. de J. (2024). Wearable Biosensor Technology in Education: A Systematic Review. MDPI. https://doi.org/10.3390/s24082437

IEEE. (2024). Wearable Technology in Education: A Systematic Review. IEEE Xplore. https://ieeexplore.ieee.org/document/9525202

Udell, C., & Woodill, G. (2019). Shock of the new: The challenge and promise of emerging technology. ATD Press.

Space.com. (2021). SpaceX Falcon 9 failure highlights need for multiple launch options. Retrieved from https://www.space.com/spacex-falcon-9-launch-failure-lessons

Space & Defense. (2023). China’s Long March 9 Rocket Inspired by SpaceX’s Starship. Retrieved from https://spaceanddefense.io/chinas-long-march-9-rocket-inspired-by-spacexs-starship/