WOL Reflection: I Am Reevaluating the Curve

WOL Reflection: I Am Reevaluating the Curve

When I began this course seven weeks ago, I placed myself on Rogers’ Diffusion of Innovation curve as an Early Adopter. At the time, this felt accurate because I have always been curious about new tools and design approaches, but I also valued structure, evidence, and real use cases before investing too deeply in an innovation. I approached technology with a balance of enthusiasm and caution. My goal was to understand how something worked, test it in controlled conditions, and evaluate whether it supported both learners and organizational priorities before integrating it into a workflow.

This mindset has shown up in my professional work as well. While taking this course, I have been leading the transition to MS Planner with Power Automate customization as our primary project management system, moving our training program away from static SharePoint lists and Excel sheets and toward more automated and efficient processes. That experience reinforced the importance of choosing technologies that meet federal expectations for compliance, accessibility, and stability. In my environment, stability means predictable performance, minimal downtime, compatibility with existing systems, and a clear return on investment that justifies the effort it takes to implement and support a new tool.

Looking back now, I can see that my original perspective captured only part of how I actually operate as a designer and leader. These past seven weeks encouraged me to evaluate not only the technologies themselves, but also how I think, react, and adapt when the pace of innovation accelerates. I no longer see my position on the curve as purely defined by comfort level or curiosity. Instead, it is shaped by the demands of my role, the expectations of the learning audience, and the responsibility I have as a designer and leader to anticipate what is coming next.

What were the pivotal moments or key technologies that significantly impacted my understanding?

There were several moments during the course where my perspective shifted more than I expected. Each one pushed me to expand my comfort zone and rethink how emerging technologies shape instructional design.

One of the most impactful experiences was the generative AI design partner project. I have used AI in various forms before, but this assignment required a good level of integration. I scripted, produced, refined, and assembled a multimedia product with the help of generative tools. Working with narration, imagery, timing, and creative direction made me realize how quickly design workflows are evolving, as well as their limitations. AI did not replace my creativity; it amplified it. I was still the designer making decisions about structure and learner experience, but the technology accelerated the early stages of production significantly. That experience shifted my thinking from, "AI can help me draft ideas," to, "AI can meaningfully shape and support the full design process".

Another important learning milestone came from the BUILDS framework discussions. Because the discussions were intentionally scaffolded, each week strengthened my ability to evaluate a technology beyond surface-level features. The framework required me to look at benefits, limitations, ethical risks, long-term scalability, and organizational fit in a systematic way. This approach is especially valuable in a federal context, where implementation decisions cannot rely on novelty alone and must be guided by well-defined requirements. Decisions have to be grounded in compliance, accessibility, and learner impact to ensure the technology supports real outcomes. Evaluating my chosen technology through the BUILDS lens showed me how structured and methodical innovation needs to be in a regulated environment. It also provided me with a repeatable evaluation model that I can apply in my professional practice and use as I assess future tools and systems.

I also learned a good deal by reading my peers’ analyses of technologies that I did not evaluate myself. Across the discussions, classmates explored topics such as VR, AR, intelligent agents, blockchain, advanced analytics, and even early conversations about quantum computing. Seeing how others interpreted use cases and adoption signals broadened my understanding of what qualifies as emerging technology. It helped me realize that innovation does not progress in a single direction. It branches out in multiple ways at once, shaped by society, policy, industry demand, and many other forces. Together, these observations reinforced that emerging technologies are not abstract concepts, but rather, active forces that influence how instructional designers work, collaborate, and create.

Where do I see myself on the innovation curve now, and why?

At the beginning of the semester, I felt confident identifying as an Early Adopter. Today, I still see myself in that category, but I have moved closer to the Innovator mindset than I expected. What changed is not my curiosity level but my willingness to engage early, test boldly, and help shape the direction of a tool before it becomes mainstream, while capitalizing on its efficiency until then.

The course helped me realize that waiting for technologies to mature can place designers on the defensive. It forces us to react rather than anticipate. In fast-moving fields like AI, xAPI analytics, immersive media, and automation-assisted design, the people who engage early are the ones who help define standards, set expectations, and guide ethical adoption. This is particularly important in my professional world where emerging technologies intersect with clinical training, regulatory compliance, Veterans’ services, and federal oversight. These environments cannot afford to be careless or uninformed, which means designers need to understand what is coming before it arrives.

I also recognized that my real-world responsibilities align closely with the expectations placed on early adopters. I evaluate vendor deliverables, guide development teams, create multimedia products, and mentor others through technology transitions. My role already places me at the front end of the adoption process. This course simply made that more visible.

Moving forward, I feel more comfortable occupying that space. I am more confident experimenting, more willing to iterate, and more committed to shaping adoption pathways that prioritize accessibility, ethical use, learner-centered design, and efficiency. I see emerging technologies becoming a bigger part of my next career chapter, especially as I explore private sector roles and/or continue developing my own eLearning business. Innovation has become a requirement, not an option.

Final Thoughts

The last seven weeks reinforced that my position on the innovation curve is not fixed. It shifts as I gain experience, as the field evolves, and as my professional responsibilities expand. I entered the course as an Early Adopter who preferred structure and evidence before embracing a new tool. I am leaving as an Early Adopter who is more proactive, more experimental, and more willing to engage with emerging technologies even before all the answers are available, with models like BUILDS to help guide the process.

This course helped me see that innovation is not just about learning new tools. It is about mindset, adaptability, and the responsibility to guide others through change. The technologies we explored have already shaped how I evaluate design decisions, how I approach workflow planning, and how I envision my future in the field. I now feel better prepared to lead with curiosity, support colleagues through transitions, and design learning experiences that remain flexible in a rapidly changing ecosystem. Emerging technologies are not slowing down, and instructional designers cannot afford to either. This course helped me strengthen the mindset I need to keep moving forward.