Where I am On the Curve
Since I came into this world, technology has never stopped moving. There has been advancing gadgets, new updates and media since I could remember. Technology is constantly shifting, adapting, reinventing itself, and it keeps finding new ways to influence how we connect and operate. In the field of learning design, that constant evolution feels both exciting and demanding. It’s not enough to simply keep up; we have to understand why something matters and how it actually supports people. Over the years, I’ve realized that my approach to technology sits somewhere between the Early Adopter and Early Majority categories in Rogers’ Diffusion of Innovation Theory. I’m quick to explore new tools that catch my attention, but I also like to observe how they play out before I commit to them fully. I’m both curious and cautious because in a time when things are created for profit I do get skeptical. I am someone who loves the promise of innovation but still looks for evidence of value and alignment with real human needs.
Finding My Place Between Early Adopter and Early Majority
According to Rogers (1962), Early Adopters are people who are quick to embrace new ideas and often act as influencers for others. They thrive on experimentation and aren’t afraid to take calculated risks. On the other hand, the Early Majority tend to adopt once an innovation has been tested and proven effective. They’re practical, thoughtful, and like to see clear outcomes before changing their routines.
I see myself in both groups. I get excited about new tools, especially when they make work or learning more meaningful. When I worked in early childhood education, I loved using Brightwheel, an app that made communication with families smoother and documentation easier. It showed me how tech can strengthen relationships instead of replacing them. I didn't hesitate to try it because I knew it was something that I needed to bridge connection between school and parents. It made my work so much easier. I’m eager to try new things but still pay attention to how they actually work for others, finding a balance between curiosity and caution.
Curiosity as a Habit
My curiosity tends to guide me toward tools that spark creativity and simplify processes. Canva is a great example. I use it constantly, not just because it’s convenient, but because it makes design accessible. It gives non-designers like me the ability to create visually appealing materials without advanced technical skills. I love how it encourages playfulness, iteration, and accessibility. Canva represents what I value most about technology: it’s inclusive, intuitive, and empowers people to express ideas clearly.
I see AI tools through a similar lens. They’re nuanced and far from perfect, but they open doors to knowledge and creativity that used to be locked behind money, expertise, or time. AI can be a bridge connecting people to resources and opportunities that would have otherwise been out of reach. To me, that’s progress. But I also remind myself that AI, like any technology, is a tool, not a replacement for human thought or creativity. I think that using it with intention, it can make learning and design make life easier for people to focus on their energy elsewhere. It can also spark ideas and serve as an assistant or mentor. I believe that used carelessly, it can flatten nuance or reinforce bias. My curiosity keeps me open to experimenting, but my early-majority side reminds me to stay critical and grounded.
What This Means for My Work in Learning Design
My place on the curve influences how I approach both technology and design. As an emerging learning designer, I try to lead with curiosity but follow with reflection. I like to test new tools, especially ones that can make learning more interactive, equitable, and emotionally engaging, but I also pay attention to how learners experience them.
When exploring a new platform or method in the future, I want to ask myself the following questions. Does this genuinely improve learning outcomes, or just make things look more advanced? Is it accessible to all types of learners? Does it protect user data and support ethical use?
These questions can keep me focused on the “why” behind innovation rather than getting swept up in the novelty of the “what.” I’ve noticed that my position on the diffusion curve helps me connect with both sides of a team: the innovators who want to try everything first and the late adopters who need evidence before committing. I can translate excitement into practicality, helping others see how technology fits into real learning contexts.
Staying Balanced and Growing Forward
One thing I’ve learned from reflecting on this theory is that our position on the curve isn’t fixed. It shifts depending on the context and the stakes. I might be an early adopter with creative tools like Canva but closer to the early majority when it comes to something complex like AI in education. Understanding that fluidity helps me stay flexible and empathetic toward others who approach technology differently.
To keep growing, I want to keep learning actively through communities such as instructional design networks. I like to experiment with intention, trying new tools through small projects or pilots so it stays manageable. I also keep ethics and inclusion at the center, always thinking about how tech affects different learners, especially those who face barriers. I plan to use my WOL blog through the LDT path to help me reflect and track how my comfort with innovation evolves over time. For me, growth is about staying aligned with purpose. I don’t need to chase every trend; I just want to understand the ones that truly make learning and connection better.
Seeing myself between the Early Adopter and Early Majority categories helps me make sense of my relationship with technology. I’m comfortable taking initiative and exploring what’s new, but I also value structure, evidence, and intention. That balance is what makes me adaptable as both a learner and a designer. Technological innovation is about balance. I believe it is important to know when to try something new and when to slow down, when to use automation and when to stay human. The tools will always evolve, but what really matters is using them to create learning experiences that feel thoughtful, inclusive and improve the conditions of humanity.
Porter, W. W., & Graham, C. R. (2015). Institutional drivers and barriers to faculty adoption of blended learning in higher education. British Journal of Educational Technology, 47(4), 748–762. Portico. https://doi.org/10.1111/bjet.12269
Rare. (2015). Diffusion of Innovation Theory: The Adoption Curve. YouTube. https://www.youtube.com/watch?v=9QnfWhtujPA
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