I'm Reevaluating the Curve

When I wrote my first WOL post, I placed myself between the Early Adopter and Early Majority categories. I’ve always been curious and willing to try new tools, but I also like to understand their purpose before committing. After a semester studying emergent technologies, I realized that being an early adopter is more complex than I initially thought.

This course pushed me to see technology beyond its features. I began thinking about who it supports, who it leaves out, and how design choices affect real learners. Concepts like accessibility, ethics, and user experience became central to how I evaluated new tools. I learned that innovation isn’t just about excitement. It requires discernment and an awareness of the responsibility that comes with choosing and implementing technology.

Where I Am on the Curve Now

At the start of the term, I confidently claimed the space between Early Adopter and Early Majority. Now, as I reflect on everything we’ve analyzed, debated, and experimented with, I find myself leaning slightly more toward the Early Majority than I anticipated. I still love exploring new tools such as AI assistants, creative platforms, formative analytics dashboards, microlearning apps, but my approach is more intentional now. The simple truth is that the more I’ve learned, the more I’ve realized how much I don’t want to adopt technologies blindly.

Instead, I want to adopt them ethically, equitably, and in alignment with learner well-being.

This shift doesn’t feel like a regression; it feels like maturing into a learning designer who understands the weight of these tools. Innovation isn’t just shiny; it has social, emotional, and ethical consequences for real people. And that awareness shapes how I see my role going forward.

How This Shapes My Approach to Future Technology 

Understanding where I sit on the innovation curve now directly influences how I plan to analyze and implement technologies in my career. Instead of asking, “Is this new?” or “Is this exciting?” my future questions will sound more like:

• Does this tool enhance accessibility and equity?

• Does it respect learner autonomy, data, and dignity?

• How does this technology change the role of the instructor or learner?

• Is it actually solving a problem or simply adding complexity?

• Who benefits and might be excluded?

In my experience, exploring technologies like AI has shown me how quickly systems can shift from helpful to problematic depending on how they’re deployed. Learning analytics demonstrated the potential for early intervention and personalized support, but also raised questions about privacy and surveillance. Microlearning showed how seamlessly learning can fit into everyday life, but also revealed how easily content can become fragmented or oversimplified if not handled well.

Moving forward, I plan to approach innovation as both a designer and an advocate. I want to embrace tools that genuinely improve learning outcomes, reduce barriers, personalize instruction, or create new pathways into knowledge, but I also want to challenge technologies that perpetuate inequity or prioritize efficiency over humanity.

Rather than rushing to adopt, I want to understand, evaluate, and then integrate with purpose.

Ethical and Social Considerations 

If there was one theme that shaped my movement on the curve, it was ethics. The speed of AI development is unlike anything I’ve ever witnessed, and while it opens extraordinary opportunities, it also raises profound questions about bias, privacy, labor, authorship, and the future of human creativity.

AI systems can personalize learning and offer immediate support, but they can also flatten nuance, reinforce stereotypes, and create dependencies if used carelessly. Learning analytics can help identify learners who need help, but they can also become tools of surveillance if institutions prioritize monitoring over empowerment. Microlearning can make content beautifully accessible, but it can also oversimplify complex ideas if used without intention.

One ethical dilemma that deeply resonated with me this semester was the role of AI in learner data collection. The idea that systems can track behavior, predict performance, or flag “at-risk” students before they even realize they’re slipping is powerful, but it also invites questions:

• Who has access to this data?

• How is it interpreted?

• Can these predictions become self-fulfilling?

• What biases exist in the model?

• How do we ensure transparency and consent?

These questions pushed me slightly away from my earlier early-adopter stance. Not because I distrust technology, if anything, I respect it more now. My thought process is that I take its implications more seriously knowing how powerful it  can be. I understand now that emerging technologies don’t simply require skill; they require judgment. In this sense, ethics becomes not an obstacle to innovation but a compass for it.

What This Means for My Future as a Learning Designer

Reevaluating the curve helped me better understand the kind of learning designer I want to become. I want to use emerging technologies in ways that genuinely support learners rather than overwhelm them. Some people see new tools as distractions or barriers, but I see them as opportunities to expand human capability when used intentionally. My goal is to help create learning environments where technology enhances accessibility, creativity, and understanding, not just efficiency. I want to use AI to support meaningful learning, analytics to guide rather than monitor, and microlearning to offer flexibility without losing depth.

This shift toward the Early Majority does not mean I am hesitant about innovation. It means I am taking it seriously. I want to approach new tools with a focus on problem solving and real human needs. In my future work, I hope to translate emerging technologies into clear, practical solutions that improve people’s experiences and help them succeed. Technology has incredible potential to make learning more equitable and empowering. I want to be part of designing it in a way that truly improves lives.

Conclusion

Looking back at the beginning of the semester, I am still optimistic about what innovation and emerging technologies could do. In addition, now I also see the designer who understands that innovation must be paired with wisdom. In the end, the curve isn’t just about how early we adopt, it’s about how responsibly we try to do it.

Thank you for reading,
Jeanie :)

I'm On the Curve

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. 

Thank you for reading!

Jeanie 

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

Designing for Connection: My Path into Learning Design & Technology

The intention I carry with me as I begin my journey in the Learning Design and Technologies program is the desire to be part of projects that will expand my knowledge and to become more of an empathetic designer, as well as blend the skills to other parts of my life. I felt inspired to pursue the Learning Design & Technologies program because of my background in early childhood education, digital marketing/sales, and belief that every person has their own unique blueprint for learning and growth. I’ve learned from my experiences that at the heart of education and business lies in meeting people exactly where they are rather than where we expect them to be. So in my LDT journey, I want to document here how I will be combining my hands-on experience with children and my creativity in digital spaces to design learning that feels accessible and personable.

My career path so far has not been linear, but filled with valuable lessons that all connected in a way. I have worked jobs in schools and corporate settings. In Early Intervention, I do one-on-one sessions for about an hour with toddlers  using play-based therapy. A two-year-old boy I worked with hardly spoke when we met and his parents were concerned with his play skills. Everyday I tried to add to his interests rather than directing his learning by following his lead. I was sort of a learning partner who guided his activities by observing his preferences and learning styles. Little moments such as him giving me eye contact, remaining in the room for more than ten minutes and mimicking sound effects were huge wins. After a few weeks, there was a day where he initiated play by calling for my name and handing me toys. That case taught me that learning takes root only when people feel safe, supported, and seen. His blueprint worked best through play, connection, and patience  and I carry that lesson with me into every new role.

I’ve also worked in sales and account management for a children’s toy company, which at first glance seems far from early intervention. But both experiences revolved around people, each with unique goals and ways of thinking. In sales, no two clients responded to the same pitch: one needed hard data while another connected with creativity and storytelling. In early intervention, I worked with families shaped by different cultures, resources, and stress levels. Each home carried its own energy and challenges. Whether working with a child, a parent, or a business client, I learned that honoring a person’s blueprint is the foundation of trust and meaningful outcomes.

This desire to recognize and design for different blueprints is what I bring into learning design. My background has taught me it is important to put myself in others' shoes, have curiosity to learn from the people around me and creativity to explore different solutions. I know the frustration of struggling as a learner, but I also know the joy of supporting someone’s breakthrough. I’ve worn many hats: therapist, marketer, student and creator, entrepreneur. Each one has shaped how I design with purpose and inspires me to keep trying. 

Design is about making learning meaningful, human, and alive. Creativity has always been the bridge that ties my experiences together whether it’s editing videos, photography, making an infographic, or designing a play activity for a therapy session. Making things that keep me feeling inspired and alive is the driving force behind what I do. I think my personal brand is the concept of continuous growth, creation and learning. 

My short term goal is to continue growing my skills in digital learning, while focusing on inclusive and empathetic approaches to education. I want to soak in as much knowledge as possible about multimedia design and learn how online learning communities can make digital learning more engaging and human-centered. From my experience, storytelling, visuals, and tone can help technology support social-emotional learning and make online education feel more personal. For the long term, I want to work with others to create environments where all learners can feel a sense of belonging and possibility. I see that coming to life where my work is the intersection of education, design, and creativity to amplify voices and create new ways of learning.

On my journey so far I am inspired by the messages of John Seely Brown and Bell Hooks who frame education as an act of freedom. From my prior classes, I drew on Seymour Papert’s constructionism, which encourages learners to build knowledge by making and creating. This is how I learn as well. More recently, incorporating Richard Mayer on multimedia learning and Karl Kapp on gamification into my projects have helped me think about designing digital spaces that are both effective and engaging. These people have influenced me to see that learning is not neutral and reflects the values of the designer. It’s important for me to also embody empathy into my designs. 

The WOL blog is an exciting space for me to look back on one day. It will serve as a living portfolio of my journey through the Learning Design and Technology program to reflect, share creative projects, and capture the lessons I learn. I would like to compile my works here and over time have it be an invitation to connect with others who care about learning in all forms. My vision is to design spaces where people feel seen in their uniqueness and supported in becoming who they want to be. That’s the future I want to shape alongside this community.

Personal Approach to Applying Learning Theory

This blog post shares my personal approach to applying learning theory in instructional design and how those theories have shaped my vision for creating engaging, meaningful learning experiences. Applying theory is what makes design intentional. Every decision from the way information is presented to how learners interact, is rooted in research and supports both engagement and retention. In this course, I applied these ideas through projects for SparkyWave Solutions, a fictional company provided as our case study.

Gamification and Behaviorism:

For my gamified learning experience on company policies, I relied on behaviorist principles to make it the experience effective and engaging. Points, badges and immediate feedback rewarded the right actions. The goal was to reinforce the desired behaviors and help make the information stick. I designed it so each part built on the last, keeping the flow clear and the objectives easy to follow.

I incorporated gamification elements such as storytelling, choice and the freedom to fail. This allowed learners to explore and master the concepts without the pressure of getting everything right immediately. The gamification mechanics were embedded into the content to make the learning experience more cohesive. I prioritized usability by having the layout and visual cues made it easy to navigate. From creating this learning experience, I noticed immediate reinforcement and thoughtful design can transform a stale company policy training to be more exciting and interactive.

Keller’s ARCS Model and Maslow’s Hierarchy of Needs: 

My infographic helps employees of Sparkywave Solutions navigate remote work using Keller’s ARCS model. To capture attention, I opened with a calm visual, a relatable quote, and a surprising statistic to spark curiosity (Park, 2018). Relevance came from addressing real challenges like isolation and work-life balance, supported by employee quotes to make strategies feel personal and applicable. Confidence was built through small, doable actions and tool suggestions, framed to promote self-efficacy. I closed with a recap, a clear next step to join the remote work Slack channel and an optional digital badge to leave users with a sense of progress and intrinsic satisfaction. This showed me how ARCS can make learning both engaging and practical. 

Mayer's Principles of Multimedia Learning and Cognitivism:

For this project, I designed a Remote Workplace Safety guide for SparkyWave Solutions using Mayer’s Principles of Multimedia Learning to make the content clear, engaging, and easy to retain. I applied signaling with bold headings, short labeled sections, and icons to guide attention. Segmenting was used by breaking the content into focused topics, so learners could process each area at their own pace. Personalization was incorporated through a conversational, supportive tone to encourage reflection and action. Cognitivist strategies was weaved in by organizing information into labeled chunks to support schema-building, using real-world tips to connect to prior knowledge, and ending with a prompt to promote deeper encoding. Every visual added was to reinforce the message and create a clear connection. These  approaches made the guide practical and memorable, supporting both immediate application and long-term retention.

Constructivism and Community of Inquiry:

I followed the framework and applied the concepts #real-world-problem-solving Slack channel. I started by defining the channel’s purpose as an online community for employees to exchange ideas, and develop solutions together. The kickoff activity invites members to post a real work challenge, add context, read others’ posts, and offer thoughtful solutions. I included ways to guide the discussion with examples and feedback, encourage connection through friendly acknowledgments and personal touches, and keep conversations focused with follow-up questions and shared resources. I also made space for empathy, recognition, and ongoing check-ins to help build a supportive community.

Generative AI, Self-Determination Theory and Transactional Distance Theory

I created a quick pitch for an AI-enhanced cybersecurity training module for SparkyWave Solutions and turned it into a video presentation. The needs assessment showed that the company’s current training was text-heavy, one-size-fits-all, and left remote learners feeling disconnected.

Using Self-Determination Theory, I designed the new module to give employees more control. They could choose a learning path based on their role and pick how to show mastery. It could be through a simulation, report, or presentation, making the experience more relevant and motivating.

To apply Moore’s Theory of Transactional Distance, I added a 24/7 AI “Cyber Coach” that answers questions instantly, breaks down concepts into plain language, and recommends resources tailored to each learner’s progress. The module included small “threat response teams,” discussion spaces, and a clear, role-based sequence to keep learners connected, engaged, and supported.

Connecting the Dots: 

I noticed that by creating these learning modules, I can see what works best for me as a learner too. Effective learning design centers on the learner. It looks at the learner’s role, background, and how they like to engage. An IT hire might need more hands-on practice, whereas a manager could gain more from case studies and policy examples. Training is useful rather than something to complete when it allows people to choose their path, learn at a pace that works for them, and work on challenges that feel real keeps the training useful. AI can be supportive in many ways from catering to learning styles or emotional needs such as encouragement and affirming. Peer interaction creates a sense of community and shared problem-solving. Feedback that’s specific and timely builds confidence. When the design adapts to the learner instead of having everyone into the same mold, it encourages motivation, ownership, and skills that last.

Connectivism and Networked Learning:

Connectivism and networked learning show how growth comes from linking to people, ideas, and resources. I connect with this because I can earn by reading others’ discussion posts, reflecting on their perspectives, and applying them to my own thinking. Although I don't completely engage in conversation with others, I stay engaged through observing others work and reflection it to the information being taught This approach reinforces that learning is continuous and network-driven, and as a designer, I aim to create spaces where learners can connect, explore, and grow in ways that fit their own style.