I'm Reevaluating the Curve
Hill with winding road
One of the courses I took in my Learning Design and Technology Master’s program required us to use an AI text generator to write a 450–500-word children’s folktale. The story was to be written about a specific endangered species of animal provided to us by our instructor. After experimenting with prompting (which I am learning is going to be an invaluable skill early on), the text was completed to my liking. An AI-generated text-to-speech program was used to read the story out loud. The next step involved the graphical component of the assignment. Using an AI graphics design program, such as Adobe Firefly, to generate 25-30 relevant images to accompany the storyline. The end goal was to produce an approximately three-minute video by combining the audio story with the images, which were inserted at the right time. We were to use DaVinci Resolve to put the video together.
With that context established, I think I am just beginning to understand the power of generative AI and how it will play a role in learning design. While researching this assignment, I realized the sheer number of text-based AI generators: ChatGPT (already familiar), Perplexity, Bing, and how handy each one was. Some did a better job than others. I learned that prompting mattered when it came to each of the different generators. Allowing AI to do the heavy lifting, such as writing out a common standard set of operating procedures or methodologies, and allowing a designer to customize the generated information, can save innumerable hours.
I’d never used graphical design AI, and the folktale writing/image-generating project using AI was especially eye-opening. While not having any real experience with other graphic AIs (Midjounery, Dall-E 2, Bing Image Creator, DreamStudio, NightCafe, GetImg.ai) I found Adobe Firefly to be incredibly easy to work with and generated, for the most part, applicable results. The folktale experience gave me mixed feelings. My immediate reaction to the graphics generator was mixed. I cannot express the number of hours I struggled with finding or creating applicable graphics in my previous design life when I didn’t have access to dedicated graphic designers. Tools like Adobe Firefly feel like a godsend. The specificity of content and quality of the AI generators was astounding and immediate. It would have taken weeks for me to have had access to that quality of pertinent content rather than minutes. While I understand the reticence of using AI and the potential threat to someone’s occupation, I truly believe the benefits outweigh the potential negatives.
Having been exposed to so many new tools, I have reassessed my position on the innovation curve. Now, I believe I am a more middle-of-the-road “early-adopter”, that is, further away from an innovator than I once was. The change stems from exposure to the sheer number of tools available and the rapid rate of growth and improvement of these tools. Designers are no longer relegated to stodgy eLearning development platforms and sometimes uninspiring Microsoft Office applications.
I believe the rate of advancement will require much more time on the job, learning and practicing using new tools. This time and cost will, of course, need to be built into the development timeline. Additional budgetary considerations for professional development and software licensing will need to be baked into the new costs of the training. The timeliness of upskilling an organization’s workforce will be crucial if that organization is to remain relevant and competitive. If I am to remain part of that workforce in some capacity (I’d rather be on the management/project management side of L&D), knowledge of these emergent technologies will be required. If working within an organization, I will need to be more self-assertive and a better self-advocate. If self-employed, professional development will be a necessity- feast or famine. Having said this, my own learning and professional growth will need to be more structured and intentional. Rather than waiting for the opportunity to be presented to me for training, I need to go and find those learning opportunities proactively.
I anticipate that all these factors will shape my approach to future technological advancements. As I work to stay current with trends, I will incorporate these technologies where applicable and supportive of the salient learning methodologies. These technologies offer various benefits, including enabling self-paced learning, supporting multiple learning styles and environments, fostering a more inclusive and engaging learning experience, integrating real-world applications, championing lifelong learning, and leveraging emerging technologies to create impactful and innovative, personalized learning experiences.
I believe that my workflow will also change because of some of these technologies, such as generative AI. AI has the potential to carry some of the burden currently carried by designers (such as graphics generation). This can open up time in the project timeline to analyze and evaluate educational efficacy and identify potential areas for improvement. These refinements manifest via an iterative approach for design improvement. The approach allows for continuous improvement and refinement of the learning experience through repeated cycles of design, development, and evaluation. Unlike the traditional linear approach, iterative design enables designers to incorporate changes and adjustments as needed, resulting in a more flexible and adaptive learning solution. In the context of eLearning, iterative design involves developing and revising each element of the project before moving on to the next stage, allowing for extensive feedback and course evaluation to create a polished end product. As new technologies become available and existing technologies evolve or are repurposed, the iterative approach to design allows these technologies to be worked into the deliverables through the cyclical design process.
