Beta Testing AI for Creative Work
This artifact documents my feedback while beta testing a course on generative AI in creative practice. The course introduced learners to several tools while encouraging reflection on the broader implications of AI in artistic work. I approached this project as both a learner and a learning experience designer, engaging critically with its structure, pacing, and intentionality. As I progressed through the lessons and activities, I documented where the experience felt intuitive or disjointed, especially for learners new to AI or digital creative tools. My notes reflect a dual perspective—immersed in the learner experience while zooming out to consider the learning design choices behind it.
Core Competencies
-
Applying Learning Theories and Design Frameworks
I engaged with the course’s structure through the lens of alignment and sequencing, paying close attention to how learning objectives were introduced and how they connected to the activities that followed. I observed opportunities to strengthen the clarity of module-level goals and transitions between concepts, particularly as learners encountered creative tools like MidJourney and MusicFX. These observations drew on my understanding of backward design and how clarity at the level of outcomes and sequencing can support learner orientation and confidence.
-
Using Research and Evaluation Skills
In this beta testing process, I approached the experience as a form of formative evaluation—documenting my own journey as a learner while identifying moments where the course could be even more intuitive and cohesive. I noted where tool demonstrations might benefit from additional context, and where earlier conceptual framing could better support learners encountering generative AI in creative contexts for the first time. My feedback aimed to surface these areas with specificity and, in service of refining an already promising and thoughtfully developed course.