completed in my Introduction to Instructional Design course using dummy data, so I was feeling a bit out of my depth. Following the instructions I had adhered to for the practice assignment, I began by identifying ten specific actions students would need to take to complete the course.

These steps included things like selecting variables from a dataset, calculating a mean, interpreting a correlation coefficient, and formatting results in APA style. I then broke down each primary task, identifying all related subtasks. From there, it became easy to identify the prerequisite knowledge or skills these students would need in order to be successful in fulfilling the task.

Instead of rushing into solutions, I treated this phase as a deep dive into the structure of the learning experience. This is where my analysis skills were tested and refined. The core questions started to sound like “What are the specific pain points? Where were the knowledge gaps? Which skills were foundational, and which could be layered on later?” Creating the inventory helped me stay focused on actual learner behaviors, not just abstract learning goals or content categories.

One of the most valuable parts of this project was refining my ability to write tasks that are both actionable and measurable. I wanted each item on the list to describe something a learner could clearly attempt, practice, and improve at. That meant being deliberate with language and aligning each task to a realistic learning context. For example, instead of saying “know how to analyze data,” the task reads “calculate and interpret a correlation coefficient using spreadsheet software.” It’s specific, measurable, and rooted in the final group project students would complete.

This task inventory also gave me a deeper appreciation for how much information can be surfaced through careful questioning and structuring. I had previously relegated the term “analysis” to the work of people scouring over highly technical data. But essentially, analysis is the discovery of patterns, identification of their significance, and amplification of their relevance to the problem being solved. I felt a clear shift in my own interest in becoming a stronger analyst upon this realization. 

an outsider with a unique chance to listen carefully and figure out what wasn’t working and why with no preconceived ideas of what the role should look like in the organizational context.

I spent weeks reviewing internal documents, talking with stakeholders, and gathering insight from people who had either served in the VISTA role or worked alongside it. I was pleased to find no shortage of information and immediate enthusiasm and support from my contact Nina Alomar. Admittedly, despite the support I had from the organization, the task of making sense of all of the information was daunting at first. I found myself having to constantly recalibrate and take one thing at a time. Once I got into a good groove, I realized the problem of the VISTA role’s shaky identity was likely a structural one. There were great people trying to do good work, but in the effort to keep the role flexible to fit an ideal candidate, ultimately the role as a piece of the organization as a whole lacked clear boundaries, consistent expectations, and institutional support leading to a variety of inefficiencies.

From a competency standpoint, this work really stretched me in terms of my technical analysis

skills. Having the chance to really dig into the situation and figuring out what was going on before making any decisions about design was as challenging as it was rewarding. I had to look at the context, the people, the workflows, the pain points and map it all out without oversimplifying or fabricating connections that did not exist. I do not think I would have been able to really learn anything about human-centered analysis if it had only existed in theory based lectures, but I felt it really clicked for me through this process.

I thoroughly enjoyed every step of this project. The final steps of compiling the final report presented here helped me get infinitely more comfortable with that constant toggling between the zoomed-out view and the on-the-ground realities. Although I had always been aware on a cognitive level that the analysis portion of design work heavily requires a strong security in the unknown, change, and uncertainty, this undertaking stretched what I thought I knew about myself in those areas. I think about this project fondly and am confident that it has provided me with a much clearer vision of who I am as a designer and the kind of work I want to be doing.