In my first blog post of this semester, written after the lo-fi prototyping session, I described a frustration that felt more important than the prototype itself. Moving from theoretical research into a quick physical test forced me to confront something I had been postponing: my topic is difficult to make visible. Attention, interruption and cognitive recovery are not things you can easily point at on a screen. They happen internally, across time and often become visible only through their consequences.
At the time, that post was mostly about the limitations of the format I had tested. Looking back, it was also the beginning of a more important question. If the topic I am researching is hard to prototype, then maybe the issue is not only the prototype. Maybe I had not yet defined clearly enough what kind of design problem I was actually trying to make visible.
This post continues that questioning.
Where the First Semester Left Off
Last semester I wrote ten posts about attention, flow, interruption, memory, emotion, and neuroadaptive interfaces. Taken one by one they look scattered. Taken together, they were building toward something I could not yet name.
The clearest position I reached was in my final post: interruption is not a problem to eliminate, it is a condition to design for. What matters is not whether a system interrupts, but whether it does so at the right moment, with the right cost, and with enough support for the user to recover.
That framing felt like a conclusion at the time. Looking back, it was more like a door. The research had built a detailed picture of what goes wrong attention fractures, cognitive load spikes, emotional friction accumulates, memory decays but it had not yet said what to do about it, in what context, using what kind of design.
That is what this semester is supposed to resolve.
A Detour That Wasn’t Really a Detour
Earlier this semester I joined a project connected to CERN’s IdeaSquare initiative through our university. My group was working on individual and communal spaces, specifically the idea of modular, adaptive environments that can shift and reconfigure themselves in response to the people using them.
At some point during the project I pushed the team toward a particular angle: spaces that adapt to their users, not the other way around. The environment should read who is there, what they are doing, and what they need, then reorganize accordingly. Less about static design and more about responsive systems.
I did not connect this to my research at the time. It just felt like the right direction for that project.
Later I realized I had done exactly the same thing I had been studying. The question I brought into that spatial design project was the same question underneath my first semester work: what would it look like if systems adapted to human state, rather than expecting humans to adapt to them? In the CERN project, the system was a physical space. In my research, it had been a digital interface. But the logic was identical.
That overlap was worth noting. Not because it proves anything, but because it confirmed something: this is not an academic interest I adopted for a class. It is genuinely how I think about design.
The Problem With Where I Was
After last semester, I had a topic cluster but not a research direction. There is a real difference. A topic cluster is a set of connected ideas you can read about indefinitely. A research direction has a specific question, a context, and a method.
My cluster was attention, interruption, cognitive load, recovery, neuroadaptive systems. Interesting and defensible, but I was circling the same ideas without committing to a specific design problem.
The first blog post of this semester already hinted at this. The lo-fi prototype did not fail because the topic was weak. It struggled because I was trying to represent an internal and temporal topic before fully deciding what form of intervention I was actually designing toward. The session was useful precisely because it exposed that gap.
The second semester also added a different kind of pressure. The business-framing exercises pushed me to specify who is affected, how and what a system would actually do. Together with the prototyping difficulties, this made clear that narrowing was not optional anymore.
What I Actually Want to Research
The direction I have arrived at is best described as adaptive interaction design.
Not notification management. Not UX for focus apps. The broader question is what it would mean for interfaces to adapt their behavior based on the user’s current cognitive state, rather than treating every moment as equally available for input, output, or interruption.
The interest in neuroadaptive and EEG-based systems from last semester was never really about brainwaves. It was about the interaction logic they represent: a closed-loop system that reads the user continuously and responds accordingly. That loop, not the hardware, is what I find compelling. The philosophical stance is that machines should adapt to humans, not the other way around. The sensor stack is just one implementation of that idea.
What has become clearer this semester is that newer forms of adaptive systems make this question even more urgent. When systems act, update, or reorganize information while the user is absent, the moment of return becomes a design problem in itself. My earlier research on interruption, memory, and resumption maps directly onto this. The cognitive science is already there. What is still missing is a clear design response.
Where This Is Heading
I am not committing to a final thesis question this semester. That is not what this phase is for. What I am committing to is a direction: adaptive interaction design, specifically the intersection of cognitive state, interruption, and resumption in contexts where systems change while the user is absent.
The medium is still open. It could remain screen-based. It could later move into spatial or wearable contexts if the research actually needs that. I do not want to decide the form too early.
What I want to do this semester is go deeper into the literature on workload-aware systems, neuroadaptive interaction, and newer adaptive interface models, then develop a prototype concept that makes the re-entry problem testable. Not to solve it immediately, but to make it visible enough to study.
The first blog post of this semester started with a prototype that revealed the limits of my current framing. This post is the continuation of that realization. The question is no longer only how to prototype interruption and recovery. It is how to define a research direction where adaptation itself becomes the design material.
That is the point I seem to have reached. Now the next task is to see whether I can narrow it without losing what made it interesting in the first place.
