#cognitive-load

#cognitive-load

A 2017 study from the University of Texas at Austin found that the mere presence of a smartphone on a desk (face down, silenced, untouched) reduced available cognitive capacity. Participants performed worse on tasks requiring sustained attention, even when they weren't using the device. The researchers called it "brain drain." Your mind allocates resources to not checking your phone, leaving less bandwidth for the task in front of you.

What fuels one person's energy may drain another. For instance, some people thrive on early morning workouts and feel ready to take on the day. For others, the same routine leaves them tired before the day even starts. Can you relate? These differences aren't signs that something is wrong with you-they're messages from how your nervous system is built to operate.

Parents tell me this all the time, often with a mix of frustration and worry: My child just can't focus the way I could at their age. School feels harder. Emotions escalate faster. Distraction seems constant. But attention isn't a moral trait. It isn't a virtue some children have and others lack. Attention is a cognitive capacity-and it is deeply shaped by the conditions surrounding a child: sleep, stress, sensory overload, and the environment in which we're asking focus to happen.

Progressive disclosure is a well-known principle in UX design. This principle is about showing users only what they need right now, and revealing more options or information gradually as they interact or gain context. The goal is to reduce cognitive load, keep interfaces clean and approachable, and still support advanced use cases when needed. The principle of progressive disclosure can be applied not only to the user interfaces we design, but also AI tools we use.

The industry is pivoting (again) to short-form vertical video right when audiences are exhausted by algorithm-driven feeds and seeking refuge from visual overload. Social media traffic is declining. Platforms have deprioritized our journalism. And yet, newsrooms are doubling down on the very formats audiences are abandoning, convinced we just need to tell the story in a faster or slicker manner.

Ask any instructor what helps students learn, and it's unlikely any of them will answer "a really big wall of text". It's incredible to me, as both a university instructor and a UX designer, that the army of people working at OpenAI are not imagining better tools for our students. I want to walk you through a design pattern in ChatGPT that, despite its good intentions, might be creating unintended hurdles for students.

Ask any instructor what helps students learn, and it's unlikely any of them will answer "a really big wall of text". It's incredible to me, as both a university instructor and a UX designer, that the army of people working at OpenAI are not imagining better tools for our students. I want to walk you through a design pattern in ChatGPT that, despite its good intentions, might be creating unintended hurdles for students.

In both learning and advertising, one challenge remains constant: capturing attention in a world full of distractions. While Instructional Designers focus on structuring knowledge, advertisers focus on visibility, clarity, and instant comprehension. Surprisingly, the same visual communication principles that make an ad effective can also make eLearning more intuitive, engaging, and memorable. Having worked closely with visual communication in high-traffic environments, I've seen how small design choices influence how people notice, process, and retain information.

When my order arrived, I kept wondering how I could've missed something so obvious. The answer? Selective attention - our brain's way of focusing on what seems most important in the moment, while filtering out the rest. Cognitive principles like selective attention shape every user interaction - what people notice, remember, learn, and even the mistakes they make. Apply them thoughtfully, and you can reduce mental effort, guide users' attention, ease recall and retention, and even motivate users.

Voice-over adds a human dimension to digital learning. It guides learners through content, clarifies complex ideas, and creates a sense of presence that static text and visuals alone cannot achieve. In asynchronous environments-where learners navigate content independently-it serves as a virtual instructor, offering structure, tone, and emphasis that help learners stay focused and emotionally connected. Enhancing Engagement And Attention One of the most powerful benefits of voice-over is its ability to anchor learner attention.

Recently, I was asked to work on a platform for an industry facing real headwinds. Layoffs and overwork have left many people drained, and the question from the client was simple but profound: can design ease some of that mental burden for the people using our platform? Not with gimmicks or forced fun, but with subtle sparks of relief. When we talk about ease, two factors consistently emerge in both psychology and design research:

Real-time dashboards are decision assistants, not passive displays. In environments like fleet management, healthcare, and operations, the cost of a delay or misstep is high. Karan Rawal explores strategic UX patterns that shorten time-to-decision, reduce cognitive overload, and make live systems trustworthy. I once worked with a fleet operations team that monitored dozens of vehicles in multiple cities. Their dashboard showed fuel consumption, live GPS locations, and real-time driver updates.

As a runner, I have often imagined what it would be like to have super speed like the Flash or Quicksilver. Unfortunately for my super speed dreams, Kyle Hill has presented the fatal flaws of super speed. But while Hill did consider the problem of perception, he seems to have missed one practical problem with being a super speedster and that is how mentally exhausting (and boring) running a super speed could be. Kant can help explain this problem.

Participants with the strongest, most distributed neural networks (i.e., they used more of their brain) didn't use technology. The more technology participants used, the less they used their brains.