Ben Shelton
Senior Manager, User Experience & Business Improvement
The University of Newcastle, Australia
Designing for the Mind: Using Cognitive Load to Measure UX Effectiveness
Friday, 28 August
Designing for the Mind: Using Cognitive Load to Measure UX Effectiveness
User experience design often focuses on usability, accessibility, and task success. But even when users complete a task successfully, an interface may still be demanding unnecessary mental effort.
Every extra decision, notification, unclear hierarchy, or fragmented workflow adds to the cognitive load users must manage. These costs are rarely visible in traditional usability metrics, yet they directly affect attention, performance, and user satisfaction.
Cognitive Load Theory offers a way to make this invisible cost visible.
In this talk, Dr Ben Shelton and Cordelia Prangley introduce how cognitive load can be used as a practical lens for evaluating interface effectiveness. Drawing on research from educational psychology and calm technology, the session explores how mental workload influences user performance, decision-making, and attention.
Attendees will learn:
- How cognitive load affects user performance and decision quality
- The relationship between perceptual load, attention, and interface complexity
- Practical techniques for identifying cognitive overload in real products
- How cognitive load insights can lead to calmer, more effective digital experiences
If we want technology to feel effortless, we need to understand the demands it places on the human mind.
Ben Shelton
Dr Ben Shelton is a Human–Computer Interaction researcher specialising in human-centred design and Senior Manager, User Experience & Business Improvement at the University of Newcastle.
His work bridges cognitive science and applied UX practice, exploring how Cognitive Load Theory can be used to measure interface effectiveness and reduce digital noise.
Ben’s research spans higher education user experience, ubiquitous computing, and workload measurement, with a focus on designing systems that support attention rather than compete for it.