learning, aging, & cognitive ergonomics lab

Current Research

Optimal Feedback for Learning
The question of how to deliver feedback has been studied for many years, but results often conflict with one another. For example, some research suggests that the more feedback you can provide to a learner, the faster and more thoroughly they can absorb information. However, other research demonstrates that too much feedback becomes a crutch for performance, and the person never really learns the material or task. Not only does the answer to this question have direct application to how we train our teachers in the school system, it applies just as well to online courses and learning how to use computer programs.

Even if we did understand how much feedback to give a school-age learner, it is likely the answer would differ for older adult learners. Our research addresses these topics simultaneously: it is an attempt to develop a theory of learning through feedback for learners of all ages.
McLaughlin, A. C., Rogers, W. A., & Fisk, A. D. (2006). A new framework for understanding the effects of feedback on learning: The controlled resource approach. Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society
Kelley, C. M. & McLaughlin, A. C. (2008). How individual differences and task load may affect feedback use when learning a new task. Proceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society
McLaughlin, A. C., Rogers, W. A., & Fisk, A. D. (2008). Feedback support for training: accounting for learner and task. Proceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society
Kelley, C. M., & McLaughlin, A. C. (2009). Feedback specificity requirements for learning in younger and older adults: the role of cognitive resources and task demand. Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society.
Human Factors and Cognitive Maintenance
The idea that mental exercise can improve cognitive ability into old age is currently popular. However, some studies find this effect and others do not. Exactly what type of "mental exercise" shows an effect and what types are just marketing and hype? The LACElab is currently working to identify whether active engagement and presence in a task or environment could be one type of exercise to improve cognition. This work is in collaboration with Maribeth Gandy, a Senior Research Scientist at the Georgia Tech Interactive Media and Technology Center and Dr. Jason Allaire of the Cognitive Aging in Context Lab at NCSU.

As we are interested in how interaction with technology can produce changes in ability, we are investigating what characteristics must be present in games or other cognitive exercises. In this project, we will produce guidelines for technology to improve the cognitive abilities of older adults.

This work is funded by the National Science Foundataion and a detailed description of current experiements can be found at our Gains Through Gaming Lab website.
Whitlock, L. A. & McLaughlin, A. C. (2009). The Role of Effortful Attention in Effective Spatial Training. Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society.
NSF Award Information
Training and "Smart" Warnings for Agricultural Workers
Our short term goals include providing the community with a comprehensive resource for agricultural population variables and accident data. We also aim to catagorize potential risk situations to discover what types of risk may be ameliorated via adaptive training and smart warning systems. Accomplishing these two goals will allow us to develop and test an individualized smart warning system.

Our long term goal is to develop a process by which effective smart warning systems may be developed a priori then refined by user testing. Currently no such process exists. This process may be fitted to multiple contexts that are similar to the agricultural risk environment, such as automobiles and other multi-task scenarios.
McLaughlin, A. C., Fletcher, L. A., & Sprufera, J. (2009). The aging farmer: human factors research needs in agricultural work. Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society.
HCI on Small Screens
As mobile devices become ubiquitous, the demand for mobile visualization applications (MVAs) is growing. In Apple, Inc.’s App Store, there are thousands of applications that use various techniques to visualize data in such categories as games, music, healthcare and fitness, productivity, utilities and education. In most MVAs the user subjectively zooms in on subsets of information. Unfortunately, subjective zooming has the consequence of requiring that the user organize those subsets in working memory. Performance tends to degrade as working memory demand increases. One potential solution to the increased load of subjective zooming is to transfer some of the burden to the mobile device. According to cognitive load theory, reducing the extraneous load of a task results in higher performance because it frees up cognitive resources that are then available to apply to the task. A sequential zooming technique can reduce extraneous load by having the MVA organize the information subsets into a logical order while simultaneously avoiding subset overlap.The present line of research investigates how particular mobile visualizations can reduce the cognitive load of a visuospatial task.
Luong, M. G. & McLaughlin, A. C. (2009). Bar Graphs and Small Screens: Mitigating Cognitive Load in Mobile Visualizations. Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society.

Back to Top