Kelly S. Steelman

Great expectations: top-down attention modulates the costs of clutter and eccentricity.

An experiment and modeling effort examined interactions between bottom-up and top-down attentional control in visual alert detection. Participants performed a manual tracking task while monitoring peripheral display channels for alerts of varying salience, eccentricity, and spatial expectancy. Spatial expectancy modulated the influence of salience and eccentricity; alerts in low-probability locations engendered higher miss rates, longer detection times, and larger costs of visual clutter and eccentricity, indicating that top-down attentional control offset the costs of poor bottom-up stimulus quality. Data were compared to the predictions of a computational model of scanning and noticing that incorporates bottom-up and top-down sources of attentional control. The model accounted well for the overall pattern of miss rates and response times, predicting each of the observed main effects and interactions. Empirical results suggest that designers should expect the costs of poor bottom-up visibility to be greater for low expectancy signals, and that the placement of alerts within a display should be determined based on the combination of alert expectancy and response priority. Model fits suggest that the current model can serve as a useful tool for exploring a design space as a precursor to empirical data collection and for generating hypotheses for future experiments.

Breaking Digital Barriers: A Social-Cognitive Approach to Improving Digital Literacy in Older Adults

The ability to navigate the ever-changing world of digital technology is a new form of literacy, one that presents a considerable challenge to older adults. Digital literacy has quickly evolved from an option to a necessity, and the rapid pace of technological change makes it insufficient to simply teach older adults to use a single technology. Rather, they must develop flexible skills and technological self-efficacy in order to maintain their hard-earned digital literacy. For four years, our research group has led a digital literacy program to address older adults’ questions about digital tools and applications. Through our work, we have identified numerous socio-technical barriers that older adults encounter as they adopt new technology and explore the digital world. Here, we review these barriers, discuss the Social Cognitive Theory that informs our tutoring approach, and describe our ongoing work to formalize the training program and develop technology to support older adults online.

Breaking Barriers to Digital Literacy: An Intergenerational Social-Cognitive Approach

In entering the digital realm, older adults face obstacles beyond the more clearly understood physical and cognitive barriers traditionally associated with accessibility. This experience report is a collection of narratives from learners and student tutors who participate in our digital literacy sessions for seniors. We point out ways in which attitudes and motivations, framed by social and cultural factors, can either hinder or assist with adoption of commodity digital technology among older newcomers. We also show how a social-cognitive approach can help learners overcome barriers to digital literacy.

Eliciting Best Practices in Digital Literacy Tutoring: A Cognitive Task Analysis Approach

Responding to the increasing need for all citizens to be digitally literate, our research group has led a program for six years that addresses older adults’ questions about digital devices and applications. Our patrons confront a range of socio-technical barriers as they adopt new technology and explore the digital world, and our tutors have developed particular practices to identify and overcome these barriers. Using a cognitive task analysis methodology, we conducted semi-structured interviews with experienced tutors. From these, we derived a set of effective and replicable practices that can form the basis for similar programs elsewhere.

Visual Attention and Display Design

Human operators in aviation, process control and other high-stress domains must monitor constantly for warnings and alerts among a rush of visual stimulation. More prosaically, website visitors and software users scan their computer screens for interesting or useful information among icons, online advertisements and other visual clutter. In all of these cases, performance hinges on the effective functioning of visual selective attention to find and extract useful information from the visual environment (Eriksen & Hoffman, 1973; Posner, 1980). At their best, failures of visual attention cause slowdowns and annoyances. At their worst, they cost lives and property. Well-designed displays that allow the viewer to readily find and extract the information required for the task at hand are crucial for efficient and safe performance of complex human—machine systems (Johnson & Proctor, 2004; Moray, 1993; Wickens & Holland, 2000; Wickens & McCarley, 2008).

Ground Vehicle Driving Aids: Assessing Driver Workload and Performance in Degraded Visual Environments

To enable indirect-driving maneuverability and threat detection in degraded visual environments (DVE), TARDEC’s ground DVE program is developing and testing a range of sensors and driver aid display systems. The current paper presents the first in a series of three simulator studies. It examined driver performance with two of the candidate driving aids, the Lane/Road Departure Warning System (LRDWS) and Optic Flow Enhancer (OFE), in three levels of degraded visual environment. Results indicated that the LRDWS best supported drivers in degraded visual environments, eliciting the lowest workload ratings and highest system usability ratings and facilitating faster driving in severe DVE conditions, with no apparent speed-accuracy tradeoff.

Identifying and Mitigating Technology-Related Anxiety

Our experience with digital literacy tutoring for older adults confirms other research that identifies technology-related anxiety as a significant barrier for this constituency. Based on established theories of instructional design, we hypothesize that anxiety impairs the development of digital literacy skills by consuming critical cognitive resources. Our research with experienced tutors reveals numerous strategies for mitigating anxiety and motivates the development of anxiety-aware instructional and design frameworks, and new anxiety scales that better reflect current devices, services, and threats.

Breaking barriers, building understanding: a multigenerational approach to digital literacy instruction for older adults

In entering the digital realm, older adults face obstacles beyond the more clearly understood physical and cognitive barriers traditionally associated with accessibility. One of these obstacles, technology related anxiety, is particularly problematic because it discourages exploration and wayfinding, two behaviors critical to the development of digital literacy. As educators at a rural, technologically-focused university, we see opportunities to address this issue and bring isolated older adults into a larger digital community, while simultaneously offering our students with valuable first-hand experience learning about and addressing the challenges faced by capable people struggling with unfamiliar technology. Here, we describe our social-cognitive approach to training digital literacy skills, pairing university student tutors with learners from the local community.

Exploring the Future of Human Factors Education: Online Learning, MOOCs, Next Generation Standards, and the Technological Skills We Need to Impart

The objective of this panel was to examine how the future of human factors education is changing given the influx of technology, a push for online learning, and adapting to the changing market. The panel will begin by Heather Lum briefly giving an overview and the precipice for this discussion panel. The panelists will provide their views and experiences regarding this topic. Kelly Steelman will discuss the potential for MOOCs and other online formats to create faster and more flexible postgraduate programs. Christina Frederick will discuss her perspectives on the technological skills we should be equipping our human factors graduates with to be successful. Nathan Sonnenfeld will give his unique take on this as a graduate student currently obtaining a human factors education. Susan Amato-Henderson will discuss the Next Generation Science Standards and the ramifications for educators. Lastly, Thomas Smith will focus on the advantages and disadvantages of online learning at the K-12 level. Dr. Lum will foster discussion among the panelists and questions from the general audience. Discussion time: 90 minutes.

Predicting Detection Times with Perceptual Euclidian Distance

How should we select a set of symbol colors to optimize detection times? Here we suggest a simple, easy- to-calculate technique for predicting symbol detection times in cued and uncued visual search tasks. We used Perceptual Euclidian Distance (PED) to measure color similarity among symbols within the set (PEDset) and between each symbol color and the background color (PEDbg). Post hoc analyses of data from two previous change-detection experiments indicated that PEDbg was negatively correlated with detection time, but only in uncued visual search. PEDset, in contrast, was negatively correlated with detection time in cued search. In the current experiment, we designed a new symbology set that included three symbols that were equidistant in PED color space and a fourth symbol that was farther away in PED color space. We used this symbol set in a change detection experiment using the flicker paradigm. Consistent with the results of our previous analyses, we found that cued detection time was correlated with PEDset. Finally, we present a summary of data from seven experiments demonstrating that this pattern of effects holds over a variety of background colors and symbol sets. The overall results suggest that the PED may serve as an easy-to-use technique for selecting symbols that will facilitate particular performance objectives.