Tiffany S. Jastrzembski

Light pen use and practice minimize age and hand performance differences in pointing tasks

We contrasted performance with mouse and light pen input devices for younger, middle-aged, and older adults (N = 72) who were experienced mouse users. Participants used both preferred and nonpreferred hands to perform a menu target selection task. The light pen minimized age differences in performance relative to the mouse. Older adults were more lateralized on a handedness test than young adults and were less efficient using their nonpreferred hand. With practice, older adults improved their response time more than other age groups did. The mouse was rated as more acceptable and easier to use than the light pen across trials, despite the performance advantage of the light pen for all age groups. Usability ratings correlated moderately with performance. A benefit-cost analysis indicated that the more efficient light pen might cover its greater initial cost within 11 months for an older adult and within 23 months for a younger adult. Actual or potential applications of this research include advising older adults to persist with practice for new input devices, advising those who must switch to their nonpreferred hand to select a direct positioning device, and providing a methodology for determining the potential payback interval when switching to a faster, though more expensive, input device.

The Model Human Processor and the Older Adult: Parameter Estimation and Validation Within a Mobile Phone Task

The authors estimate weighted mean values for nine information processing parameters for older adults using the Card, Moran, and Newell (1983) Model Human Processor model. The authors validate a subset of these parameters by modeling two mobile phone tasks using two different phones and comparing model predictions to a sample of younger (N = 20; M-sub(age) = 20) and older (N = 20; M-sub(age) = 69) adults. Older adult models fit keystroke-level performance at the aggregate grain of analysis extremely well (R = 0.99) and produced equivalent fits to previously validated younger adult models. Critical path analyses highlighted points of poor design as a function of cognitive workload, hardware/software design, and user characteristics. The findings demonstrate that estimated older adult information processing parameters are valid for modeling purposes, can help designers understand age-related performance using existing interfaces, and may support the development of age-sensitive technologies.

Expertise and age effects on knowledge activation in chess

Novice, intermediate, and expert chess players of various ages, playing with two chess pieces on a quarter-section of a chessboard, performed a simple task to detect that the king is in check or is threatened with being in check. Age slowed response for both tasks. An interaction of task and skill revealed differences in diminishing response time between check and threat tasks as skill increased; experts were equally fast on both tasks. Measures of speed and working memory were negatively related to age but unrelated to skill. Skill did not mitigate age-related effects on speed of detection. These results suggest that knowledge-activation processes necessary to assess basic chess relationships slow with age, even in experts.

Input devices for web browsing: age and hand effects

The work reported in this paper examined performance on a mixed pointing and data entry task using direct and indirect positioning devices for younger, middle-aged, and older adults (n=72) who were experienced mouse users. Participants used both preferred and non-preferred hands to perform an item selection and text entry task simulating a typical web page interaction. Older adults performed more slowly than middle-aged adults who in turn performed more slowly than young adults. Performance efficiency was superior with the mouse for older adults only on the first two trial blocks. Thereafter mouse and light pen yielded equivalent performance. For other age groups, mouse and light pen were equivalent at all points of practice. Contrary to prior research revealing superior performance with a light pen for pure pointing tasks, these results suggest that older adults may initially perform worse with a light pen than a mouse for mixed tasks.

Monitor viewing distance for younger and older workers

Rempel, Willms, Anshel, Jaschinski & Sheedy (2007) recommend 52–73 cm for eye distance to a computer monitor based on an experiment that manipulated viewing distance. Jaschinski (2002) found a preferred viewing distance of 63 cm. However, these and other studies of viewing distance used relatively small samples of young adults below age 40. In this study a representative sample of 206 university employees in two age ranges, <= 40 years and => 50 years, were observed in their offices at their computer workstations. Mean distance to the center of the screen was 68 cm (95% confidence interval: 66 to 71 cm). Regressions showed that factors such as gender, whether a lens was worn, type of monitor, monitor resolution, and monitor contrast ratio did not predict distance to screen. However, there was an age by job class interaction for viewing distances with younger faculty at 64 cm, older faculty at 71 cm, young staff at 73 cm and older staff at 67 cm. Reported eye strain was related solely to glare rating. Results indicate that monitor positioning guidelines are reasonable for older workers and that glare sources could be reduced in typical office environments.

What Older Adults Can Teach Us About Designing Better Ballots

FEATURE AT A GLANCE: In this article, we examine the interplay between electronic voting technology machine types (touchscreen vs. touchscreen + keypad) and ballot designs (full ballot vs. one office per page) that together comprise the interface to which voters are exposed. Using a gerontological approach, we show that determining the most usable system for voters with the most limited capabilities (in this study, older participants) also corresponded to higher performance across groups (younger participants). Because older adults are more sensitive to slight differences in human-computer interaction designs, examining their performance may help shed light on potential problems that could otherwise go undetected.

Aging and Input Devices: Voice Recognition Performance is Slower Yet More Acceptable than a Lightpen

Microcomputers are ubiquitous to modern society, yet older adults consistently perform more poorly than younger counterparts using standard input devices (e.g. a mouse). Prior research has revealed that direct positioning devices (e.g. light pen), minimize age differences and enable quick transfer to the non-preferred hand. This study investigates whether speech recognition may also reduce age-related declines and enhance performance of older adults in target selection tasks. Twenty-four participants ages 20–26 (M = 21.7), twenty-four participants ages 44-55 (M = 48.9), and twenty-four participants ages 65–78 (M = 70.4) were asked to select a specified target using either a light pen or speech recognition software (IBMs ViaVoice). Results revealed no age effects for type of device, but response times for target acquisition were approximately 2178 ms longer for speech recognition than the direct positioning device, and preference ratings were higher using speech as input versus the lightpen. Implications are discussed.

Videoconferencing Technology as Environmental Support for Older Adults

Age-related declines in cognitive abilities can sometimes be remedied for working memory intensive tasks by providing what Craik (1986) termed “environmental support,” for instance, using external memory cues to alleviate normal memory retrieval demands. We investigated a way-finding task that requires serial recall, a particularly challenging memory task for older adults. We compared videoconference versus voice-only guided presentation of routes to younger and older adults. Participants viewed or did not view maps containing the to-be-learned routes. Additionally, participants were allowed to take notes to simulate real-world situations more closely for half of the trials. Analyses indicate an interaction of age, notes, and map presentation at recall, suggesting environmental support from videoconferencing reduces the advantage of note taking for older adults. Videoconferencing can be a particularly effective presentation medium for older adults with respect to memory-intensive everyday tasks.

A Principled Account of the Older Adult in ACT-R: Age-Specific Model Human Processor Extensions in a Mobile Phone Task

In previous research, Jastrzembski & Charness (2007) estimated weighted mean values for nine information processing parameters for older adults using the Card, Moran, & Newell (1983) Model Human Processor (MHP) model, and successfully validated a subset of those parameters with age-specific GOMS models for two mobile phone tasks across two mobile phone devices. The current research extends the mapping of MHP parameters to the ACT-R cognitive architecture (e.g., Anderson, 2007), and transitions age-specific MHP parameters into theoretically-plausible ACT-R models of older adult performance. We argue that the incorporation of theoretically-motivated MHP parameters into ACT-R will produce better fits to empirical data than default ACT-R parameters, and the use of those theoretically-principled parameter values will provide designers with more precise insight concerning why hardware/software designs/devices work or fail as a function of age. We test these hypotheses in the same mobile phone domain used to validate the age-specific MHP parameters in previous research and our findings demonstrate that age-specific ACT-R models using elemental MHP parameter values achieve better fits than default ACT-R parameters. This research may provide designers and human factors engineers the ability to inspect details of human performance at a finer grain of resolution than is currently available, help determine the cause of specific errors resulting from hardware/software design, cognitive workload, or user characteristics, and support the development of age-sensitive technologies.

DataShopping for Performance Predictions

Mathematical models of learning have been created to capitalize on the regularities that are seen when individuals acquire new skills, which could be useful if implemented in learning management systems. One such mathematical model is the Predictive Performance Equation (PPE). It is the intent that PPE will be used to predict the performance of individuals to inform real-world education and training decisions. However, in order to improve mathematical models of learning, data from multiple samples are needed. Online data repositories, such as Carnegie Mellon University’s DataShop, provide data from multiple studies at fine levels of granularity. In this paper, we describe results from a set of analyses ranging across levels of granularity in order to assess the predictive validity of PPE in educational contexts available in the repository.