Icon Identification Research Articles

Developing icons for older adults: The roles of icon design categories, text labels, and learning strategies

When using electronic devices, older adults usually face challenges associated with difficulties in understanding icons. This study investigated age-related differences in icon identification using various design principles (Experiment 1), as well as the impacts of adding text labels (Experiment 2) and learning strategies (Experiment 3) on improving the performance of older adults. Participants, including older adults (aged 60 or older) and younger individuals, were asked to identify icons matching previous descriptions. The results revealed that the identification performance between older and younger adults varied across icon categories. The addition of text labels resolved differences in icon comprehension related to age of participant and design principles. Learning strategies had diverse effects on the identification performance of older and younger participants, depending on the icon category. These findings provide guidance for designers to apply effective principles and identify optimal strategies to support older adults in the identification and understanding of icons.

Effects of Users' Familiarity With the Objects Depicted in Icons on the Cognitive Performance of Icon Identification.

This study investigated the effects of users’ familiarity with the objects depicted in icons on the cognitive performance of icon identification. First, without knowing the specific semantic information of icons, 20 participants were required to search for target icons among visually similar distractors for 3-hour-long training sessions across 1 week, during which their familiarity with different icons was manipulated by differential exposure frequencies. Half of the icons were presented 10 times more often than the other half. Subsequently, participants’ abilities to recall corresponding semantic information when cued with associated target icons were tested after they had learned all the icons. The results showed that, in both the visual search task and the semantic information recall task, participants performed significantly better when the icons were more familiar. Importantly, the effects of icon complexity in the visual search task diminished as participants became familiar with the icons, and the beneficial effects of familiarity in the semantic information recall task were larger when the icons were complex. These findings have practical implications for icon design. When creating new icons for time critical user interfaces, icons should be kept as simple as possible and employ familiar, commonly used, graphics.

Does a "stoplight!" improve processing a stoplight? Cross-modal influences of time-compressed spoken denotations on automotive icon classification.

Findings from three experiments support the conclusion that semantic auditory primes facilitate processing of complex warning icons in the automotive context. In Experiment 1, we used a cross-modal icon identification task with auditory primes and visual icons as targets, presented in a high perceptual load context. Responses were faster for congruent priming in comparison to neutral or incongruent priming. This effect also emerged for different levels of time-compression of auditory primes. In Experiment 2, participants took part in a driving simulation with target icons on a gantry road sign. Participants had to categorize the color of the icons. Again, compressed auditory primes facilitated responses in cases of congruency (compared with incongruent and neutral primes). This result was replicated in Experiment 3 with more complex responses (i.e., braking, switching lanes). Our results suggest semantic object-based auditory-visual interactions, which rapidly increase the denoted target object's salience. (PsycINFO Database Record

Designing Interfaces for Older Users: Effects of Icon Detail and Semantic Distance

Older users are increasingly using digital means (especially the Internet and mobile devices) for work and leisure. Yet, until recently, researchers have not paid sufficient attention to how one can adapt the human-computer interface to older users. In this paper, we propose an approach to adapting interfaces to older users that is based on the knowledge of design and knowledge of age-related capabilities and needs. We concentrate on icons, which are perhaps the most common means of controlling human-computer interaction. First, we determined age-related cognitive impairments that might affect icon identification and selected two icon attributes that we could adapt to overcome performance degradation. We then conducted an experiment to test the hypothesized differences between young and old adults in terms of the impact of icon design on user performance. The two attributes of icon design were level of detail in the icon (i.e., the number of elements that constitute the icon) and its semantic distance (i.e., the distance between the meaning of the icon and function it represents). We found that both attributes affected the performance of older users more strongly than they did young users except for an extreme case in which the negative impact on young users when adapting for older users was devastating. We believe that these results demonstrate that adaptation of icons for older users is desirable and feasible but must be done with caution. We need more research to determine the nuances and limitations of adaptation to understand the adaptation of other design attributes by going beyond the cognitive aspects to the physical, affective, and social aspects of human computer interaction.

What’s in a name? The role of graphics, functions, and their interrelationships in icon identification

Communication using icons is now commonplace. It is therefore important to understand the processes involved in icon comprehension and the stimulus cues that individuals utilize to facilitate identification. In this study, we examined predictors of icon identification as participants gained experience with icons over a series of learning trials. A dynamic pattern of findings emerged in which the primary predictors of identification changed as learning progressed. In early learning trials, semantic distance (the closeness of the relationship between icon and function) was the best predictor of performance, accounting for up to 55% of the variance observed, whereas familiarity with the function was more important in later trials. Other stimulus characteristics, such as our familiarity with the graphic in the icon and its concreteness, were also found to be important for icon design. The theoretical implications of these findings are discussed, with particular emphasis on the parallels with picture naming. The icon identification norms from this study may be downloaded from brm.psychonomic-journals.org/content/supplemental.

Icon Identification in Context: The Changing Role of Icon Characteristics With User Experience

This research examined the relative importance of icon characteristics in determining the speed and accuracy of icon identification. Studies to date have focused on the role of one or two icon characteristics when users first experience an icon set. This means that little is known about the relative importance of icon characteristics or how the role of icon characteristics might change as users gain experience with icons. Thirty participants carried out an icon identification task over a long series of trials to simulate learning through experience. Icon characteristics investigated included semantic distance, concreteness, familiarity, and visual complexity. Icon characteristics were major determinants of performance, accounting for up to 69% of the variance observed in performance. However, the importance of icon characteristics changed with experience: Semantic distance is crucial initially while icon-function relationships are learned, but familiarity is important later because it has lasting effects on access to long-term memory representations. These findings suggest that icon concreteness may not be of primary importance when identifying icons and that semantic distance and familiarity may be more important. Designers need to take into account icon characteristics other than concreteness when creating icons, particularly semantic distance and familiarity. The precise importance of the latter characteristics will vary depending on whether icons are rarely encountered or frequently used.

Impact of graphical user interface screen features on computer task accuracy and speed in a cohort of patients with age-related macular degeneration

PURPOSE: To investigate the impact of graphical user interface screen features on computer task performance in patients with age-related macular degeneration (AMD). DESIGN: Interventional case series. METHODS: Eighteen patients with visual impairment due to AMD were recruited from the Bascom Palmer Eye Institute Low Vision Clinic. Each patient underwent evaluation of visual acuity using the Early Treatment Diabetic Retinopathy Study protocol, contrast sensitivity using a Pelli-Robson chart, binocular simultaneous visual field using the Esterman program on an automated perimeter, and color vision using Farnsworth D-15. Each subject then completed computer icon identification tasks while the following screen features of the graphical user interface were varied: size of icons displayed, icon set size (number of icons displayed), and background color. Each patient performed all 125 computer tasks with each of five icon sizes (9.2 mm, 14.6 mm, 23.2 mm, 36.8 mm, 58.3 mm), each of five icon set sizes (2, 3, 4, 5, 6), and each of five different background colors (black, white, red, green, blue) in a randomly ordered fashion. Relationships between computer task performance (accuracy and speed) and graphical user interface screen features were studied. RESULTS: Icon size and icon set size are significantly associated with computer task accuracy ( P < .001), whereas background color is not a significant predictor of task accuracy ( P = .63). The impact of icon size on accuracy is nonlinear, with the data indicating that no additional improvement in accuracy is associated with increasing the icon size beyond 23.2 mm. The impact of icon set size on accuracy is linear, with a smaller icon set size significantly associated with greater computer accuracy. A larger icon size is significantly associated with a shorter time to task completion ( P = .001); this relationship is largely linearly related to icon size. There was no significant impact of background color ( P = .11) or set size ( P = .37) on time to task completion. CONCLUSIONS: Modifications of graphical user interface design may permit improved computer task performance among patients with visual impairment due to AMD.

Impact of visual function on computer task accuracy and reaction time in a cohort of patients with age-related macular degeneration

PURPOSE: To investigate the impact of visual function parameters on computer task performance in patients with age-related macular degeneration (AMD). DESIGN: Interventional case series. METHODS: Eighteen patients with visual impairment due to age-related macular degeneration underwent evaluation of visual acuity using the Early Treatment Diabetic Retinopathy Study protocol, contrast sensitivity using a Pelli-Robson chart, binocular simultaneous visual field using the Esterman program on an automated perimeter, and color vision using Farnsworth D-15. Each subject then completed 125 computer icon identification tasks. Relationships between computer task performance (accuracy and speed) and visual function parameters (visual acuity, contrast sensitivity, visual field, and color vision) were analyzed. RESULTS: Visual acuity and contrast sensitivity in the better eye, weighted average contrast sensitivity, and color vision defects are significantly associated with computer task accuracy. Visual acuity in the better eye, weighted average visual acuity, and color vision defects are significantly associated with performance speed. Visual function parameters and clinical features significantly associated with computer task accuracy in a multiple regression model include weighted average contrast sensitivity ( P = 0.001), protan color vision defect ( P = 0.002), cataract severity in the better-seeing eye ( P = 0.036), and geographic atrophy outside the central macula ( P = 0.046). Visual function parameters and clinical features significantly associated with computer task speed in a multiple regression model include color vision defects (deutan, P < 0.001; protan, P < 0.001) and gender ( P = 0.05). CONCLUSIONS: Among this cohort of patients with AMD, visual acuity, contrast sensitivity, and color vision defects are significant predictors of computer task performance. Visual function parameters of the better eye played a more significant role than parameters of the worse eye, and contrast sensitivity is the most significant predictor of computer task accuracy.

Transfer between Icon Sets and Ratings of Icon Concreteness and Appropriateness

Two studies are reported on the usability of icons. Firstly, an experiment was carried out to investigate the transfer of performance between sets of icons for different computer functions. The aim was to determine whether users would benefit from common underlying elements within concrete icon sets, compared with unrelated abstract icons. A cross-over study was employed whereby subjects performed an icon identification task with one set of icons (a concrete or abstract learning set) and then transferred to another set of icons (a concrete or abstract transfer set). It was hypothesized that transferring from concrete to concrete icons would yield the best results due to the use of repeated elements in the concrete sets. Identification time data did not produce significant results to support the hypothesis. Significant results were yielded from the error data, this demonstrated the superiority of concrete icons, but no advantage came from previous experience with a concrete set. A second study examined the rating of the icons used in the first study in terms of concreteness and appropriateness. Appropriateness was found to be a reasonable predictor of icon identification time.