It has recently been proposed that in searching for a target defined as a conjunction of two or more separable features, attention must be paid serially to each stimulus in a display. Support for this comes from studies in which subjects searched for a target that shared a single feature with each of two different kinds of distractor items (e.g., a red O in a field of black Os and red Ns). Reaction time increased linearly with display size. We argue that this design may obscure evidence of selectivity in search. In an experiment in which the numbers of the two distractors were unconfounded, we find evidence that subjects can search through specified subsets of stimuli. For example, subjects told to search through just the Os to find the red O target do so without searching through Ns. Implications of selective search are discussed.
Attention has been given to making user interface design and testing less costly so that it might be more easily incorporated into the product development life cycle. Three experiments are reported in this paper that relate the proportion of usability problems identified in an evaluation to the number of subjects participating in that study. The basic findings are that (a) 80% of the usability problems are detected with four or five subjects, (b) additional subjects are less and less likely to reveal new information, and (c) the most severe usability problems are likely to have been detected in the first few subjects. Ramifications for the practice of human factors are discussed as they relate to the type of usability test cycle employed and the goals of the usability test.
Models ofthe Stroop effect that postulate single, centralized processing stations are fundamentally incorrect. A translational model is proposed in which parallel processing systems are hypothesized that are linked by a translation mechanism. Each system processes information using its own internal code specifically linked to the type of information the system processes. Information is passed between these systems via the translation mechanism. Evidence supporting this model comes from both the literature and the experiments reported in this article. Of primary importance is the demonstration that the pattern of interference that emerges is dependent upon the cognitive system used to process the information.The Stroop paradigm was employed in the four experiments reported. In this paradigm, first reported by Stroop in 1935,1 bidimensional stimuli are created such that either dimension of a stimulus may be responded to with the same overt response. Reaction time is measured of the response to one of the stimulus dimensions, while the subject attempts to ignore the other dimension, which will conflict on some trials with the correct response. For example, a subject who is shown the word RED printed in blue ink could respond either to word meaning by saying "red" or to ink color by saying "blue."?The interesting finding is that, when subjects must read the word out loud, there is no effect of a conflicting ink color. Reaction time in the conflicting condition is as fast as in the condition in which the color word names the ink color for the trial. However, when the subject must name the ink color, reaction time in the conflicting condition is greatly increased, compared to the time required for the condition in which the color word and the ink color have the same value (e.g., RED in red).Similar findings have been reported using different stimulus sets. For example, when word meaning and spatial position are combined (e.g., the words RIGHT or LEFT appear to the right or left of fixation), reading the word out loud is not affected by a conflicting spatial position, but naming the position the word occupies is slowed if a conflicting word appears in that position (Palef & Olson, 1975;Seymour, 1974).The models proposed to account for the Stroop effect have differed in detail but have two underlying assumptions in common. The first is that, at some point in the system, all the information passes through a single, centralized decision and/or response stage. This is true regardless of the particular task employed. To account for the asymmetry in the interference effects, the second assumption is made: The two dimensions are hypothesized to arrive at the decision stage at different times.In Figure 1, a schematic of this type of model is shown for the ink color/color word form of the Stroop task. Two stimulus-analyzing stages are hypothesized: one to abstract word meaning and another to abstract ink color information (see Treisman, 1969). These stimulus analyzers work in parallel, and output from them races toward a centra...
In two experiments, each using a different product (either a CD-ROM based eleclxonic book or an interactive voice response system), we compared the usability problems uncovered using low-and high-fidelity prototypes. One group of subjects performed a series of tasks using a paperbased low-fidelity prototype, while another performed the same tasks using either a high-fidelity prototype or the actual product. In both experiments, substantially the same sets of usability problems were found in the low-and highfidelity conditions. Moreover, there was a significant correlation between the proportion of subjects detecting particular problems in the low-and high-fidelity groups. In other words, individual problems were detected by a similar proportion of subjects in both the low-and high-fidelity conditions. We conclude that the use of low-fidelity prototypes can be effective throughout the product development cycle, not just during the initial stages of design.
Recent attention has been focused on making user interface design less costly and more easily incorporated into the product development life cycle. This paper reports an experiment conducted to determine the minimum number of subjects required for a usability test. It replicates work done by Jakob Nielsen and extends it by incorporating problem importance into the curves relating the number of subjects used in an evaluation to the number of usability problems revealed. The basic findings are that (1) with between 4 and 5 subjects, 80% of the usability problems are detected and(2) that additional subjects are less and less likely to reveal new information. Moreover, the correlation between expert judgments of problem importance and likelihood of discovery is significant, suggesting that the most disruptive usability problems are found with the first few subjects. Ramifications for the practice of human factors are discussed as they relate to the type of usability test cycle the practitioner is employing, and the goals of the usability test.
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