Factors Affecting Speed and Accuracy of Response Selection in Operational Environments

Models of human information processing have been useful tools for analyzing and predicting human performance. A typical model breaks task performance into three broad processes: stimulus encoding, response selection, and motor execution. The response-selection process is the most critical in determining the speed and accuracy of performance in a complex operational environment. We describe research conducted for the Multidisciplinary University Research Initiative project, Training Knowledge and Skills for the Networked Battlefield, that investigates factors that affect speed and accuracy of response selection. Implications of the research for interface designs and training of operational skills are discussed. Acknowledgements The research described in the present paper was supported in part by MURI Grant W9112NF-05-1-0153 from the Army Research Office. We thank Lyle E. Bourne, Jr., and Alice F. Healy for helpful comments on an earlier version of this paper. Response Selection 3 Factors Affecting Speed and Accuracy of Response Selection in Operational Environments The research described in our paper was conducted for the Multidisciplinary University Research Initiative (MURI) project, Training Knowledge and Skills for the Networked Battlefield, supported by the U.S. Army Research Office. This MURI project is a five-year grant, started in 2005, for which Alice Healy and Lyle Bourne of the University of Colorado, Boulder, are the principal investigators. The main objective of the project is “to construct a theoretical and empirical framework that can account for and make accurate predictions about the effectiveness of different training methods” (http://psych.colorado.edu/~ahealy/MuriFrame.htm). The project adopts an integrated approach that involves (a) experimental investigations of components and principles for training of individuals and teams, (b) development of a taxonomy for training programs, and (c) ACT-R and IMPRINT modeling of training efficiency. Our part of the project focuses on the basic components of skill training, which are of primary interest for both human interface design and training of perceptual-motor skills. Since the rapid growth of cognitive theories in the mid 1950s, human performance has been analyzed from an information-processing perspective (Proctor & Vu, 2006b), which decomposes task performance into distinct processing components (e.g., Card, Moran, & Newell, 1983). Information-processing models typically consist of three major subsystems – stimulus encoding, response selection, and response execution (see Figure 1) – of which the most critical component in determining the speed and accuracy of performance is that of response selection (Welford, 1960). Consequently, factors that affect response-selection processes have been of theoretical and practical concern. They include, for example, the number of alternative choices (Hick, 1952), the interval between tasks (Smith, 1967), cognitive load (Baddeley, 1998), task sequence (Monsell, 2003), and compatibility between stimuli and responses (Fitts & Seeger, Response Selection 4 1953). Among those factors, the compatibility between stimuli and responses has been recognized as one of the most important in designing operational systems to provide optimal task performance. In basic psychological research, the effect of compatibility is termed stimulusresponse compatibility (SRC; Proctor & Vu, 2006a), whereas in applied human factors research it is often called display-control compatibility (Andre & Wickens, 1990). The SRC effect occurs when responses are mapped to stimuli for which there are some corresponding attributes, or dimensional overlap. These stimulus and response attributes may be their spatial locations (e.g., a signal displayed on the left side of the monitor and a response device placed on the left of the operator), or symbology of displays used to indicate controlling actions (e.g., arrow pointing to the left as a signal to turn a vehicle to the left). When stimuli are mapped to the corresponding responses, the stimulus-response (S-R) mapping is called compatible, whereas when they are mapped to noncorresponding responses the mapping is called incompatible (see Figure 2a). The SRC effect is often attributed to population stereotypes (Fitts & Seeger, 1953) or long-term associations (Barber, & O’Leary, 1997) acquired through experience. A traditional description of the SRC effect is that stimuli are more easily translated into responses when they correspond than when they do not. The advantage for compatible stimulus and response sets remains intact after several days of practice with the task (Dutta & Proctor, 1992; Fitts & Seeger, 1953), and the SRC effect is robust in a variety of task settings (Proctor & Vu, 2006a). Nevertheless, in recent studies we identified several task conditions in which the advantage of the compatible mapping is reduced or eliminated. In the following sections, we describe several lines of research conducted for the MURI project that include such conditions. SRC Effect in Mixed-Mapping Task Response Selection 5 In the first line of research, we examined the SRC effect in a flight simulator (Yamaguchi & Proctor, 2006, 2007). In one study, participants monitored the primary flight display and banked the aircraft by turning the yoke to the left or right according to the location of a signal presented on the display. They were to bank the aircraft in the direction corresponding to the signal location in one condition and in the direction opposite the signal location in another condition. That is, participants always responded compatibly or incompatibly to the signal locations depending on the mapping condition. Response times (RTs) and percentage errors (PEs) for the two conditions showed a relatively large SRC effect. Of more interest, in another condition, participants were required to choose on each trial whether to bank the aircraft compatibly or incompatibly to the signal location on the basis of its color: When the signal was green, participants were to bank the aircraft toward the signal location, but when the signal was red, they were to bank away from the signal location. Thus, the compatible and incompatible mappings were intermixed in a single task condition. Responses were generally slower and less accurate when the two mappings were mixed than when they were not, indicating a mixing cost. More important, the cost of mixing was larger for trials with compatible mapping than those with incompatible mapping, which reduced the SRC effect. Moreover, when the yoke-turn responses were replaced with presses of buttons on the left and right handles of the flight yoke, the SRC effect with mixed mappings was completely eliminated (see Figure 3). In a follow-up study (Yamaguchi & Proctor, 2008a), we observed that the elimination of the SRC effect in a mixed-mapping task was stable with the button-press responses but with the yoke-turn responses seemed to depend on the participants’ strategy. Namely, with yoke turns, the SRC effect appeared when responses were made quickly but less accurately, whereas it was eliminated when responses were made slowly but more accurately; Response Selection 6 thus, this observation seems to reflect speed-accuracy tradeoffs. A possibility is that modes of responding differently affect participants’ strategy, but it also seems possible that the observation is due to the fact that these response modes allow different types of response preparation. In fact, a previous study suggested that preparatory states can affect the reduction/elimination of the SRC effect in a mixed-mapping task (De Jong, 1995). We also conducted a series of experiments using a mixed-mapping task with four alternative responses (Proctor & Vu, 2008), rather than only two alternatives as in the studies discussed previously. Stimuli were presented on the left or right of the screen in green or red, with color indicating whether the mapping of stimulus locations to responses was compatible or incompatible. Two keys were operated by the middle and index fingers of the left hand for one mapping, and another two keys were operated by the index and middle fingers of the right hand for the other mapping. Thus, while participants were required to select the appropriate mapping on each trial, each response was assigned to only a single mapping. In this case, the SRC effect was neither eliminated nor reduced by mixing the two mappings (see Figure 4), most likely because the mapping of stimulus location to each response was consistent rather than variable. Though it is still left to future research to determine exactly which environmental manipulations can influence the pattern of SRC effects in mixed-mapping tasks, both the twoand fouralternative choice tasks suggest that the nature of responses modulates the SRC effect in mixedmapping tasks. Transfer of Learning: 1. Sensory Modality Robustness of the SRC effect is also implied by the fact that responses are typically faster and more accurate when a “task-irrelevant” stimulus attribute overlaps with a response attribute. The SRC effect on the basis of a task-irrelevant stimulus dimension is called the Simon effect, Response Selection 7 and the task that produces this effect is called the Simon task (Lu, & Proctor, 1995; Simon, 1990). In a typical Simon task, participants are asked to make a left or right keypress in response to the color of the stimulus that appears on the left or right of the screen (see Figure 2b). Even though participants are instructed to ignore the spatial dimension of stimuli, responses are faster and more accurate when they correspond to the spatial stimulus attributes than when they do not, yielding the Simon effect. Although the Simon effect is also known to persist through several days of practice for the task (e.g., Proctor & Lu, 1999; Simon, Craft, & Webster, 1973), another line of research we have conducted for the MURI project show