scholarly journals The effect of computer response time on user performance and satisfaction: A preliminary investigation

1983 ◽  
Vol 15 (2) ◽  
pp. 213-216 ◽  
Author(s):  
Gary L. Dannenbring
1982 ◽  
Vol 26 (8) ◽  
pp. 698-702 ◽  
Author(s):  
Stuart Martin Weiss ◽  
George Boggs ◽  
Mark Lehto ◽  
Sogand Shodja ◽  
David J. Martin

With the advent of time-shared interactive systems, the psychological impact of system response time (SRT) and SRT variability (SRTV) has become an important issue. Carbonell, et. al. (1968) have suggested that both SRT and SRTV may influence system user performance and satisfaction. A number of studies have been reported that address this issue, but results have been mixed. In this experiment, twenty subjects ( Ss) executed keyboard entries to control the temperature of a simulated industrial process via time-shared process control computer. Temperature was displayed in analog form on a CRT. The task was to maintain the temperature within upper and lower bounds that were clearly indicated on the display. The experimental design consisted of repeated measures with SRT and SRTV as experimental factors. Three SRT's were employed (2, 6 and 10 seconds) with two levels of SRTV (σ2 = 0 and σ2 = 0.33 seconds). Mean blood pressure (MBP) and heart rate (HR) were continuously monitored during experimental conditions. Task errors were defined as temperature excursions beyond the displayed bounds. Significant main effects were not obtained for MBP or HR. Significant differences for error rate (performance) were noted for SRT ( F(2, 15) = 23.10, p < .05), subjects x SRT ( F37, 15) = 1.66, p < .001), and SRT x SRTV ( F(1, 15) = 13.14, p < .05). Error data are consistent with the Carbonell et. al. suggestion that long and variable SRT may affect user performance. The results are discussed in terms of their incongruity with current literature.


Author(s):  
Tom Goodman ◽  
Robert Spence

Subjects solved a two-parameter optimization problem using a graphic display with light-pen interaction via either two linear light potentiometers or one planar light potentiometer. Normally distributed computer response times were used, with a mean of 1.0 s and a range of 0.2 to 3.4 s. Three standard deviation values were used: 0.2, 0.4, and 0.8 s. Potentiometer dimensionality affected the extent to which each of the two parameters was searched, but had no significant effect on solution time. System response time variability affected the time taken to solve the problem, and its effect interacted strongly with time of day.


1981 ◽  
Vol 25 (1) ◽  
pp. 754-758 ◽  
Author(s):  
Glen R. Gallaway

Response times (response delays) in interactive computer systems can greatly effect user performance and system productivity. This document summarizes the literature on user response time needs in interactive computer systems, and presents a set of guidelines for specifying response times that meet those needs. During the literature survey, it became evident that much more supporting data is required in order to have guidelines that cover most conditions under which people use a computer, and in order to provide a solid foundation of data taken from real world user interaction with computer systems. The information presented in this document should be viewed as a starting point for further work on defining response time needs for interactive computer system users.


Author(s):  
Jonathan Flittner* ◽  
John Luksas ◽  
Joseph L. Gabbard

This study determines how to apply existing image analysis measures of visual clutter to augmented reality user interfaces, in conjunction with other factors that may affect performance such as the percentage of virtual objects compared to real objects in an interface, and the type of object a user is searching for (real or virtual). Image analysis measures of clutter were specifically chosen as they can be applied to complex and naturalistic images as is common to experience while using an AR UI. The end goal of this research is to develop an algorithm capable of predicting user performance for a given AR UI. In this experiment, twelve participants performed a visual search task of locating a target object in an array of objects where some objects were virtual, and some were real. Participants completed this task under three different clutter levels (low, medium, high) against five different levels of virtual object percentage (0%, 25%, 50%, 75%, 100%) and two types of targets (real, virtual) with repetition. Task performance was measured through response time. Results show significant differences in response time between clutter levels and between virtual object percentage, but not target type. Participants consistently had more difficulty finding objects in more cluttered scenes, where clutter was determined through image analysis methods, and had more difficulty in finding objects when the virtual of objects was at 50% as opposed to other scenarios. Response time positively correlated to measures of combined clutter (virtual and real) arrays but not for measures of clutter taken of the individual array components (virtual or real), and positively correlated with the clutter scores of the target objects themselves.


1988 ◽  
Vol 32 (5) ◽  
pp. 344-346 ◽  
Author(s):  
Jeanne P. Bayerl ◽  
David R. Millen ◽  
Steven H. Lewis

Personal-computer applications-software often requires people to navigate and select options using their keyboard's function keys where context-dependent meanings for these keys are assigned by guides or menus labeled on the screen. The physical layout of function keys on standard PC-compatible keyboards differs from the most common layouts of screen labels. This study examined user performance consequences of this simple, spatial, inconsistency. In a simulated order entry task, 36 participants each completed 240 trials, 40 with each of six different combinations of two keyboards and three screen guides with different spatial arrangements of function keys and screen labeling. One keyboard used the standard 5×2 function key pad and one used a single horizontal row of function keys; the screen guides were either a horizontal row, a vertical list, or a grid consistent with the standard key pad. We collected measures of response time, errors, and user preferences. Analysis of errors showed no reliable results. Analysis of response times showed several significant effects. Responses were faster with the two combinations of key pad and screen-guide layouts that were spatially consistent than with the four inconsistent layouts. Response times were also faster with the keyboard with horizontal function keys than with the standard layout, and slower with the vertical screen guide than with either of the other two guides. Over 80% of the participants thought the task was easiest when the screen guide matched the function key layout.


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