Automation Technology and Human Performance: Current Research and Trends

By Mark W. Scerbo | Go to book overview

as easier than low-DC participants, F(1,41) = 5.88, p < .05. This might be due to the high-DC tendency to want to master a situation. Although they might have been more motivated to do well, it did not improve their performance. The more favorable ratings of the high-DC participants were likely the result of perceptions of performance.

None of the independent variables affected helpfulness. Again, this supports the assertion that high- DC participants did not see the computer as a threat to their control because they did not reject its help and rated its helpfulness similar to that of low-DC participants.

Participants were also asked to rate how well they enjoyed interacting with the computer. The results showed an interaction between communication mode and desire for control, F(3,55) = 3.79, p < .05. High- DC participants reported more enjoyment than low-DC participants in the limited human-computer interaction condition, but less enjoyment in the control condition. This interaction might be explained by the way high- and low-DC participants perceived the tasks. The limited human-computer interaction group was faced with the most challenging condition (as shown by task score) in which participants were still able to actively communicate with the computer. It is possible that high-DC participants in this group may have enjoyed the interaction more because of the challenge of formulating appropriate utterances to communicate with the computer. By contrast, the control group had no control over their interaction with the computer because they could not communicate in any way. This inability to control when and how the computer would intervene may have caused high-DC participants to rate enjoyment as lower in this group.


CONCLUSIONS

This study was designed to examine the effects of DC on adaptive human-computer interactions. DC has been found to reliably affect achievement-related behavior in human interactions. It was hypothesized that DC would have similar effects on adaptive human-computer interactions. The results, however, did not support Burger ( 1985) research on DC. It is possible that DC does not apply to interactions with computers in the same way it does with a human. Future research may need to distinguish between DC for humans and computers.


REFERENCES

Burger J. ( 1985). "Desire for control and achievement-related behaviors". Journal of Personality and Social Psychology, 48, 1520-1533.

Burger J. & Cooper H. ( 1979). "The desirability of control". Motivation and Emotion, 3, 381-393.

Crowne D., & Marlowe D. ( 1960). "A new scale of social desirability independent of psychopathology". Journal of Consulting Psychology, 24, 349-354.

Gould J., Conti J., & Hovanyecz T. ( 1983). "Composing letters with a simulated listening typewriter". Communications of the ACM, 26, 295-308.

Kieras D. ( 1988). Towards a practical GOMS model methodology for user interface design. In M. Helander (Ed.), Handbook of human-computer interaction (pp. 135-157). Amsterdam: North Holland.

Rotter J. ( 1966). "Generalized expectancies for internal versus external control of reinforcement". Psychological Monographs, 80, Whole Number 609.

Rouse W. B. ( 1988). "Adaptive aiding for human/computer control". Human Factors, 30, 431-443.

Scerbo M. W. ( 1994). Implementing adaptive automation in aviation: The pilot-cockpit team. In M. Mouloua & R. Parasuraman (Eds.), Human performance in automated systems: Current research and trends (pp. 249-255). Hillsdale, NJ: Lawrence Erlbaum Assoc.

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