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Robert Molloy

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Publication statistics

Pub. period:1992-1997
Pub. count:4
Number of co-authors:4

Co-authors

Number of publications with 3 favourite co-authors:

Raja Parasuraman:4
Indramani L. Singh:2
Mustapha Mouloua:1

Productive colleagues

Robert Molloy's 3 most productive colleagues in number of publications:

Raja Parasuraman:26
Mustapha Mouloua:11
Saroj Parasuraman:3

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May 27

13th Intl. Conf. on New Interfaces for Musical Expression

May 28

Graphics Interface 2013

May 29

Intl. Workshop on Design and Spontaneity in Computer-Supported Collaborative Learning (DS-CSCL 2013)

May 22

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Robert Molloy

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Publications by Robert Molloy (bibliography)

1997

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Singh, Indramani L., Molloy, Robert and Parasuraman, Raja (1997): Automation-Induced Monitoring Inefficiency: Role of Display location. In International Journal of Human-Computer Studies, 46 (1) pp. 17-30.

“Operators can be poor monitors of automation if they are engaged concurrently in other tasks. However, in previous studies of this phenomenon the automated task was always presented in the periphery, away from the primary manual tasks that were centrally displayed. In this study we examined whether centrally locating an automated task would boost monitoring performance during a flight-simulation task consisting of system monitoring, tracking and fuel resource management sub-tasks. Twelve nonpilot subjects were required to perform the tracking and fuel management tasks manually while watching the automated system monitoring task for occasional failures. The automation reliability was constant at 87.5% for six subjects and variable (alternating”

1993

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Mouloua, Mustapha, Parasuraman, Raja and Molloy, Robert (1993): Monitoring Automation Failures: Effects of Single and Multi-Adaptive Function Allocation. In: Proceedings of the Human Factors and Ergonomics Society 37th Annual Meeting 1993. pp. 1-5.

“Adaptive function allocation has been proposed to allow the advantages of task automation to be realized without some of the disadvantages of "static" automation. However, few empirical studies of the efficacy of adaptive allocation have been reported. The effects of adaptive function allocation on monitoring for automation failure during multi-task flight simulation were examined in two experiments. The first study examined the use of two methods of adaptive function allocation as a possible counter-measure to automation-induced monitoring problems. Subjects were required to perform a tracking and fuel management task while monitoring an automated system monitoring task for possible failures. For the "model-based" and "performance-based" adaptive groups, a single 10-minute block of fully manual performance on the monitoring task was allocated to subjects in the middle of a session. For the control group system monitoring was automated throughout all sessions. All three groups had low probabilities of detection of automation failures for the first 40 minutes spent with automation, before the adaptive function allocation change. However, detection probabilities were higher for both adaptive groups than for the control group following the function allocation change. The second study found that multiple adaptive changes (repeated function allocation) sustained these performance benefits over a longer automation period. These results clearly indicate that adaptive function allocation can improve detection of automation failures and that the improvement can be sustained over long periods of automation cycles.”

1992

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Singh, Indramani L., Molloy, Robert, Parasuraman, Raja and Parasuraman, Saroj (1992): Development and Validation of a Scale of Automation-Induced "Complacency". In: Proceedings of the Human Factors Society 36th Annual Meeting 1992. pp. 22-25.

“In the present studies, a scale was developed for measuring attitudes toward automation technology that reflect a potential for complacency. In the first, developmental study, a 20-item questionnaire consisting of statements concerning various aspects of automation was administered to 139 undergraduates at Catholic University. Factor analysis of the complacency potential rating scale (CPRS) revealed five independent factors, namely: general, confidence-, reliance-, trust-, and safety-related complacency. The internal consistency reliability coefficients of the five factors and the scale as a whole were found to be high, and the scales revealed satisfactory test-retest reliabilities. The pattern of correlations among CPRS score, age, gender, computer use, and computer experience were consistent with previous studies examining attitudes toward microcomputer usage (Igbaria and Parasuraman, 1991). In the second, validation study, the 20-item CPRS was cross-validated on a sample of 175 undergraduate students at Drexel University. Factor analysis similarly revealed five factors with high alphas. The results indicate that the potential for complacency can be evaluated by assessing attitudes towards automation technology.”

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Molloy, Robert and Parasuraman, Raja (1992): Monitoring Automation Failures: Effects of Automation Reliability and Task Complexity. In: Proceedings of the Human Factors Society 36th Annual Meeting 1992. pp. 1518-1521.

“Two studies examined the effects of automation reliability and task complexity on the monitoring of automation failures during performance of a flight-simulation task. In the first study, 24 students performed tracking and resource management tasks while an automation routine monitored for system malfunctions over four 30-minute sessions. Detection of automation failures was significantly higher for variable reliability automation (mean = 81.6%) than for constant reliability automation (mean = 32.7%), indicating that constant-reliability automation induced complacency in monitoring. The effect of automation reliability was eliminated when 16 more subjects were required to complete the monitoring task only. Neither group of subjects exhibited a vigilance decrement. In the second study monitoring performance and vigilance decrement were examined for a situation in which only one automation failure occurred during a session. 36 students were randomly assigned to one of three task groups: simple (visual discrimination task), single-complex (monitoring only) or multi-complex (tracking, resource management, and monitoring). In both the simple and the multi-complex tasks, more subjects detected the automation failure in the first ten minutes of a session than in the last ten minutes of a session (67%-17% and 75%-42% respectively). Subjects in the single-complex condition detected the automation failure equally well in both time periods (92%-83%). The results point to two areas of potential costs in the automation of a task: (1) constant patterns of automation reliability can lead to inefficiency in monitoring automation failures, and (2) infrequent automation failures in multi-task conditions can lead to a vigilance decrement. While these costs should not prohibit the implementation of automation, they should be considered in the design of any automated system.”

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