Leader Attributions and Evaluations: Effects of Locus of Control, Supervisory Control, and Task Control

1994 ◽  
Vol 59 (1) ◽  
pp. 27-50 ◽  
Author(s):  
Neal M. Ashkanasy ◽  
Cynthia Gallois
2007 ◽  
Vol 118 (4) ◽  
pp. e34-e35
Author(s):  
R. Gobbelé ◽  
U. Stegelmeyer ◽  
T.D. Waberski ◽  
K.E. Stephan ◽  
K. Rache ◽  
...  

1977 ◽  
Vol 40 (3_suppl) ◽  
pp. 1059-1069
Author(s):  
Jerry L. Hart ◽  
J. Wesley Libb

Previous studies on locus of control and instructions have been interpreted to support the position of either a social learning theory or an anxiety. 144 college students were separated into locus of control categories based on scores on Rotter's I-E Scale and randomly assigned to receive skill or chance instructions and one of three anagram tasks of varying levels of difficulty. Primary dependent variables were number of correct anagrams and latency to the first response. The ratio of typical shifts to the total number of shifts in expectancy of success served as a third dependent variable. A check on the credibility of the instructions was also performed. The results of the moderate task showed that internals given chance instructions responded faster and solved more anagrams correctly than when given skill instructions. When the credibility of instructions was taken into account, significant differences between the groups were found for only those who did not believe the instructions. Assessment of credibility of instructions provided valuable clarification since disbelief of instructions may account for the results found in earlier research as well.


2008 ◽  
Vol 1205 ◽  
pp. 81-90 ◽  
Author(s):  
René Gobbelé ◽  
Kathrin Lamberty ◽  
Klaas E. Stephan ◽  
Ulrike Stegelmeyer ◽  
Helmut Buchner ◽  
...  

Author(s):  
Samuel J. Levulis ◽  
Patricia R. DeLucia ◽  
So Young Kim

Objective: We evaluated three interface input methods for a simulated manned-unmanned teaming (MUM-T) supervisory control system designed for Air Mission Commanders (AMCs) in Black Hawk helicopters. Background: A key component of the U.S. Army’s vision for unmanned aerial vehicles (UAVs) is to integrate UAVs into manned missions, called MUM-T (Department of Defense, 2010). One application of MUM-T is to provide the AMC of a team of Black Hawk helicopters control of multiple UAVs, offering advanced reconnaissance and real-time intelligence of flight routes and landing zones. Method: Participants supervised a (simulated) team of two helicopters and three UAVs while traveling toward a landing zone to deploy ground troops. Participants classified aerial photographs collected by UAVs, monitored instrument warnings, and responded to radio communications. We manipulated interface input modality (touch, voice, multimodal) and task load (number of photographs). Results: Compared with voice, touch and multimodal control resulted in better performance on all tasks and resulted in lower subjective workload and greater subjective situation awareness, ps < .05. Participants with higher spatial ability classified more aerial photographs ( r = .75) and exhibited shorter response times to instrument warnings ( r = −.58) than participants with lower spatial ability. Conclusion: Touchscreen and multimodal control were superior to voice control in a supervisory control task that involved monitoring visual displays and communicating on radio channels. Application: Although voice control is often considered a more natural and less physically demanding input method, caution is needed when designing visual displays for users sharing common communication channels.


1999 ◽  
Vol 160 (4) ◽  
pp. 436-442 ◽  
Author(s):  
Tracy Janssen ◽  
John S. Carton

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