The Perception of Teamwork With an Autonomous Agent Enhances Affect and Performance Outcomes
| Autor: | Patrick Mead, James C. Walliser, Tyler H. Shaw |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Teamwork
Knowledge management Team Structure business.industry media_common.quotation_subject education 05 social sciences Autonomous agent Affect (psychology) 050105 experimental psychology Design characteristics Task (project management) Medical Terminology Perception 0501 psychology and cognitive sciences Psychology business 050107 human factors Medical Assisting and Transcription media_common Cognitive psychology |
| Zdroj: | Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 61:231-235 |
| ISSN: | 1071-1813 2169-5067 |
| DOI: | 10.1177/1541931213601541 |
| Popis: | Among groups of humans, the team structure has been argued to be the most effective way for people to organize to accomplish work. Research suggests that humans and autonomous agents can be more effective when working together. However, the drive toward capable autonomous teammates has focused on design characteristics while ignoring the importance of social interactions between teammates. In the present study we created team structure though task interdependence and observed teamwork outcomes in the form of affect, behavior, and performance outcomes. A team structure resulted in improved affect and performance outcomes relative to a non-team structure. However, team structure did not elicit significant behavioral differences. Human partners received higher affect ratings and elicited significantly more communication from the participant than an autonomous partner. These findings suggest that social interactions between humans and autonomous teammates should be an important design consideration. While the current data is promising, team structure alone may not be sufficient to ensure effective teams, so further research should explore the utility of team development interventions between humans and autonomous agents. |
| Databáze: | OpenAIRE |
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