Matching Items (2)
Filtering by
- All Subjects: Aging in place
- All Subjects: Task Complexity
- Creators: Cooke, Nancy
Description
As people begin to live longer and the population shifts to having more olderadults on Earth than young children, radical solutions will be needed to ease the
burden on society. It will be essential to develop technology that can age with the
individual. One solution is to keep older adults in their homes longer through smart
home and smart living technology, allowing them to age in place. People have many
choices when choosing where to age in place, including their own homes, assisted
living facilities, nursing homes, or family members. No matter where people choose to
age, they may face isolation and financial hardships. It is crucial to keep finances in
mind when developing Smart Home technology.
Smart home technologies seek to allow individuals to stay inside their homes for
as long as possible, yet little work looks at how we can use technology in different
life stages. Robots are poised to impact society and ease burns at home and in the
workforce. Special attention has been given to social robots to ease isolation. As
social robots become accepted into society, researchers need to understand how these
robots should mimic natural conversation. My work attempts to answer this question
within social robotics by investigating how to make conversational robots natural and
reciprocal.
I investigated this through a 2x2 Wizard of Oz between-subjects user study. The
study lasted four months, testing four different levels of interactivity with the robot.
None of the levels were significantly different from the others, an unexpected result. I
then investigated the robot’s personality, the participant’s trust, and the participant’s
acceptance of the robot and how that influenced the study.
ContributorsMiller, Jordan (Author) / McDaniel, Troy (Thesis advisor) / Michael, Katina (Committee member) / Cooke, Nancy (Committee member) / Bryan, Chris (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2022
Description
In human-autonomy teams (HATs), the human needs to interact with one or more autonomous agents, and this new type of interaction is different than the existing human-to-human interaction. Next Generation Combat Vehicles (NGCVs), which are envisioned for the U.S. military are associated with the concept of HAT. As NGCVs are in the early stage of development, it is necessary to develop different training methods and measures for team effectiveness. The way team members communicate and task complexity are factors affecting team efficiency. This study analyzes the impact of two interaction strategies and task complexity on team situation awareness among 22 different teams. Teams were randomly assigned different interaction conditions and went through two missions to finish their assigned tasks. Results indicate that the team with the procedural interaction strategy had better team situation awareness according to the Coordinated Awareness of the Situation by Teams (CAST) scores on the artillery calls. However, the difference between the strategies was not found on CAST scores of perturbations, map accuracy, or Situation Awareness Global Assessment Technique (SAGAT) scores. Additionally, the impact of task complexity on the team situation awareness was not found. Implications and suggestions for future work are discussed.
ContributorsKim, Jimin (Author) / Gutzwiller, Rober (Thesis advisor) / Cooke, Nancy (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2021