TY - GEN
T1 - Engagement and Mind Perception Within Human-Robot Interaction
T2 - 12th International Conference on Social Robotics, ICSR 2020
AU - Kont, Melissa
AU - Alimardani, Maryam
PY - 2020
Y1 - 2020
N2 - People can feel engaged and attribute human-like traits when interacting with a social robot and reveal this unconsciously to observers. Studies have suggested that behavioral signals such as facial expressions, posture, speech and laughter play an important role in identifying engagement in Human-Robot Interaction (HRI), however the effect of these factors in different age groups, as well as their relationship with mind attribution towards robots remains unclear. This study examined 24 elderly people and 24 university students on facial expressions, laughter and speech during an interaction with a NAO-robot. In addition, self-reported engagement level and mind perception scores were collected after the interaction and analyzed. Results showed that elderly had a significantly lower report of engagement with the robot, which was positively correlated with their perception of mind capacity in the robot. Furthermore, for both elderly and students, there was a negative trend between self-reported mind perception and observed behavioral engagement with the robot. Findings of this study could be employed in the design and evaluation of future HRI scenarios.
AB - People can feel engaged and attribute human-like traits when interacting with a social robot and reveal this unconsciously to observers. Studies have suggested that behavioral signals such as facial expressions, posture, speech and laughter play an important role in identifying engagement in Human-Robot Interaction (HRI), however the effect of these factors in different age groups, as well as their relationship with mind attribution towards robots remains unclear. This study examined 24 elderly people and 24 university students on facial expressions, laughter and speech during an interaction with a NAO-robot. In addition, self-reported engagement level and mind perception scores were collected after the interaction and analyzed. Results showed that elderly had a significantly lower report of engagement with the robot, which was positively correlated with their perception of mind capacity in the robot. Furthermore, for both elderly and students, there was a negative trend between self-reported mind perception and observed behavioral engagement with the robot. Findings of this study could be employed in the design and evaluation of future HRI scenarios.
UR - http://www.scopus.com/inward/record.url?scp=85097131336&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-62056-1_29
DO - 10.1007/978-3-030-62056-1_29
M3 - Conference contribution
SN - 9783030620554
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 344
EP - 356
BT - Social Robotics - 12th International Conference, ICSR 2020, Proceedings
A2 - Wagner, A.R.
A2 - Feil-Seifer, D.
A2 - Haring, K.S.
A2 - Rossi, S.
A2 - Williams, T.
A2 - He, H.
A2 - Sam Ge, S.
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 14 November 2020 through 18 November 2020
ER -