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Charlene K. Stokes

dblp:12/9894 · DBLP profile ↗
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5ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 5Human-computer interaction and ubiquitous computing · 5Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
2 papers
Human-robot interaction · 64% Human-AI interaction · 16% Games and playful interaction · 14%

Topics — the 5 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-AI interaction
trust and reliance
0.212016
Social Interaction Moderates Human-Robot Trust-Reliance Relationship and Improves Stress Coping · HRI 2016
Human-robot interaction
child-robot interaction
0.212015
Emotional Storytelling in the Classroom: Individual versus Group Interaction between Children and Robots · HRI 2015
Games and playful interaction
interactive narrative
0.212015
Emotional Storytelling in the Classroom: Individual versus Group Interaction between Children and Robots · HRI 2015
Human-robot interaction
multi-robot systems
0.212015
Emotional Storytelling in the Classroom: Individual versus Group Interaction between Children and Robots · HRI 2015
Human-robot interaction › assistive robotics
socially assistive robotics
0.212015
Emotional Storytelling in the Classroom: Individual versus Group Interaction between Children and Robots · HRI 2015

Methods — techniques the papers use, named apart from their topics

statistical moderation analysis · 0.2experimental user study · 0.2between-subjects study · 0.2
YearPublicationVenuePosition
2017 Do We Need Emotionally Intelligent Artificial Agents? First Results of Human Perceptions of Emotional Intelligence in Humans Compared to Robots
Lisa Fan, Matthias Scheutz, Monika Lohani, Marissa McCoy, Charlene K. Stokes
IVA5
2016 Social Interaction Moderates Human-Robot Trust-Reliance Relationship and Improves Stress Coping
abstract
Previous work with non-social human-robot interaction has found no links between trust and reliance [1]. The current study tested the question: Can social interactions moderate trust-reliance relationship? Human-robot interactions may share similar characteristics to social and emotional interactions between humans. We investigated how social and emotional human-robot interactions moderate the trust-reliance relationship and impacts perceived stress coping abilities. In the experimental condition, social and emotional interactions were used to guide the dialogue between a participant and a virtual robot in order to promote team building. In the matched control condition, the interactions were information-focused, without social or emotional interaction. We show that social interaction moderated the effect of trust on reliance such that higher trust led to greater reliance on the robot. The experimental condition also had higher perceived stress coping abilities. These findings contribute to the existing literature and suggest that creating deeper social and emotional interactions with a robot teammate can facilitate human-robot partnership.
Monika Lohani, Charlene K. Stokes, Marissa McCoy, Christopher A. Bailey, Susan E. Rivers
HRI2
2016 Autonomous disengagement classification and repair in multiparty child-robot interaction
abstract
As research on robotic tutors increases, it becomes more relevant to understand whether and how robots will be able to keep students engaged over time. In this paper, we propose an algorithm to monitor engagement in small groups of children and trigger disengagement repair interventions when necessary. We implemented this algorithm in a scenario where two robot actors play out interactive narratives around emotional words and conducted a field study where 72 children interacted with the robots three times in one of the following conditions: control (no disengagement repair), targeted (interventions addressing the child with the highest disengagement level) and general (interventions addressing the whole group). Surprisingly, children in the control condition had higher narrative recall than in the two experimental conditions, but no significant differences were found in the emotional interpretation of the narratives. When comparing the two different types of disengagement repair strategies, participants who received targeted interventions had higher story recall and emotional understanding, and their valence after disengagement repair interventions increased over time.
Iolanda Leite, Marissa McCoy, Monika Lohani, Nicole Salomons, Kara McElvaine, Charlene K. Stokes, Susan E. Rivers, Brian Scassellati
RO-MAN6
2016 Perceived role of physiological sensors impacts trust and reliance on robots
abstract
Physiological sensors can be instrumental in facilitating complex behavioral and social interactions between humans and robots. However, there is a limited understanding of the psychological implications of incorporating such sensors in the context of human-robot interaction. We show that perception of sensors' role can act as an individual difference factor that can implicitly influence trust and reliance on a robot. We argue that some people may believe in the ability of physiological sensors to facilitate mentalization (or understanding) of humans. We refer to this tendency as mentalizing propensity. Such implicit differences in mentalizing propensity may influence participants' trust and reliance on a robot, as found in the current study. We also found that trust can mediate the influence of mentalizing propensity on reliance. Furthermore, we show that social interactions with a robot influenced participants' mentalizing propensity. The current work shows that implicit understanding of sensors' role in human-robot interaction context is an important attribute to assess in future studies on trust and reliance.
Monika Lohani, Charlene K. Stokes, Marissa McCoy, Christopher A. Bailey, Aditi Joshi, Susan E. Rivers
RO-MAN2
2015 Emotional Storytelling in the Classroom: Individual versus Group Interaction between Children and Robots
abstract
Robot assistive technology is becoming increasingly prevalent. Despite the growing body of research in this area, the role of type of interaction (i.e., small groups versus individual interactions) on effectiveness of interventions is still unclear. In this paper, we explore a new direction for socially assistive robotics, where multiple robotic characters interact with children in an interactive storytelling scenario. We conducted a between-subjects repeated interaction study where a single child or a group of three children interacted with the robots in an interactive narrative scenario. Results show that although the individual condition increased participant's story recall abilities compared to the group condition, the emotional interpretation of the story content seemed more dependent on the difficulty level rather than the study condition. Our findings suggest that, despite the type of interaction, interactive narratives with multiple robots are a promising approach to foster children's development of social-related skills.
Iolanda Leite, Marissa McCoy, Monika Lohani, Daniel Ullman 0002, Nicole Salomons, Charlene K. Stokes, Susan E. Rivers, Brian Scassellati
HRI6