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Teresa Flanagan

dblp:249/6760 · DBLP profile ↗
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5ranked-venue papers
4as first author
3since 2021 · last 2026
0000-0002-6003-7089ORCID · corroborated

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

Artificial intelligence and machine learning · 5 · 4 first-author · 3 since 2021Applied, interdisciplinary, general and emerging computing · 3 · 3 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 2 since 2021

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 · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
child-robot interaction
1.012026
Can You Help Me? The Influence of Robot Requests for Help on Child-Robot Connection · HRI 2026
Human-robot interaction
robot ethics
0.912025
Perceived Morality of Robot and Human Transgressors Varies By Perceived Ability to Feel · HRI 2025
Human-robot interaction
trust in robots
0.312026
Can You Help Me? The Influence of Robot Requests for Help on Child-Robot Connection · HRI 2026
Human-robot interaction
robot design
0.312025
Perceived Morality of Robot and Human Transgressors Varies By Perceived Ability to Feel · HRI 2025

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

between-subjects study · 1.9
YearPublicationVenuePosition
2026 Can You Help Me? The Influence of Robot Requests for Help on Child-Robot Connection
abstract
Children are interacting with robots in sophisticated ways to the extent in which they may be establishing a relationship. Forming appropriate levels of connection between children and robots could have significant impacts on the future of robot design, particularly in education. Despite this, little is known about the underlying mechanisms of such formation. In this work, we take an initial step by exploring what robot behaviors build a child-robot connection in a single interaction. Specifically, we investigated whether 6-10-year-old children feel more connected to a robot that responds to an issue by asking the child for help or simply disclosing the issue, and whether this is dependent on the valence of the response to the issue (emotional or mechanical). In a 2 x 2 between-subjects study (N=100), we found that children of all ages trusted a robot that asked for help more than a robot that simply disclosed the issue. Furthermore, children felt closer to an emotional robot that asked for help than an emotional robot that did not ask for help. Together, these findings suggest that asking for help builds trust between a robot and child and expressing relatable vulnerability, via emotional help requests, creates further feelings of connection.
Teresa Flanagan, Justin Zhang 0009, Lin Bian, Sarah Sebo
HRI1
2025 Perceived Morality of Robot and Human Transgressors Varies By Perceived Ability to Feel
abstract
Mistakes, failures, and transgressions committed by a robot are inevitable as robots become more involved in our society. When a wrong behavior occurs, it is important to understand what factors might affect how the robot is perceived by people. In this paper, we investigated how the type of transgressor (human or robot) and type of backstory depicting the transgressor's mental capabilities (default, physio-emotional, socio-emotional, or cognitive) shaped participants' perceptions of the transgressor's morality. We performed an online, between-subjects study in which participants (N =720) were first intro-duced to the transgressor and its backstory, and then viewed a video of a real-life robot or human pushing down a human. Although participants attributed similarly high intent to both the robot and the human, the human was generally perceived to have higher morality than the robot. However, the backstory that was told about the transgressors' capabilities affected their perceived morality. We found that robots with emotional backstories (i.e., physio-emotional or socio-emotional) had higher perceived moral knowledge, emotional knowledge, and desire than other robots. We also found that humans with cognitive backstories were perceived with less emotional and moral knowledge than other humans. Our findings have consequences for robot ethics and robot design for HRI.
Nicholas C. Georgiou, Teresa Flanagan, Brian Scassellati, Tamar Kushnir
HRI2
2023 Must there be an explanation? Children and the Principle of Sufficient Reason
Teresa Flanagan, Alejandro Vesga, Tamar Kushnir, Shaun Nichols
CogSci1
2019 Individual differences in fluency with idea generation predict children's beliefs in their own free will
Teresa Flanagan, Tamar Kushnir
CogSci1
2019 Do Children Ascribe the Ability to Choose to Humanoid Robots?
Teresa Flanagan, Joshua Rottman, Lauren Howard
CogSci1