Demo Data from EDBT 2026 / reviewers in the wild / expert
Daniela Di Canio
dblp:319/3673
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 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
1 paper |
Learning and educational technologies · 56% Human-robot interaction · 44% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Learning and educational technologies
embodied learning |
0.6 | 1 | 2022 | Embodied Geometric Reasoning with a Robot: The Impact of Robot Gestures on Student Reasoning about Geometrical Conjectures · CHI 2022 |
Human-robot interaction › nonverbal communication
robot gesture |
0.6 | 1 | 2022 | Embodied Geometric Reasoning with a Robot: The Impact of Robot Gestures on Student Reasoning about Geometrical Conjectures · CHI 2022 |
Methods — techniques the papers use, named apart from their topics
randomized controlled study · 0.6embodied cognition · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Embodied Geometric Reasoning with a Robot: The Impact of Robot Gestures on Student Reasoning about Geometrical ConjecturesabstractIn this paper, we explore how the physically embodied nature of robots can influence learning through non-verbal communication, such as gesturing. We take an embodied cognition perspective to examine student interactions with a NAO robot that uses gestures while reasoning about geometry conjectures. College aged students (N = 30) were randomly assigned to either a dynamic condition, where the robot uses dynamic gestures that represent and manipulate geometric shapes in the conjectures, or control condition, where the robot uses beat gestures that match the rhythm of speech. Students in the dynamic condition: (1) use more gestures when they reason about geometry conjectures, (2) look more at the robot as it speaks, (3) feel the robot is a better study partner and uses effective gestures, but (4) were not more successful in correctly reasoning about geometry conjectures. We discuss implications for socially supported and embodied learning with a physically present robot. Joseph E. Michaelis, Daniela Di Canio |
CHI | 2 |