Lauren Sy

dblp:344/8907 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-0742-9120ORCID · reported

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
Collaborative and social computing · 56% Human-robot interaction · 44%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing
mixed reality collaboration
0.712023
UnMapped: Leveraging Experts' Situated Experiences to Ease Remote Guidance in Collaborative Mixed Reality · CHI 2023
Human-robot interaction › cognitive human-robot interaction › spatial cognition
spatial memory
0.712023
UnMapped: Leveraging Experts' Situated Experiences to Ease Remote Guidance in Collaborative Mixed Reality · CHI 2023
Collaborative and social computing › remote collaboration
remote assistance
0.212023
UnMapped: Leveraging Experts' Situated Experiences to Ease Remote Guidance in Collaborative Mixed Reality · CHI 2023

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

interface design · 0.7comparative study · 0.7
YearPublicationVenuePosition
2023 UnMapped: Leveraging Experts' Situated Experiences to Ease Remote Guidance in Collaborative Mixed Reality
abstract
Collaborative Mixed Reality (MR) systems that help extend expertise for physical tasks to remote environments often situate experts in an immersive view of the task environment to bring the collaboration closer to collocated settings. In this paper, we design UnMapped, an alternative interface for remote experts that combines a live 3D view of the active space within the novice’s environment with a static 3D recreation of the expert’s own workspace to leverage their existing spatial memories within it. We evaluate the impact of this approach on single and repeated use of collaborative MR systems for remote guidance through a comparative study. Our results indicate that despite having a limited understanding of the novice’s environment, using an UnMapped interface increased performance and communication efficiency while reducing experts’ task load. We also outline the various affordances of providing remote experts with a familiar and spatially-stable environment to assist novices.
Janet G. Johnson, Thomas Sharkey, Iramuali Cynthia Butarbutar, Danica Xiong, Ruijie Huang, Lauren Sy, Nadir Weibel
CHI6