Evidence map›Paper›PMID 41305301›Full record

ArticleSensors (Basel, Switzerland)2025

Designing Personalization Cues for Museum Robots: Docent Observation and Controlled Studies.

Heeyoon Yoon, Min-Gyu Kim, Sara Kim, Jin-Ho Suh

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Heeyoon YoonHuman-Robot Interaction Research Center, Korea Institute of Robotics and Technology Convergence, Pohang 37553, Republic of Korea.ORCID 0009-0003-3635-8629
Min-Gyu KimHuman-Robot Interaction Research Center, Korea Institute of Robotics and Technology Convergence, Pohang 37553, Republic of Korea.ORCID 0000-0003-0744-8812
Sara KimInstitute of Library, Information and Media Science, University of Tsukuba, Tsukuba 305-8550, Japan.ORCID 0000-0003-1868-3797
Jin-Ho SuhMajor of Mechanical System Engineering, Pukyong National University, Busan 48513, Republic of Korea.ORCID 0000-0002-8673-4528

Funding

Institute of Information and Communications Technology Planning and Evaluation (IITP) RS-2019-II190330Korea Evaluation Institute of Industrial Technology (KEIT) 20023495
6 · The paper itself

Abstract

Social robots in public cultural venues, such as science museums, must engage diverse visitors through brief, one-off encounters where long-term user modeling is infeasible. This research examines immediately interpretable behavioral cues of a robot that can evoke a sense of personalization without storing or profiling individual users. First, a video-based observational study of expert and novice museum docents identified service strategies that enable socially adaptive communication. Building on these insights, three controlled laboratory studies investigated how specific cues from robots influence user perception. A video-based controlled study examined how recognition accuracy shapes users' social impressions of the robot's intelligence. Additional studies based on the Wizard-of-Oz (WoZ) method tested whether explanatory content aligned with participants' background knowledge and whether explicit preference inquiry and memory-based continuity strengthened perceptions of personalization. Results showed that recognition accuracy improved social impressions, whereas knowledge alignment, explicit preference inquiry, and memory-based continuity cues increased perceived personalization. These findings demonstrate that micro-level personalization cues, interpretable within a short-term encounter, can support user-centered interaction design for social robots in public environments.

Indexed as

CuesMuseumsRoboticsAdultFemaleHumansMalehuman–robot interactionknowledge alignmentmemory continuityperceived personalizationpreference inquiryscience museumvisual recognition accuracy

Identifiers

PMID41305301
PMCPMC12656183

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.