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Record W4313040844 · doi:10.1109/hri53351.2022.9889672

“Let's read a book together”: A Long-term Study on the Usage of Pre-school Children with Their Home Companion Robot

2022· article· en· W4313040844 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI) · 2022
Typearticle
Languageen
FieldPsychology
TopicSocial Robot Interaction and HRI
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRobotReading (process)Term (time)Social robotFunction (biology)Variety (cybernetics)PsychologyComputer scienceDevelopmental psychologyHuman–computer interactionArtificial intelligenceMobile robotRobot controlPolitical science

Abstract

fetched live from OpenAlex

In several countries, social robots are increasingly accessible within homes, particularly in those with pre-school-aged children. However, research on social robots has mostly been conducted in laboratory or classroom settings, and their long-term use has received little attention. Additionally, while there is a growing body of literature on CRI in a variety of domains such as education and health, less is known about the interactions between children and social robots in home settings during daily activities. Conducted during the Covid-19 pandemic, this article describes a longitudinal mixed-method study that examines children's interactions with their home reading companion robot - Luka. Focusing on parental perspectives, we examined how children interact with robots over time and revealed that a social robot with reading as its primary function has the potential to both attract parental buyers and engage children in long-term use of the robot's diverse features. We offer recommendations for social robot designers and product developers targeting younger users.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.576
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0920.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.189
GPT teacher head0.433
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it