Evidence map›Paper›PMID 42232318›Full record

ArticleFrontiers in robotics and AI2026

Exploring child engagement in a multi-robot tutor-peer learning scenario.

Luca Raggioli, Rahul Singh Maharjan, Joanna Kolak, Gemma Taylor, Amanda Banks Gatenby, Angelo Cangelosi

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

6 authors.

Luca RaggioliDepartment of Neuroscience, and Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy.
Rahul Singh MaharjanManchester Centre for Robotics and AI, University of Manchester, Manchester, United Kingdom.
Joanna KolakDepartment of Psychology and Human Development, Institute of Education, University College London, London, United Kingdom.
Gemma TaylorDepartment of Psychology, University of Salford, Salford, United Kingdom.
Amanda Banks GatenbyManchester Institute of Education, University of Manchester, Manchester, United Kingdom.
Angelo CangelosiManchester Centre for Robotics and AI, University of Manchester, Manchester, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The use of social robots in education has increasingly focused on how different role framings, such as tutor, peer, or novice, shape children's engagement and learning. However, most studies employ a single robot whose role is manipulated behaviourally (e.g., the same robot is used to act either as a peer or as a tutor), leaving open the question of how children respond when multiple, physically distinct robots adopt complementary roles within the same session. Methods: In this exploratory feasibility study, we introduce a blue multi-robot learning environment in which one robot acts as a tutor and the other as a novice peer. The robots supported an early word-learning task in which children learned novel object names and were later asked to name or identify them. In the proposed scenario, participants were exposed to novel words assigned to unusual or unconventional objects (e.g., dog toys and shapes made with interlocking disks), alongside familiar objects. After an initial training phase, children were asked to locate or name the novel items. Sixteen children aged 4-5 years interacted with both robots while their attention, affect, and engagement behaviours were recorded. The study characterised children's distribution of attention during a word-learning task involving a tutor and a novice peer robot, including attention to task-relevant objects and robots and its relation to attentional complexity, affect, and engagement, as well as the relation between individual characteristics (language ability, age, and media exposure) and task performance, measured as correct naming or pointing during recall. Results: Children consistently attended to task-relevant objects throughout the session, with attention distributed across objects and robots in structured patterns. Attentional complexity co-occurred with sustained engagement and positive affect. Task performance and engagement showed little variation with age or media exposure, while baseline language ability was negatively associated with recall performance. Discussion: Overall, the findings indicate that a multi-robot learning configuration is feasible and capable of supporting sustained engagement and structured attentional behaviour in young children. While the results are exploratory and limited by sample size, they provide initial evidence that complementary robot roles can be meaningfully integrated within early learning activities and motivate further systematic investigation.

Indexed as

child engagementchild-robot interactionearly language learningmulti-robot systemssocial robots

Identifiers

PMID42232318
PMCPMC13222814

What OpenQuestion holds

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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.