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Adaptive Versus Non-adaptive Mathematics Tutoring by Social Robots in Tanzanian Primary Schools

 
cris.virtual.department#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.orcid0000-0001-5207-7745
cris.virtualsource.department6c1aac4b-593e-4f80-9ecc-911fd20f3c31
cris.virtualsource.orcid6c1aac4b-593e-4f80-9ecc-911fd20f3c31
dc.contributor.authorNtahomvukye, Elina C.
dc.contributor.authorRutatola, Edger P.
dc.contributor.authorDaudi, Morice
dc.contributor.authorKomba, Mercy Mlay
dc.contributor.authorStroeken, Koen
dc.contributor.authorBelpaeme, Tony
dc.date.accessioned2026-07-23T12:59:22Z
dc.date.available2026-07-23T12:59:22Z
dc.date.createdwos2026
dc.date.issued2025
dc.description.abstractThe use of social robots in education is increasingly being explored as a way to enhance learner engagement and improve learning outcomes. However, most research to date has focused on one-to-one tutoring in high-resource settings, leaving open questions about how social robots perform in group learning contexts—especially in low-resource environments. This study is one of the first to investigate human-robot interaction (HRI) in a low-resource African context, specifically in Tanzanian primary schools. We examined how a social robot tutor can support group-based mathematics learning, comparing the effects of adaptive versus non-adaptive tutoring strategies. Through an experimental, mixed-methods research design, we evaluated pupils’ learning outcomes, engagement, and classroom interactions. Our findings show that social robot tutoring has a significant positive impact on learning outcomes, with adaptive tutoring leading to slightly higher knowledge gains than non-adaptive tutoring. Qualitative observations further reveal that the presence of the robot fostered motivation, engagement, and collaborative classroom dynamics. This work demonstrates the potential of social robots to support group learning in under-resourced educational settings and highlights the importance of extending HRI research beyond well-resourced contexts.
dc.description.wosFundingTextWe extend our gratitude to VLIR-UOS for funding this study through Mzumbe University and Ghent University's IoT-4-Youths (TZ2023SIN398A103) and AI4STEM (TZ2024TEA570A103) projects. We also appreciate all the participants for their time and valuable insights. Lastly, we thank the Government of Tanzania for providing the necessary permits that facilitated a smooth research process.
dc.identifier.doi10.1109/ro-man63969.2025.11217562
dc.identifier.isbn979-8-3315-8772-7
dc.identifier.issn1944-9445
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/59946
dc.language.isoeng
dc.provenance.editstepusergreet.vanhoof@imec.be
dc.publisherIEEE
dc.relation.ispartofseriesIEEE RO-MAN
dc.source.beginpage1658
dc.source.conference34th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
dc.source.conferencedate2025-08-25
dc.source.conferencelocationEindhoven
dc.source.endpage1663
dc.source.journal2025 34TH IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION, RO-MAN
dc.source.numberofpages6
dc.title

Adaptive Versus Non-adaptive Mathematics Tutoring by Social Robots in Tanzanian Primary Schools

dc.typeProceedings paper
dspace.entity.typePublication
imec.internal.crawledAt2025-10-22
imec.internal.sourcecrawler
imec.internal.wosCreatedAt2026-07-14
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