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Virtual Characters Help K–12 Students Learn and Improve Motivation

A Meta-Analysis

Datos Bibliográficos

ID21380997
AutoresNoah L Schroeder (0000-0002-3281-2594, University of Florida, autor de correspondencia), Shan Zhang (0000-0001-5142-1559, University of Florida), Chris Davis Jaldi (0009-0000-2287-1198, Wright State University), Jessica R Gladstone (0000-0001-6030-6288, University of Illinois Urbana-Champaign), Alexis A Lopez (0000-0002-4616-1091, Educational Testing Service), Emmanuel Dorley (0000-0002-8624-7295, University of Florida)
Año2025
Fecha de publicación2025-11-29
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaReview of Educational Research (JOURNAL)
Identificadores de la revistaISSN: 0034-6543 • E-ISSN: 1935-1046
EditorialAmerican Educational Research Association (AERA) (PUBLISHER)
DOI10.3102/00346543251389930
OpenAlexW4416823136
IdiomaEN
Citas recibidas1
Referencias citadas87

Pedagogical agents, conversational agents, motivational agents, and other virtual characters have long been used in educational technologies. We built and analyzed the most comprehensive dataset to date of studies examining how virtual characters influence K–12 students’ learning and learning-related outcomes using three-level meta-analytic procedures. The results from five three-level meta-analyses indicate that virtual characters helped K–12 students learn (g = 0.42, p g = 0.48, p = .001, k = 47) but did not have any significant effects on emotions ( g = 0.60, p = .20, k = 15), perceptions (g = 0.05, p = .88, k = 34), or cognitive load ( g = −0.09, p = .84, k = 5) compared to systems without a virtual character present. We conclude that virtual characters can provide a meaningful addition to learning environments for K–12 learners

Character (mathematics) · Cognition · Cognitive Load · Instructional simulation · Perception · Virtual learning environment · Virtual reality · AI in Service Interactions · Social Robot Interaction and HRI · Virtual Reality Applications and Impacts

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Obras citantes distintas1
Citas por año1
Intervalo de citas2026 - 2026 (1)
Velocidad de citacióncurrent
Altamente citadoNo
Tipos de citaNeutras: 1
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