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 < .001, k = 70) and improved their motivation (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.
*AndréV.JostC.HausbergerM.Le PévédicB.JubinR.DuhautD.LemassonA. (2014). Ethorobotics applied to human behaviour: Can animated objects influence children’s behaviour in cognitive tasks?Animal Behaviour, 96, 69–77. https://doi.org/10.1016/j.anbehav.2014.07.020
3.
*ArguedasM.DaradoumisT. (2021). Analysing the role of a pedagogical agent in psychological and cognitive preparatory activities. Journal of Computer Assisted Learning, 37(4), 1167–1180. https://doi.org/10.1111/jcal.12556
4.
AssinkM.WibbelinkC. J. M. (2016). Fitting three-level meta-analytic models in R: A step-by-step tutorial. The Quantitative Methods for Psychology, 12(3), 154–174. https://doi.org/10.20982/tqmp.12.3.p154
5.
AtkinsonR. K.MayerR. E.MerrillM. M. (2005). Fostering social agency in multimedia learning: Examining the impact of an animated agent’s voice. Contemporary Educational Psychology, 30(1), 117–139. https://doi.org/10.1016/j.cedpsych.2004.07.001
6.
BaylorA. L.KimY. (2005). Simulating instructional roles through pedagogical agents. International Journal of Artificial Intelligence in Education, 15(2), 95–115. https://doi.org/10.3233/irg-2005-15(2)02
7.
BeegeM.SchneiderS. (2023). Emotional design of pedagogical agents: The influence of enthusiasm and model-observer similarity. Educational Technology Research and Development, 71(3), 859–880. https://doi.org/10.1007/s11423-023-10213-4
8.
*Bøg PetersenG.KlingenbergS.MakranskyG. (2022). Pipetting in virtual reality can predict real-life pipetting performance. Technology, Mind, and Behavior, 3(3). https://doi.org/10.1037/tmb0000076
9.
Castro-AlonsoJ. C.WongR. M.AdesopeO. O.PaasF. (2021). Effectiveness of multimedia pedagogical agents predicted by diverse theories: A meta-analysis. Educational Psychology Review, 33(3), 989–1015. https://doi.org/10.1007/s10648-020-09587-1
10.
*ChenC.ChouM. (2015). Enhancing middle school students’ scientific learning and motivation through agent-based learning. Journal of Computer Assisted Learning, 31(5), 481–492. https://doi.org/10.1111/jcal.12094
11.
*ChenZ.-H.ChenS. Y. (2014). When educational agents meet surrogate competition: Impacts of competitive educational agents on students’ motivation and performance. Computers & Education, 75, 274–281. https://doi.org/10.1016/j.compedu.2014.02.014
12.
ChiouE. K.SchroederN. L.CraigS. D. (2020). How we trust, perceive, and learn from virtual humans: The influence of voice quality. Computers & Education, 146, 103756. https://doi.org/10.1016/j.compedu.2019.103756
13.
ClareboutG.ElenJ.JohnsonW. L.ShawE. (2002). Animated pedagogical agents: An opportunity to be grasped?Journal of Educational Multimedia and Hypermedia, 11(3), 267–286.
14.
ClarkR. E.ChoiS. (2007). The questionable benefits of pedagogical agents: Response to veletsianos. Journal of Educational Computing Research, 36(4), 379–381. https://doi.org/10.2190/2781-3471-67MG-5033
15.
CohenL.ManionL.MorrisonK. (2007). Research methods in education (6th ed.). Routledge.
16.
CowanN. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(1), 87–114. https://doi.org/10.1017/s0140525x01003922
17.
CowanN. (2010). The magical mystery four: How is working memory capacity limited, and why?Current Directions in Psychological Science, 19(1), 51–57. https://doi.org/10.1177/0963721409359277
18.
CraigS. D.SchroederN. L. (2017). Reconsidering the voice effect when learning from a virtual human. Computers & Education, 114, 193–205. https://doi.org/10.1016/j.compedu.2017.07.003
19.
*DaradoumisT.ArguedasM. (2020). Cultivating students’ reflective learning in metacognitive activities through an affective pedagogical agent. Journal of Educational Technology & Society, 23(2), 19–31.
20.
DavisR. O.ParkT.VincentJ. (2021). A systematic narrative review of agent persona on learning outcomes and design variables to enhance personification. Journal of Research on Technology in Education, 53(1), 89–106. https://doi.org/10.1080/15391523.2020.1830894
21.
DavisR. O.ParkT.VincentJ. (2023). A meta-analytic review on embodied pedagogical agent design and testing formats. Journal of Educational Computing Research, 61(1), 30–67. https://doi.org/10.1177/07356331221100556
22.
De JongT. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science, 38(2), 105–134. https://doi.org/10.1007/s11251-009-9110-0
23.
Deepbrain AI. (2023). Best ai video generator | deepbrain ai. Best Ai Video Generator | Deepbrain Ai. https://www.deepbrain.io/
24.
*DincerS.DoganayA. (2015). The impact of pedagogical agent on learners’ motivation and academic success. Practice and Theory in Systems of Education, 10(4), 329–348. https://doi.org/10.1515/ptse-2015-0032
25.
*DinçerS.DoğanayA. (2017). The effects of multiple-pedagogical agents on learners’ academic success, motivation, and cognitive load. Computers & Education, 111, 74–100. https://doi.org/10.1016/j.compedu.2017.04.005
26.
Fernández-CastillaB.DeclercqL.JamshidiL.BeretvasS. N.OnghenaP.Van den NoortgateW. (2020). Visual representations of meta-analyses of multiple outcomes: Extensions to forest plots, funnel plots, and caterpillar plots. Methodology, 16(4), 299–315. https://doi.org/10.5964/meth.4013
27.
*GenovaH. M.LancasterK.MorecraftJ.HaasM.EdwardsA.DiBenedettoM.KrchD.DeLucaJ.SmithM. J. (2021). A pilot RCT of virtual reality job interview training in transition-age youth on the autism spectrum. Research In Autism Spectrum Disorders, 89, 101878. https://doi.org/10.1016/j.rasd.2021.101878
28.
GladstoneJ. R.CimpianA. (2021). Which role models are effective for which students? A systematic review and four recommendations for maximizing the effectiveness of role models in STEM. International Journal of STEM Education, 8, 1–20. https://doi.org/10.1186/s40594-021-00315-x
29.
GladstoneJ. R.SchroederN. L.HeidigS.ZhangS.PalaguachiC.PiteraM. (2025). Do pedagogical agents enhance student motivation? Unraveling the evidence through meta-analysis. Educational Psychology Review, 37(3), 72. https://doi.org/10.1007/s10648-025-10050-2
30.
*GovindasamyM. K. (2013). Embodied agent in tutor role: Effects on field dependent and independent low achiever’s retention and perceived science self-efficacy beliefs. Journal of Educational Multimedia and Hypermedia, 22(3), 273–297.
31.
*GrynszpanO.BouteillerJ.GrynszpanS.MartinJ.-C.NadelJ. (2022). Social gaze training for Autism Spectrum Disorder using eye-tracking and virtual humans. Interaction Studies, 23(1), 89–115. https://doi.org/10.1075/is.21022.gry
32.
GuoY. R.GohD. H.-L. (2015). Affect in embodied pedagogical agents: Meta-analytic review. Journal of Educational Computing Research, 53(1), 124–149. https://doi.org/10.1177/0735633115588774
33.
HartholtA.TraumD.MarsellaS. C.ShapiroA.StratouG.LeuskiA.MorencyL.-P.GratchJ. (2013). All together now. In AylettR.KrennB.PelachaudC.ShimodairaH. (Eds.), Intelligent virtual agents. IVA 2013. Lecture notes in computer science (Vol. 8108, pp. 368–381). Springer.
34.
HattieJ. (2015). The applicability of Visible Learning to higher education. Scholarship of Teaching and Learning in Psychology, 1(1), 79–91. https://doi.org/10.1037/stl0000021
35.
HeidigS.ClareboutG. (2011). Do pedagogical agents make a difference to student motivation and learning?Educational Research Review, 6(1), 27–54. https://doi.org/10.1016/j.edurev.2010.07.004
*HongZ.-W.ChenY.-L.LanC.-H. (2014). A courseware to script animated pedagogical agents in instructional material for elementary students in English education. Computer Assisted Language Learning, 27(5), 379–394. https://doi.org/10.1080/09588221.2012.733712
38.
*JaquesP. A.LehmannM.PestyS. (2009). Evaluating the affective tactics of an emotional pedagogical agent [Conference session]. Proceedings of the 2009 ACM Symposium on Applied Computing, 104–109. Association for Computing Machinery. https://doi.org/10.1145/1529282.1529304
39.
*JingB.LiuJ.GongX.ZhangY.WangH.WuC. (2022). Pedagogical agents in learning videos: Which one is best for children?Interactive Learning Environments. Advance online publication. https://doi.org/10.1080/10494820.2022.2141787
40.
JohnsonA. M.OzogulG.MorenoR.ReissleinM. (2013). Pedagogical agent signaling of multiple visual engineering representations: The case of the young female agent. Journal of Engineering Education, 102(2), 319–337. https://doi.org/10.1002/jee.20009
41.
JohnsonW. L.RickelJ. (1997). Steve: An animated pedagogical agent for procedural training in virtual environments. ACM SIGART Bulletin, 8(1–4), 16–21. https://doi.org/10.1145/272874.272877
42.
*KimY. (2009). The role of learner attributes and affect determining the impact of agent presence. International Journal of Learning Technology, 4(3/4), 2–2. https://doi.org/10.1504/IJLT.2009.028808
43.
*KizilkayaG.AskarP. (2008). The effect of an embedded pedagogical agent on the students’ science achievement. Interactive Technology and Smart Education, 5(4), 208–216. https://doi.org/10.1108/17415650810930893
44.
*LeeT. T.MustaphaN. H. (2017). Who is more efficient: Teacher or pedagogical agents? In PutehM.AbdHamidN.AdenanN. (Eds.), Proceedings of the International Conference on Education, Mathematics, and Science 2016 (Vol. 1847). AIP Publishing. https://doi.org/10.1063/1.4983903
45.
*LeeT. T.OsmanK. (2012). Interactive multimedia module in the learning of electrochemistry: Effects on students’ understanding and motivation. In BaskanG.OzdamliF.KanbulS.OzcanD. (Eds.), 4th World Conference on Educational Sciences (Vol. 46, pp. 1323–1327). Elsevier Ltd. https://doi.org/10.1016/j.sbspro.2012.05.295
46.
LesterJ. C.ConverseS. A.KahlerS. E.BarlowS. T.StoneB. A.BhogalR. S. (1997). The persona effect: Affective impact of animated pedagogical agents [Conference session]. Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems, 359–366, Springer-Verlag, Berlin, Heidelberg.
47.
LinL.GinnsP.WangT.ZhangP. (2020). Using a pedagogical agent to deliver conversational style instruction: What benefits can you obtain?Computers & Education, 143, 103658. https://doi.org/10.1016/j.compedu.2019.103658
48.
LópezA. A.Guzman-OrthD.Zapata-RiveraD.ForsythC. M.LuceC. (2021). Examining the accuracy of a conversation-based assessment in interpreting English learners’ written responses. ETS Research Report Series, 2021(1), 1–15. https://doi.org/10.1002/ets2.12315
49.
MayerR. E. (2014a). Cognitive theory of multimedia learning. In MayerR. E. (Ed.), Cambridge handbook of multimedia learning (2nd ed., pp. 43–71). Cambridge University Press.
50.
MayerR. E. (2014b). Principles based on social cues in multimedia learning: Personalization, voice, image, and embodiment principles. In MayerR. E. (Ed.), The Cambridge handbook of multimedia learning (2nd ed., pp. 345–368). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.017
51.
MayerR. E. (2024). The past, present, and future of the cognitive theory of multimedia learning. Educational Psychology Review, 36(1), 8. https://doi.org/10.1007/s10648-023-09842-1
52.
MayerR. E.SobkoK.MautoneP. D. (2003). Social cues in multimedia learning: Role of speaker’s voice. Journal of Educational Psychology, 95(2), 419–425. https://doi.org/10.1037/0022-0663.95.2.419
53.
*MohammadhasaniN.FardaneshH.HatamiJ.MozayaniN.FabioR. A. (2018). The pedagogical agent enhances mathematics learning in ADHD students. Education & Information Technologies, 23(6), 2299–2308. https://doi.org/10.1007/s10639-018-9710-x
54.
*MorenoR.MayerR. E.SpiresH. A.LesterJ. C. (2001). The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents?Cognition and Instruction, 19(2), 177–213. https://doi.org/10.1207/S1532690XCI1902_02
55.
National Center for Education Statistics. (n.d.). Education indicators: An international perspective / indicator 1 side bar. ISCED Levels of Education. https://nces.ed.gov/pubs/eiip/eiip1s01.asp
56.
*NielenT. M. J.SmithG. G.Sikkema-de JongM. T.DrobiszJ.van HorneB.BusA. G. (2018). Digital guidance for susceptible readers: Effects on fifth graders’ reading motivation and incidental vocabulary learning. Journal of Educational Computing Research, 56(1), 48–73. https://doi.org/10.1177/0735633117708283
57.
*OkitaS. Y. (2008). Learn wisdom by the folly of others: Children learning to self correct by monitoring the reasoning of projective pedagogical agents (PQDT:64921281) [Doctoral dissertation]. Stanford University.
58.
*OkitaS. Y. (2014). Learning from the folly of others: Learning to self-correct by monitoring the reasoning of virtual characters in a computer-supported mathematics learning environment. Computers & Education, 71, 257–278. https://doi.org/10.1016/j.compedu.2013.09.018
59.
*OsmanK.LeeT. (2014). Impact of interactive multimedia module with pedagogical agents on students’ understanding and motivation in the learning of electrochemistry. International Journal of Science & Mathematics Education, 12(2), 395–421. https://doi.org/10.1007/s10763-013-9407-y
60.
PaasF.SwellerJ. (2014). Implications of cognitive load theory for multimedia learning. In The Cambridge handbook of multimedia learning (2nd ed., pp. 27–42). Cambridge University Press.
61.
PageM. J.McKenzieJ. E.BossuytP. M.BoutronI.HoffmannT. C.MulrowC. D.ShamseerL.TetzlaffJ. M.AklE. A.BrennanS. E.ChouR.GlanvilleJ.GrimshawJ. M.HróbjartssonA.LaluM. M.LiT.LoderE. W.Mayo-WilsonE.McDonaldS.MoherD. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71.
62.
PekrunR. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18(4), 315–341. https://doi.org/10.1007/s10648-006-9029-9
63.
PekrunR.FrenzelA. C.GoetzT.PerryR. P. (2007). The control-value theory of achievement emotions. In SchutzP. A.PekrunR. (Eds.), Emotion in education (pp. 13–36). Elsevier. https://doi.org/10.1016/B978-012372545-5/50003-4
64.
PekrunR.GoetzT.FrenzelA. C.BarchfeldP.PerryR. P. (2011). Measuring emotions in students’ learning and performance: The Achievement Emotions Questionnaire (AEQ). Contemporary Educational Psychology, 36(1), 36–48. https://doi.org/10.1016/j.cedpsych.2010.10.002
65.
PengT.-H.WangT.-H. (2022). Developing an analysis framework for studies on pedagogical agent in an e-learning environment. Journal of Educational Computing Research, 60(3), 547–578. https://doi.org/10.1177/07356331211041701
66.
PintrichP. R.MarxR. W.BoyleR. A. (1993). Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63(2), 167–199. https://doi.org/10.2307/1170472
67.
*PlantE. A.BaylorA. L.DoerrC. E.Rosenberg-KimaR. B. (2009). Changing middle-school students’ attitudes and performance regarding engineering with computer-based social models. Computers & Education, 53(2), 209–215. https://doi.org/10.1016/j.compedu.2009.01.013
68.
R Core Team. (2022). R: A language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing. https://www.r-project.org/
69.
RehmM.NakanoY.KodaT.Winschiers-TheophilusH. (2012). Culturally aware agent communication. In ZacariasM.de OliveiraJ. V. (Eds.), Human-computer interaction: The agency perspective (pp. 411–436). Springer.
70.
RodgersM. A.PustejovskyJ. E. (2021). Evaluating meta-analytic methods to detect selective reporting in the presence of dependent effect sizes. Psychological Methods, 26(2), 141–160. https://doi.org/10.1037/met0000300
71.
RyuJ.BaylorA. L. (2005). The psychometric structure of pedagogical agent persona. Technology, Instruction, Cognition and Learning, 2(4), 291–315.
72.
SchneiderS.BeegeM.NebelS.SchnaubertL.ReyG. D. (2022). The cognitive-affective-social theory of learning in digital environments (CASTLE). Educational Psychology Review, 34(1), 1–38. https://doi.org/10.1007/s10648-021-09626-5
73.
SchroederN. L. (2017). The influence of a pedagogical agent on learners’ cognitive load. Journal of Educational Technology & Society, 20(4), 138–147.
SchroederN. L.AdesopeO. O. (2014). A systematic review of pedagogical agents’ persona, motivation, and cognitive load implications for learners. Journal of Research on Technology in Education, 46(3), 229–251. https://doi.org/10.1080/15391523.2014.888265
76.
SchroederN. L.AdesopeO. O. (2015). Impacts of pedagogical agent gender in an accessible learning environment. Educational Technology & Society, 18(4), 401–411.
77.
SchroederN. L.AdesopeO. O.GilbertR. B. (2013). How effective are pedagogical agents for learning? A meta-analytic review. Journal of Educational Computing Research, 49(1), 1–39. https://doi.org/10.2190/EC.49.1.a
78.
SchroederN. L.CenkciA. T. (2020). Do measures of cognitive load explain the spatial split-attention principle in multimedia learning environments? A systematic review. Journal of Educational Psychology, 112(2), 254–270. https://doi.org/10.1037/edu0000372.
79.
SchroederN. L.GotchC. M. (2015). Persisting issues in pedagogical agent research. Journal of Educational Computing Research, 53(2), 183–204. https://doi.org/10.1177/0735633115597625
80.
SchroederN. L.RomineW. L.CraigS. D. (2017). Measuring pedagogical agent persona and the influence of agent persona on learning. Computers & Education, 109, 176–186. https://doi.org/10.1016/j.compedu.2017.02.015
81.
SchroederN. L.YangF.BanerjeeT.RomineW. L.CraigS. D. (2018). The influence of learners’ perceptions of virtual humans on learning transfer. Computers & Education, 126, 170–182. https://doi.org/10.1016/j.compedu.2018.07.005
82.
SiegleR. F.SchroederN. L.LaneH. C.CraigS. D. (2023). Twenty-five years of learning with pedagogical agents: History, barriers, and opportunities. TechTrends, 67(5), 851–864. https://doi.org/10.1007/s11528-023-00869-3
83.
SinatraG. M. (2005). The “warming trend” in conceptual change research: The legacy of Paul R. Pintrich. Educational Psychologist, 40(2), 107–115. https://doi.org/10.1207/s15326985ep4002_5
84.
*SinooC.van der PalS.HenkemansO. A. B.KeizerA.BiermanB. P. B.LooijeR.NeerincxM. A. (2018). Friendship with a robot: Children’s perception of similarity between a robot’s physical and virtual embodiment that supports diabetes self-management. Patient Education and Counseling, 101(7), 1248–1255. https://doi.org/10.1016/j.pec.2018.02.008
85.
SwellerJ. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22(2), 123–138. https://doi.org/10.1007/s10648-010-9128-5
86.
SwellerJ. (2020). Cognitive load theory and educational technology. Educational Technology Research and Development, 68(1), 1–16. https://doi.org/10.1007/s11423-019-09701-3
*van der MeijH.van der MeijJ.HarmsenR. (2015). Animated pedagogical agents effects on enhancing student motivation and learning in a science inquiry learning environment. Educational Technology Research & Development, 63(3), 381–403. https://doi.org/10.1007/s11423-015-9378-5
Van MulkenS.AndreE.MüllerJ. (1998). The persona effect: How substantial is it? In JohnsonH.NigayL.RoastC. (Eds.), People and computers XIII (pp. 53–66). Springer.
91.
VeletsianosG. (2010). Contextually relevant pedagogical agents: Visual appearance, stereotypes, and first impressions and their impact on learning. Computers & Education, 55(2), 576–585. https://doi.org/10.1016/j.compedu.2010.02.019
92.
ViechtbauerW. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. https://doi.org/10.18637/jss.v036.i03
ViechtbauerW.CheungM. W.-L. (2010). Outlier and influence diagnostics for meta-analysis. Research Synthesis Methods, 1(2), 112–125. https://doi.org/10.1002/jrsm.11
96.
WangY.FengX.GuoJ.GongS.WuY.WangJ. (2022). Benefits of affective pedagogical agents in multimedia instruction. Frontiers in Psychology, 12, Article 797236. https://doi.org/10.3389/fpsyg.2021.797236
97.
WangY.GongS.CaoY.LangY.XuX. (2023). The effects of affective pedagogical agent in multimedia learning environments: A meta-analysis. Educational Research Review, 38, N.PAG-N.PAG. https://doi.org/10.1016/j.edurev.2022.100506
98.
WuC.JingB.GongX.MaX. (2023). The zoomorphic effect: A contribution to the study of images of pedagogical agents for children’s learning in instructional videos. Journal of Computer Assisted Learning, 39(5), 1620–1635. https://doi.org/10.1111/jcal.12822
99.
YilmazF. G. K.OlpakY. Z.YilmazR. (2018). The effect of the metacognitive support via pedagogical agent on self-regulation skills. Journal of Educational Computing Research, 56(2), 159–180. https://doi.org/10.1177/0735633117707696
100.
*YılmazR.Kılıç-ÇakmakE. (2012). Educational interface agents as social models to influence learner achievement, attitude and retention of learning. Computers & Education, 59(2), 828–838. https://doi.org/10.1016/j.compedu.2012.03.020
101.
*YungH. I.PaasF. (2015). Effects of cueing by a pedagogical agent in an instructional animation: A cognitive load approach. Educational Technology & Society, 18(3), 153–160.
102.
ZhangS.JaldiC. D.SchroederN. L.GladstoneJ. R. (2024). Pedagogical agents in K–12 education: A scoping review. Journal of Research on Technology in Education, 1–28. https://doi.org/10.1080/15391523.2024.2381229
