TY - JOUR
T1 - Do Generative AI-Powered Pedagogical Agents Improve Learners’ Academic Performance Effectively? Evidence From Meta-Analysis
AU - Cheng, Liang
AU - Shi, Hui
AU - Wu, Yuhan
AU - Li, Feng
N1 - Publisher Copyright:
© The Author(s) 2025
PY - 2025
Y1 - 2025
N2 - With the breakthrough advancements in generative artificial intelligence (GenAI) technology, GenAI-powered pedagogical agents (GenAI-PA) are emerging as a transformative paradigm shift in education. However, there is still debate about whether the use of GenAI-PA is beneficial for learners’ academic performance. Therefore, this study conducted a meta-analysis of 27 experimental and quasi-experimental studies from 2015 to 2025. The results showed that (1) GenAI-PA had a significant effect on learners’ academic performance (g = 0.401). (2) In a collectivist culture, GenAI-PA had a greater effect on learners’ academic performance. (3) The effect of GenAI-PA in teacher-directed learning was significantly better than in self-directed learning. (4) The dialogue modality of GenAI-PA moderated the effect on learners’ academic performance, with multimodal dialogue showing the highest pedagogical potential. (5) The predictive effect of GenAI-PA on learners’ academic performance was not influenced by grade level, gender, learning domain, learning duration, or the instructional role of GenAI-PA. Ultimately, recommendations for the design and application of GenAI-PA are discussed.
AB - With the breakthrough advancements in generative artificial intelligence (GenAI) technology, GenAI-powered pedagogical agents (GenAI-PA) are emerging as a transformative paradigm shift in education. However, there is still debate about whether the use of GenAI-PA is beneficial for learners’ academic performance. Therefore, this study conducted a meta-analysis of 27 experimental and quasi-experimental studies from 2015 to 2025. The results showed that (1) GenAI-PA had a significant effect on learners’ academic performance (g = 0.401). (2) In a collectivist culture, GenAI-PA had a greater effect on learners’ academic performance. (3) The effect of GenAI-PA in teacher-directed learning was significantly better than in self-directed learning. (4) The dialogue modality of GenAI-PA moderated the effect on learners’ academic performance, with multimodal dialogue showing the highest pedagogical potential. (5) The predictive effect of GenAI-PA on learners’ academic performance was not influenced by grade level, gender, learning domain, learning duration, or the instructional role of GenAI-PA. Ultimately, recommendations for the design and application of GenAI-PA are discussed.
KW - academic performance
KW - generative artificial intelligence
KW - human-computer interaction
KW - meta-analysis
KW - pedagogical agents
UR - https://www.scopus.com/pages/publications/105022155644
U2 - 10.1177/07356331251400540
DO - 10.1177/07356331251400540
M3 - 文献综述
AN - SCOPUS:105022155644
SN - 0735-6331
JO - Journal of Educational Computing Research
JF - Journal of Educational Computing Research
ER -