A Scoping Review of Large Language Model-Based Pedagogical Agents
This scoping review examines the emerging field of Large Language Model (LLM)-based pedagogical agents in educational settings. While traditional pedagogical agents have been extensively studied, the integration of LLMs represents a transformative advancement with unprecedented capabilities in natural language understanding, reasoning, and adaptation. Following PRISMA-ScR guidelines, we analyzed 52 studies across five major databases from November 2022 to January 2025. Our findings reveal diverse LLM-based agents spanning K-12, higher education, and informal learning contexts across multiple subject domains. We identified four key design dimensions characterizing these agents: interaction...
| Authors | Shan Li, Juan Zheng |
|---|---|
| Primary category | cs.AI |
| Published | 14 April 2026 |
| Last updated at source | 18 May 2026 |
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