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教学能力培养是职前教师教育的核心内容,但传统培养方式存在供给失衡、反馈主观以及评价滞后等问题。随着生成式人工智能的快速发展,人机融智成为职前教师教学能力培养的新方向。研究首先梳理了职前教师教学能力培养的现状、多智能体赋能人机融智教学能力提升的方式;其次,基于分布式认知理论和共生理论,构建了涵盖专项技能分析、综合反馈及个性化教练三类功能的多智能体系统,以及多智能体支持的人机融智实训框架;最后,通过实践验证了该框架能显著提高职前教师的教学能力,析出职前教师利用多智能体实训中的四类典型认知参与行为路径:问题解决型路径、协作优化型路径、元认知调节型路径以及批判反思型路径,以期为多智能体赋能职前教师高质量培养提供参考。
Abstract：The cultivation of teaching competence is a core element of pre-service teacher education, yet traditional approaches are constrained by insufficient provision, subjective feedback, and delayed evaluation. With the rapid advancement of generative artificial intelligence, human-machine collaborative intelligence has emerged as a promising direction for enhancing pre-service teachers' professional preparation. This study first reviews the current status of teaching competence cultivation and examines how human-machine collaborative intelligence can improve its effectiveness. Drawing on distributed cognition theory and symbiosis theory, it then develops a multi-agent system with three core functions, including specialized skill analysis, integrated feedback, and personalized guidance, and proposes a training framework for pre-service teachers supported by multi-agent human-machine collaborative intelligence. Empirical evidence further confirms that this framework significantly improves teaching competence. Moreover, four typical cognitive engagement pathways are identified during the training process: problem-solving, collaboration optimization, metacognitive regulation, and critical reflection. The findings provide theoretical foundations and practical implications for advancing the high-quality cultivation of pre-service teachers through multi-agent empowerment.
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基本信息:
中图分类号:G652;G434
引用信息:
[1]刘晓红,朱敏捷,陈孝然,等.多智能体支持的职前教师教学能力实训：建构、实施与成效剖析[J].中国电化教育,2026,No.472(05):111-118.
基金信息:
2024年国家社会科学基金一般项目“教师数字胜任力伴随式智能测评研究”(项目编号:BCA240050)研究成果
2026-05-10
2026-05-10