AI生成多模态反馈效果不输真人，还更受学生欢迎。
LLM-based Multimodal Feedback Produces Equivalent Learning and Better Student Perceptions than Educator Feedback
- 用AI整合文字、音频和课件链接，实时生成多模态反馈。
- 学习效果相当，但学生觉得AI反馈更清晰、简洁、提神。
- 适合想减轻备课负担的教师和追求即时反馈的学生。
及时、精准、多模态的反馈有助于学生快速纠错、深化理解并保持动力，但规模化实施仍具挑战。本研究提出一种实时AI驱动的多模态反馈系统，整合结构化文本说明与动态多媒体资源，包括检索到的相关幻灯片页码及流式AI语音解说。在一项在线众包实验中，该系统与教师固定反馈在三个维度上对比：(1) 学习效果，(2) 学习投入度，(3) 反馈感知质量与价值。结果表明，AI多模态反馈在学习成效上等同于原教师反馈，且在感知清晰度、具体性、简洁性、动机激发、满意度方面显著优于教师反馈，同时降低认知负荷，正确率、信任度与接受度相当。过程日志显示：对选择题，教师反馈促使更多提交；对开放题，AI靶向建议降低了修改门槛，促进迭代改进。研究证实，AI多模态反馈可实现可扩展、实时、情境感知的支持，在减轻教师负担的同时提升学生体验。
原文摘要 · Abstract (English)
Providing timely, targeted, and multimodal feedback helps students quickly correct errors, build deep understanding and stay motivated, yet making it at scale remains a challenge. This study introduces a real-time AI-facilitated multimodal feedback system that integrates structured textual explanations with dynamic multimedia resources, including the retrieved most relevant slide page references and streaming AI audio narration. In an online crowdsourcing experiment, we compared this system against fixed business-as-usual feedback by educators across three dimensions: (1) learning effectiveness, (2) learner engagement, (3) perceived feedback quality and value. Results showed that AI multimodal feedback achieved learning gains equivalent to original educator feedback while significantly outperforming it on perceived clarity, specificity, conciseness, motivation, satisfaction, and reducing cognitive load, with comparable correctness, trust, and acceptance. Process logs revealed distinct engagement patterns: for multiple-choice questions, educator feedback encouraged more submissions; for open-ended questions, AI-facilitated targeted suggestions lowered revision barriers and promoted iterative improvement. These findings highlight the potential of AI multimodal feedback to provide scalable, real-time, and context-aware support that both reduces instructor workload and enhances student experience.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。