人工智能智能体赋能BOPPPS教学的设计与实现

Design and Implementation of AI Agent Empowered BOPPPS Instruction

摘要: BOPPPS教学模式以目标导向和参与式学习为核心理念，已在高校课堂中得到广泛应用，但在大班教学场景中，教师仍面临教案生成耗时长、课堂测评即时分析难、个性化学习反馈不足等现实问题。本研究设计并开发了一款深度融合AI智能体的BOPPPS教学辅助平台，围绕导入、目标、前测、参与式学习、后测、总结六大环节，分别实现了情境素材智能推荐、学习目标对齐检查、自适应前测组卷、分层任务与即时答疑、多维后测评价以及教学证据自动汇总等功能。平台采用教师审核与系统生成协同的工作机制，所有AI输出均需经人工确认方可生效，以保障内容质量与教学安全。实验数据表明，该平台能显著缩短教师备课时间，提升课堂互动频率与测评反馈时效性，为AI技术嵌入结构化教学流程提供了一条可操作的实现路径。

Abstract: The BOPPPS teaching model, centered on outcome orientation and participatory learning, has been widely adopted in higher education. However, in large-class settings, teachers continue to face practical challenges, including time-consuming lesson preparation, difficulties in real-time analysis of classroom assessments, and insufficient personalized learning feedback. This study designed and developed an AI agent-enhanced instructional support platform deeply integrated with the BOPPPS model. Across its six stages—Bridge-in, Objective, Pre-assessment, Participatory Learning, Post-assessment, and Summary, the platform provides intelligent recommendations of contextual materials, alignment checks for learning objectives, adaptive generation of pre-assessment items, differentiated learning tasks and real-time question answering, multidimensional post-assessment, and automated aggregation of instructional evidence. The platform adopts a human-AI collaborative workflow in which all AI-generated outputs must be reviewed and approved by teachers before implementation, thereby ensuring content quality and instructional safety. Experimental results indicate that the platform significantly reduces teachers’ lesson preparation time, increases the frequency of classroom interaction, and improves the timeliness of assessment feedback, offering an actionable approach to embedding AI technologies into structured instructional processes.