Linux实验课程是计算机类与信息类专业基础核心课程,具有较强的实践性和复杂的操作链条。传统评价系统多依赖学生提交的实验报告,存在结果导向强、缺乏过程分析、情境感知能力不足等问题,难以全面、动态地反映学生实际能力与学习状态。为此,提出一种融合知识图谱与多模态感知的Linux实验课程评价体系,通过融合代码行为分析、语音与表情情感识别、系统操作轨迹提取和知识图谱推理等关键技术,构建覆盖“教—学—评”全过程的智能化评价机制。系统以学生行为日志、语音答辩、表情图像、操作流程、错误类型为多模态输入,利用焦点对比学习机制与Neo4j知识图谱模型实现综合评分与个性化反馈。实验结果表明,该体系在评价准确性、一致性、学生学习动机激发成效等方面取得显著提升,可为Linux等系统类实验课程的教学改革提供新范式与技术支撑。
Abstract
The Linux laboratory course is a fundamental core course for computer science and information related majors, characterized by strong practicality and complex operational chains. Traditional evaluation systems mainly rely on students' submitted lab reports, which are result-oriented, lacking process analysis and contextual awareness, making it difficult to comprehensively and dynamically reflect students’ actual abilities and learning status. To this end, this paper proposes an evaluation system for Linux laboratory courses that integrates knowledge graphs with multimodal perception. It integrates key technologies such as code behavior analysis, speech and facial emotion recognition, system operation trajectory extraction, and knowledge graph reasoning. The system takes multimodal inputs—including student behavior logs, oral defense speech, facial expressions, operation flows, and error types—and applies focal contrastive learning and a Neo4j-based knowledge graph model to achieve comprehensive scoring and personalized feedback. Experimental results demonstrate that the proposed system significantly improves evaluation accuracy, consistency, and the stimulation of students’ learning motivation, providing a new paradigm and technological support for teaching reform in Linux and other system-oriented laboratory courses.
关键词
Linux实验课程 /
知识图谱 /
多模态感知 /
焦点对比学习
Key words
Linux laboratory course /
knowledge graph /
multimodal perception /
focal contrastive learning
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参考文献
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基金
教育部产学合作协同育人项目“产教融合视域下Linux操作系统课程教学内容与实践体系改革研究”,项目编号：250503492302259; 广东省自然科学基金面上项目“基于区块链的高效农产品质量安全可信追溯模型及系统研究”,项目编号：2023A1515011230
