标题： 在线参与度监控的实时度量 显示英文标题

标题： A real-time metric of online engagement monitoring

摘要： 衡量在线学生行为参与度通常依赖于简单的计数指标或回顾性、预测方法，这在实时应用中存在挑战。 为解决这些局限性，我们重新概念化了一个现有的课程范围内的参与度指标，以创建一个与在线课程每周结构相一致的章节级版本。 该新指标直接来源于虚拟学习环境的日志数据，允许累积的实时跟踪学生活动，而无需结果数据或模型训练。 我们在两个学年内的三个本科统计模块中评估了该方法，并将其与课程范围的版本进行比较，以评估重新概念化如何影响所测量的内容。 结果表明，从第3周开始就表现出强烈的吻合度，并在结构化、以讲座为主的环境中对最终成绩的预测效度具有可比性或改进。 在课程中期，每周指标能够识别出与课程结束时同样数量的低绩效学生。 尽管各模块的表现有所不同，但基于章节的版本为早期参与度监测和学生支持提供了一种可扩展且易于理解的方法。 显示英文摘要

摘要： Measuring online behavioural student engagement often relies on simple count indicators or retrospective, predictive methods, which present challenges for real-time application. To address these limitations, we reconceptualise an existing course-wide engagement metric to create a chapter-based version that aligns with the weekly structure of online courses. Derived directly from virtual learning environment log data, the new metric allows for cumulative, real-time tracking of student activity without requiring outcome data or model training. We evaluate the approach across three undergraduate statistics modules over two academic years, comparing it to the course-wide formulation to assess how the reconceptualisation influences what is measured. Results indicate strong alignment from as early as week 3, along with comparable or improved predictive validity for final grades in structured, lecture-based contexts. By the course midpoint, the weekly metric identifies as many low-performing students as are identifiable by the end of the course. While performance varies across modules, the chapter-based formulation offers a scalable and interpretable method for early engagement monitoring and student support.