摘要
针对MOOC教学评价中存在的评价维度单一、数据驱动能力不足及反馈应用脱节等问题,本文提出以“知识掌握、过程参与、实践能力、学习态度”为核心的“四维一体”动态评价框架。通过整合多源学习行为数据,结合随机森林算法构建动态评价模型,实现89.7%的学习风险预测准确率,并依托“评价-认证-激励”闭环机制,创新学分银行制度与教师发展积分体系,推动评价结果向教学改进的实质性转化。以《工程施工组织与管理》课程为实证对象,验证了动态化指标与产教融合机制对教学质量的显著提升作用。本研究为MOOC教学评价体系提供了可操作的智能重构路径与机制优化方案,对促进教育数字化转型与学习者个性化发展具有重要实践价值。
Aiming to address the issues of single-dimensional evaluation,insufficient data-driven capabilities,and disconnected feedback application in MOOC teaching evaluations,this work proposes a"four-dimension integrated"dynamic evaluation framework centered on"knowledge mastery,process participation,practical ability,and learning attitude".By integrating multi-source learning behavior data and employing the random forest algorithm to construct a dynamic evaluation model,an 89.7%prediction accuracy for learning risks is achieved.Furthermore,leveraging the closed-loop mechanism of"evaluation-certification-incentive,"this work innovatively designs a credit bank system and a teacher development point system to facilitate the substantive transformation of evaluation results into teaching improvements.Taking the course"Engineering Construction Organization and Management"as an empirical case,this work verifies the significant impact of the dynamic index and production-teaching integration mechanism on enhancing teaching quality.This research could provide an actionable intelligent reconstruction path and mechanism optimization solution for the MOOC teaching evaluation system,and offer important practical value for promoting the digital transformation of education and the personalized development of learners.
作者
史慧芳
潘格林
樊海霞
SHI Huifang;PAN Gelin;FAN Haixia(School of Smart City Engineering,Qingdao Huanghai University,Qingdao,Shandong,266000,China)
出处
《水利与建筑工程学报》
2025年第4期240-246,共7页
Journal of Water Resources and Architectural Engineering
基金
青岛黄海学院校级一流本科课程教改项目(hhxyjg2211)。
