作业数据驱动的大规模因材施教——上海市闵行区“智慧教育示范区”创建实践

Assignment Data Driven Mass Teaching Based upon the Students’Ability:The Practice of Creating a“Smart Education Demonstration Zone”in Minhang District,Shanghai

在“智慧教育示范区”创建和基础教育数字化转型的大背景下,为了打造优质均衡的教育体系,满足每个学生的发展需求,上海市闵行区在区域层面构建了区校两级作业系统,梳理了作业业务的构成要素,对作业业务各个环节进行量化。通过伴随式采集数据,形成区域作业数据驱动大规模因材施教的模型,并将知识状态追踪模型、学科核心能力评价模型、学习品质模型、学生综合画像模型等四个模型作为子模型。通过模型应用,开展基于知识状态的个性化辅导、学习策略和学习意志力的分层教学、学习投入的分层教学等实践,形成通过作业数据发掘差异的新路径。基于区域探索性数据分析,证明通过作业数据可以发掘学生的“材”,且发掘的结果既符合教师已有经验,又能弥补经验的不足。经实践证明,精准“施教”具有可行性,可为数据驱动的大规模因材施教提供参考。

Under the context of the creation of the“Smart Education Demonstration Zone”and the digital transformation of K12,in order to build a high-quality and balanced education system and meet the development needs of each student,Minhang District in Shanghai has built a district and school assignment system at the regional level,sorted out the components of the assignment work and quantified each aspect of the assignment work.Through concomitant data collection,a regional homework data-driven model for large-scale teaching and learning based on students’abilities was formed,and four models,including the model of knowledge state tracking,that of subject core competency assessment,that of learning quality and a comprehensive student portrait model,were explored and formed as sub-models.Through the application of the model,personalized tutoring based on knowledge level,tiered teaching of learning strategies and willpower to learn,and tiered teaching practice of learning input are carried out,forming a path to uncover differences through homework data.Based on the regional exploratory data analysis,it has been proved that students’talents can be discovered through homework data,and the discoveries are in line with teachers’existing experience and can make up for the shortcomings of experience.It has been demonstrated that precision‘teaching’is feasible and can be used as a reference for data-driven,large-scale teaching of students’ability.