基于大数据的多源多维 综合素质评价模型的构建

Construction of Multi-source and Multi-dimensional Comprehensive Quality Evaluation Model Based on Big

The comprehensive quality evaluation of senior high school has become the breakthrough of comprehensive education reform. It is difficult for traditional educational evaluation which based on examination to assess students' learning outcomes and development potential. Big data make it possible to record students' learning behavior and resulting data. Combined with the development of data analysis techniques and learning science， this paper attempts to build a multi-source and multi-dimensional comprehensive quality evaluation model based on large data technology. The background is the reform of comprehensive quality evaluation in Shanghai. The model can take the convergence and integration of multi-source data into account， trying to expand the scope of student objective information to the inside and outside of the classroom， formal and informal learning environment， offline and online learning， learning activities and life performance and other perspectives， and get the data that can map the students'comprehensive quality， forming systematic and complete big data of Student growth. Integrating and standardizing multisource data which can reflect comprehensive quality of students， the article constructs a learning analysis model to carry out big data analysis， finally， forming digital portraits of comprehensive quality for individual and group based on big data. The model provides value judgments and result output in multiple dimensions to provide evidence in the aspects of learning and learning environment improvements as well as student development and talent classification selection. The model will provide a useful solution for the flourishing reform of comprehensive quality evaluation in senior high school.