教师提升数据智慧的起点在于教师掌握学生的大数据。与以往不同之处在于，学

教师提升数据智慧的起点在于教师掌握学生的大数据。与以往不同之处在于，学生的大数据不再仅仅是作为结果的数据。在学校数据挖掘的过程中，除了那些较容易获得的显性数据外，比如学生测验成绩、班级评比、学区排名等，还应该包括学生学习目标与动机、学习需要与教师反馈、教师教学方法、学校文化等难以量化的隐形数据。因此，这就要求学校的数据团队建立学校数据分析模型，这个模型要有清晰的框架，涵盖数据来源、数据内容、数据分析方法选择、行动计划、现状分析、改进教学策略等要素，才能使得数据具有可控制、可管理、可分析的特点，才能为教师所用，有目的有意识的提高自身的数据智慧。

The starting point for teachers to improve data wisdom is that teachers master students' big data. The difference from the past is that students' big data is no longer just data as a result. In the process of school data mining, in addition to the more easily available explicit data, such as student test scores, class evaluation, school district ranking, it should also include students' learning objectives and motivation, learning needs and teachers' feedback, teachers' teaching methods, school culture and other invisible data that are difficult to quantify. Therefore, the data team of the school is required to establish a school data analysis model. This model should have a clear framework, covering data sources, data content, data analysis method selection, action plan, current situation analysis, improved teaching strategies and other elements, so as to make the data controllable, manageable and analyzable, and be used by teachers, Purposefully and consciously improve their own data intelligence.

The starting point of improving teachers' data wisdom lies in their mastery of students' big data. Different from the past, students' big data is no longer just the result data. In the process of school data mining, in addition to those explicit data that are easy to obtain, such as students' test scores, class appraisal, school district ranking, etc., it should also include invisible data that are difficult to quantify, such as students' learning goals and motivations, learning needs and teachers' feedback, teachers' teaching methods, school culture, etc. Therefore, this requires the school data team to establish a school data analysis model. This model should have a clear framework, covering data source, data content, data analysis method selection, action plan, current situation analysis, improvement of teaching strategies and other elements, so that the data can be controlled, manageable and analyzable, and can be used by teachers to improve their own data wisdom purposefully and consciously.