| The era of big data has come,and data driven intelligent decision making has become the trend of the big data age.Precision and individuation become the key words.The research of precision education in the context of big data is inseparable from the indepth analysis and mining of data,so the construction of mathematical models and the application of necessary analysis techniques are indispensable.This thesis mainly studies the mathematical model of precision education in the era of big data,and strives to discuss mathematical models of precision education from the perspective of statistical theory and methods in the context of big data,focusing on the evaluation and optimization of the precision education regimes,especially the optimization of the multi stage dynamic precision education regimes,hopes to fully analyze the information of big data,provide effective support for education decision making and precision education services for students.This thesis first summarizes the precision education in the era of big data,and then proposes mathematical models for precise education based on conditional expectations.It focuses on the evaluation model of precision education regimes,variable selection of evaluation models,and the development of single stage and multi stage precision teaching regimes.Finally,the specific application of the precision education mathematics model in an actual early warning case is constructed.This thesis translates the development of precision education regimes in precision education into an optimization problem and elaborates the basic ideas for solving it.In the section of precision education regimes evaluation,based on the idea of conditional expectation and regression model,the evaluation model of precision education regimes is constructed,and the education effect produced by a certain education regimes for students with certain characteristics and behavioral monetization is finely characterized.In the section of the evaluation model optimization,the variable selection method was used to study the principle and implementation algorithm of variable selection based on the evaluation model of precision education regimes,and to analyze the key factors that have an impact on the education effect.In the formulation of precision education regimes development,the formulation method for precision education regimes is studied,especially the method for formulating a multi-stage dynamic teaching plan.The Qlearning method is used to solve this multi-stage dynamic decision problem to find the optimal decision function according to the optimum.According to the decision function,precision education regimes to a student with any characteristic and behavior can be given.The work of this article is mainly focused on two aspects.On the one hand,based on the idea of conditional expectation and regression model,the evaluation model of precision teaching scheme is constructed,which provides a theoretical method for fully analyzing the large data information of education.The results obtained in the actual case also show the precision and meticulous character of the model to the individual factor analysis.On the other hand,considering the time-series and post-effect characteristics of education,the issue of multi-stage dynamic and precision education is studied.To grasp the dynamic characteristics of educational data,the method of multi stage dynamic decision making is used to study the formulation of precision education regimes,which can provide more powerful support for precision education decision and personalized learning. |
