| In the new round of curriculum reform,deep learning has become a hot topic in education and teaching.Deep learning refers to on the basis of the understanding of learning,learners will be able to critically learn new knowledge and ideas,new knowledge and ideas into existing cognitive structure,can contact between many thoughts and migration of existing knowledge in the new situation,as a kind of learning way of decision-making and problem solving.Therefore,deep learning is an effective way to fully implement the new curriculum reform and optimize teaching.Based on the research on the current situation and strategies of high school mathematics teaching under the background of deep learning,this paper aims to overcome the obstacles of shallow learning for students,promote the all-round development of students and the improvement of multiple abilities,and provide teaching strategies for teachers to carry out deep teaching.This article through the literature review,the application of questionnaire survey and interview method and the corresponding case study,in order to explore the effective way of high school mathematics teaching.First,clear the definition,content and depth of study through literature research value,on the basis of questionnaire design,questionnaire design points of the heart to,learning strategies and learning results of three dimensions,and in a provincial demonstration high school in dalian freely choose 486 students questionnaires,understand the present situation of the depth of the high school mathematics learning,After data collection,SPSS and EXCEL were used for statistical analysis,and charts were drawn to comprehensively study the current situation of deep learning in senior high school mathematics.At the same time,five students were randomly selected from the school to design interview questions to get an in-depth understanding of the current situation and existing problems of deep learning among high school students.The main problems are as follows :(1)high school students’ learning motivation and learning investment are insufficient;(2)High school students lack deep integration,transfer and reflection of knowledge;(3)High school students lack critical thinking and cooperation and communication between teachers,students and students.Based on literature and investigation results,in Chapter 6,this paper divides deep learning into four stages: teaching presupposition,situational mobilization,in-depth inquiry,evaluation and reflection,and puts forward corresponding teaching strategies in each stage.In the teaching preset stage,fully analyze the learning situation,set reasonable unit teaching objectives and teaching difficulties,simulate the classroom;In the stage of situational mobilization,a good learning atmosphere is constructed and a deep teaching situation is created.In the in-depth exploration stage,information-based teaching means are used to build a good cooperation and communication environment,provide an expression platform for teachers and students to blend,supplemented by precise and precise teacher instruction,and enhance the in-depth exploration of problems.In the evaluation and reflection stage,improve the depth evaluation system and guide students to learn self-reflection in the face of mathematical problems.In this paper,in the case of each stage with corresponding to the sufficient conditions,necessary conditions,the equality and inequality,the definition of the ellipse,the geometric series summation,for example,according to this paper,the depth of the teaching strategies for the design of corresponding,and in the seventh chapter is the sine theorem of teaching design,the depth to interpret how to carry out the depth of the high school mathematics learning in teaching.In short,under the requirements of the new college entrance examination and the new curriculum reform,high school teachers should pay more attention to the deep learning of students,constantly adjust teaching strategies according to the requirements of curriculum standards and students’ conditions,and promote the implementation of deep learning. |
