Research On Teaching Design Of High School Mathematics Unit Based On Deep Learning

The reform of high school education is the focus of China’s education development.The rise of deep learning theory in the field of education in our country makes the reform of high school education and teaching have a theoretical basis and practical grasp.At present,in our country’s high school mathematics unit teaching,there is a separation between subject knowledge and students’ life,ignoring students’ individuality,uniqueness,initiative and initiative,resulting in the unit teaching design falling into the dilemma of fragmentation,repetition and full house.Deep learning helps to break through the current dilemma,improve the quality of high school mathematics unit teaching design,and promote students’ mathematics knowledge Knowledge,mathematical thinking,mathematical ability.This study takes the teaching content of high school mathematics "sequence" as a case to explore the teaching design of high school mathematics unit from the perspective of deep learning.Based on deep understanding,deep design,deep experience,deep thinking,deep interaction and deep reflection,this study constructs a theoretical framework of high school mathematics unit teaching design based on deep learning,emphasizing the importance of mathematics discipline system,overall planning of knowledge,students’ active participation,students’ high-level mathematical thinking and core literacy cultivation,equal dialogue between teachers and students,and teaching process Dynamic adjustment in the system.On the basis of theoretical analysis,according to the teaching design process,from the goal analysis,element analysis,content analysis,determining the design theme,establishing the evaluation system and so on,this paper constructs the high school mathematics unit teaching design mode based on deep learning,emphasizing the value orientation of students’ discovery,students’ subjectivity and students’ experience,aiming at cultivating students’ thinking ability and core elements in mathematics Raise.The case study and implementation effect evaluation of "sequence" unit teaching design based on deep learning are carried out.In the aspect of case study,this paper systematically analyzes the teaching objectives,elements(subject status,content,learning situation,key and difficult points),contents and students’ core literacy of the "sequence" unit,and forms a systematic teaching plan and carries out teaching practice by taking the top n sums of arithmetic sequence as an example.In the aspect of implementation effect evaluation,teachers think that deep learning provides a new idea for the teaching design of mathematics unit,so that they can grasp the teaching as a whole,constantly explore the intention of textbook design,and clarify the high school mathematics system,while students think that the current teaching design no longer pays too much attention to mechanical repetition formula,so that they have the ability to sort out mathematics knowledge as a whole and do not have the ability to understand The consciousness of training one’s way of thinking.Combined with the above research results,based on the theoretical construction and practical exploration of unit teaching design,this paper designs a deep learning oriented high school mathematics unit teaching design strategy from the school,teachers,curriculum teaching,students and other aspects.At the school level,we should actively establish a teaching design team to strengthen the cultivation of teachers’ teaching design ability;at the teacher level,we should enrich the theoretical knowledge of high school mathematics and improve the professional ability of mathematics teaching;break the class hour doctrine and integrate the teaching objectives and contents;at the curriculum teaching level,we should take deep learning as the core to optimize the teaching design of high school mathematics units;establish an evaluation system to improve the teaching quality At the student level,it should be rooted in students’ daily life and stimulate students’ initiative in deep learning.