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Research On The Teaching Practice Of High School Physics Review Course From The Perspective Of Deep Learning

Posted on:2022-12-03Degree:MasterType:Thesis
Country:ChinaCandidate:S Y GaoFull Text:PDF
GTID:2517306761463114Subject:(Physics) Curriculum and Pedagogy
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With the continuous renewal of educational ideas,in-depth learning has been raised in recent years,which has become a hot spot in the educational circles at home and abroad.Different from shallow learning,deep learning pays more attention to students’ understanding of knowledge,critical consciousness and the ability to transfer knowledge flexibly,which is very consistent with the requirements of the new curriculum reform and has become the inevitable trend of domestic education development.Under the background of the new college entrance examination,physics in senior high school has become more important.As one of the disciplines with relatively strong logic and application,teachers are required to not only pursue the superficial understanding of symbolic knowledge,but also pay attention to the deep grasp and critical understanding of the core knowledge of physics,Strive to improve the discipline logic system and build a good knowledge framework in the process of reflection.Therefore,we should integrate the concept of in-depth learning into the teaching of physics,so as to further implement the development of core literacy in the physics curriculum standard of senior high school.This study is mainly divided into the following parts:Literature research on the current situation of deep learning and physics review teaching.Firstly,sort out the research related to deep learning,summarize the concept of deep learning,research history,relevant theories and discrimination with shallow learning,clarify the close relationship between deep learning and physics review teaching,and establish the content,methods and thinking of research problems on this basis.By carefully studying the NSSE China deep learning subscale and combined with the deep learning ability framework,this paper designs the evaluation index framework of the deep learning ability of physics review course,and then develops the pre-test questionnaire.Through the questionnaire survey method,we investigate and understand the current situation of deep learning of physics review course in senior high school,and analyze the data according to the survey results,Study the causes of the problems.Combined with the above analysis of the problems and causes in the in-depth learning of senior high school physics review course,according to the continuous teaching process extending in time order in the pre class preparation stage,the teaching process,the knowledge acquisition and in-depth processing stage in the classroom,the post class evaluation stage after the completion of teaching activities,this paper puts forward the teaching strategy based on in-depth learning,Prepare and pave the way for the practice of the next link.Select the appropriate topic in the physics textbook as the subject of case analysis,and then conduct practical exploration in combination with the problems existing in the in-depth learning of the review course and the corresponding practical strategies,so as to put the teaching strategies into the front-line teaching.According to the solo classification theory,the test questions were designed,and the test volumes were distributed in the experimental class and the control class.After the results of the questionnaires,the data statistics and effects were elaborated.The promotion effect of the analytic hierarchy process on students’ deep learning ability was discovered.The students’ deep understanding of knowledge was promoted and they could participate in the classroom learning consciously.And the improvement of the flexible transfer ability of knowledge,etc.,which comes to the conclusion that the review class teaching strategy based on in-depth learning in this study has a certain feasibility.
Keywords/Search Tags:Deep learning, Teaching strategy of review class, High school physics
PDF Full Text Request
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