Research On Deep Learning Evaluation Of High School Physics Based On Mazzano Educational Goal Classification

Physical deep learning is one of the hot topics in physics teaching and research,deep learning is based on the teacher’s preset teaching program,with strong learning motivation to experience the process of guidance,challenge,high investment,high cognition,and obtain meaningful learning results,which has special significance for students’ lifelong learning,and is of great significance to cultivate the development of high school students’ behavioral ability through the study of physical deep learning.Through literature research,it is found that deep learning is the foundation and starting point of Mazzano theory,and Mazzano classification theory guides the development of deep learning evaluation.The deep learning evaluation system of high school physics based on the taxonomy of Mazano educational goals established in this study can guide the development of high school physics learning evaluation in the direction of scientific,systematic and integrated,and is conducive to the development of learning evaluation concepts and principles,help the implementation of core literacy,and promote the optimization of teaching evaluation.Firstly,the concept of deep learning is defined and the characteristics of deep learning are determined by literature research method,the taxonomy of Mazzano educational goals is summarized,and the intrinsic relationship between the taxonomy theory of Mazzano educational objectives and deep learning is deeply explored.Secondly,the Delphi method and questionnaire survey method were used to construct the evaluation index system,the analytic hierarchy method was used to construct the high school physics deep learning evaluation model,and the practice of high school students’ physical deep learning was investigated by compiling an evaluation questionnaire.The physical deep learning level of 346 high school students was evaluated,and the reliability and validity of the questionnaire were verified by SPSS software,and the analysis of variance showed that the content of the questionnaire was reasonable and the structure was effective,and the evaluation results of the deep learning were grasped through overall descriptive analysis and partial difference analysis.Based on the theory of physical deep learning and the taxonomy theory of Mazano educational goals,this study constructs a physical deep learning evaluation index system,and determines the proportion of each system in the physical deep learning evaluation model,among which the cognitive system accounts for the highest proportion.Through practice,it is found that the overall deep learning level performance of students meets the normal distribution,the level of metacognitive system is low,the deep learning performance of high school students in different elective subjects and different genders is inconsistent,and the deep learning characteristics of learning motivation,metacognitive monitoring,and memory mode still need to be strengthened.