| With the development of educational reform,our country classroom evaluation system is constantly improving.Classroom evaluation is not only used to judge students’ learning results,but more importantly to develop students’ potential ability,cultivate higher-order thinking and guide students to learn effectively.As a common form of classroom evaluation,instant evaluation can play a regulating and guiding role in the teaching process,and has become an important part of classroom teaching.As an important part of normal education major,physical education major in colleges and universities is the main front to train physical education teachers in primary and secondary schools.Basketball course is one of the main courses of physical education major,through the study of this course,students can master the professional knowledge and skills of basketball,have a certain ability of basketball teaching organization,and promote the all-round development of students.And how to ensure students to learn and understand knowledge and skills more thoroughly,the role of immediate evaluation in the classroom teaching process can not be underestimated.However,in the actual basketball classroom teaching,the methods and means used by some teachers in the classroom immediate evaluation are relatively simple and random,and the evaluation is more in the shallow layer of knowledge or technical action itself,resulting in students’ knowledge and skill learning is not deep enough.In view of this,this study takes deep learning as the direction and integrates it into the instant evaluation in basketball class.By combining the two organically,deep learning provides a new theoretical perspective and impetus for the optimization of instant evaluation and points out the direction for promoting the evaluation effect.The optimization of real-time evaluation provides a feasible way to realize students’ deep learning.In this study,literature,questionnaire,experiment and other research methods were adopted to design the instant evaluation index of basketball class for physical education majors based on deep learning.The instant evaluation scheme was designed according to the content of the index and the characteristics of the class and applied to the teaching practice of basketball class,so as to verify the influence on the deep learning effect of students.In order to enrich and develop the connotation of instant evaluation in basketball classroom and improve the effect of achieving teaching objectives in teaching practice.Through the research,the following research results and conclusions are drawn:Research results:(1)Through the questionnaire survey of experts,this study designed the instant evaluation index of basketball classroom of physical education major based on deep learning,including instant evaluation objective,instant evaluation content,instant evaluation method,instant evaluation subject 4 first-level indicators,17 second-level indicators,55 third-level indicators,all dimensions of the indicators reached a high consistency.It provides a certain basis for the design of the follow-up immediate evaluation scheme.(2)After the implementation of the real-time evaluation scheme of the experimental group and the control group,the comparison results of basketball skills test are obtained: before and after the experiment,the experimental group of 60 seconds self-shooting and self-grabbing,powerful dribble,comprehensive dribble,teaching competition,teaching speaking test indicators improved,with very significant differences(P<0.001);Before and after the experiment,the control group had significant differences in the four test indexes of 60-second self-throwing and self-grabbing,powerful dribble,comprehensive dribble,teaching and speaking(P<0.001),while the teaching competition index had significant differences(P<0.05),all of which were improved.After the experiment,there were significant differences between the experimental group and the control group in 60 seconds self-throwing and self-grabbing,powerful dribble,comprehensive dribble and teaching competition test indexes(P<0.05),and there were very significant differences in teaching speaking test indexes(P<0.01).From the test results,the experimental group of students are better than the control group after the experiment.(3)Comparison results of deep learning ability: before and after the experiment,there were significant differences in cooperation ability and learning perseverance of the experimental group(P<0.01),and significant differences in communication ability,autonomous learning ability and total score of deep learning ability(P<0.001);Before and after the experiment,there were significant differences in the dimensions of cooperation ability of the control group(P<0.05),no significant differences in the dimensions of autonomous learning ability,learning perseverance and communication ability(P>0.05),and very significant differences in the overall deep learning ability(P<0.01).In general,the deep learning ability of students in the experimental group improved more significantly than that of students in the control group.After the experiment,the experimental group and the control group had significant differences in the overall level of cooperation ability and deep learning ability(P<0.01),communication ability dimension had significant differences(P<0.001),learning perseverance and independent learning ability dimension had significant differences(P<0.05).After the experiment,the deep learning ability of the experimental group was better than that of the control group in all dimensions.(4)Comparison results of cognitive level: before and after the experiment,the test scores of cognitive level and the number of cognitive level in deep learning and shallow learning in the experimental group had a great degree of change,with a very significant difference(P<0.001);Before and after the experiment,the cognitive level test scores of the control group had a very significant difference(P<0.001),and the number of people in the deep learning and shallow learning cognitive level had a small change range,no significant difference(P>0.05).After the experiment,the cognitive level test scores of the experimental group and the control group were significantly different(P<0.05).There was significant difference between the two groups in the number of people at the cognitive level of deep learning and shallow learning(P<0.05).The overall cognitive level of the experimental group was higher than that of the control group.(5)Comparison results of learning methods: Before and after the experiment,students in the experimental group had a large improvement in learning methods,with a very significant difference(P<0.001);Before and after the experiment,students in the control group had a small improvement in learning methods,and there was no significant difference(P>0.05).After the experiment,there were significant differences between the two groups of students in the test results of deep learning methods(P<0.01),superficial learning methods(P<0.001),and strategic learning methods(P<0.05).After the experiment,the deepening degree of learning methods of the experimental group was more significant than that of the control group.Research conclusion:(1)The application of the deep-learning-based instant evaluation program in the basketball classroom of physical education majors can significantly improve students’ basketball skills,promote students’ deep understanding of basketball knowledge and skills,and enable students to master basketball skills.(2)The application of the instant evaluation program based on deep learning in basketball class of physical education majors can significantly improve students’ deep learning ability,and effectively improve students’ cooperation ability,communication ability,independent learning ability and learning perseverance.(3)The application of instant evaluation scheme in basketball class of physical education major based on deep learning can significantly improve students’ cognitive level and promote students to reach the cognitive level of deep learning.(4)The application of instant evaluation scheme based on deep learning in basketball class of physical education majors can significantly deepen students’ learning methods,weaken students’ original tendency of superficial learning methods more obviously,and further strengthen the tendency of deep and strategic learning methods.(5)The instant evaluation scheme based on deep learning is more effective in improving students’ basketball skill level,deep learning ability,cognitive level and learning method than the regular instant evaluation scheme in the basketball class of physical education major,and the scheme design has certain effectiveness and feasibility. |
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