Research On The Development And Application Of Mathematics Deep Learning Assessment Tools For Senior High School Students

As an effective way to cultivate students' mathematics core accomplishment,deep learning of mathematics promotes the development of students' advanced thinking ability.Facing situation of lack of deep learning mathematics assessment tools,this study through literature analysis,interview,questionnaire compiled and statistical analysis methods such as questionnaire explores the deep learning mathematics evaluation model,compiled the depth of the high school mathematics learning questionnaire,and analyze the formal questionnaire survey result,according to current situation of research and puts forward some rationalization proposal,helps to promote deep learning mathematics.The research mainly focuses on the following three aspects:Firstly,the questionnaire on mathematics deep learning of high school students was compiled.Based on the analysis of the evaluation model of mathematical deep learning and the reference of the existing deep learning scale,the dimensions of the mathematical deep learning scale were constructed by combining with the expert interviews,and the items in the scale were compiled.The following results are further obtained:(1)the questionnaire for mathematics deep learning for senior high school students is divided into two subscales of deep learning and superficial learning.The total scale is divided into four subscales: deep motive,deep strategy,surface motive,surface strategy,including mathematical learning interest,mathematical learning commitment,knowledge understanding,knowledge transfer,learning anxiety,aim for qualification,minimizing scope of study and memorisation eight subcomponents.(2)the reliability analysis results show that the depth of the mathematics learning subscales cronbach's alpha coefficient is 0.910,superficial learning mathematics subscales cronbach's alpha coefficient is 0.875,sub scale and scale between different dimensions of alpha coefficient between 0.681 ? 0.860,cronbach subscales and the internal consistency coefficients between subscales dimensions conform to the requirements of the statistical measurement,to ensure the reliability of scale.(3)the validity analysis results showed that the data obtained from the content validity and the structure validity were within the standard value range,ensuring the validity of the scale.Then,descriptive analysis and difference analysis are carried out for the valid data in formal investigation.The following results were obtained by analyzing the three statistical variables of student gender,grade and arts and science in the background information:(1)descriptive analysis shows that the degree of data concentration is good and the volatility of the two is consistent.On the whole,the deep learning of mathematics is better than the superficial learning of mathematics.(2)gender difference analysis shows that boys are stronger than girls in deep learning of mathematics;In grade three,the group's deep learning of mathematics is the strongest,the second in grade one,and the second in grade two is weak.In the aspect of arts and science,the deep learning of mathematics of science students is stronger than that of arts students.Finally,some teaching Suggestions are put forward: in mathematics classroom teaching,in order to improve students' in-depth learning of mathematics as a whole,it is necessary to strengthen girls' motivation of deep learning and strategies of deep learning.Considering the ways in which students learn mathematics and teachers teach mathematics without division of arts and sciences,teachers and students work together to improve students' in-depth learning of mathematics.