Measurement And Evaluation Of Data Analysis Literacy Of High School Students

With the advent of the era of big data,statistical and probabilistic core literacy has become one of the essential thinking qualities and key abilities of future citizens.The core literacy of mathematics has become the focus of current attention in the field of mathematics education research.The Ordinary High School Curriculum Standards(2017 Edition)puts forward six core literacy of mathematics disciplines,which fully embodies the important position of the core literacy of mathematics in high school mathematics education.Data analysis literacy is one of the most important characteristics of mathematics in the context of the era of big data.At present,the core literacy assessment system suitable for the current situation of mathematics curriculum reform in China needs to be established and improved.Based on the quality description and level division theory,PISA evaluation theory and SOLO classification theory of the core curriculum literacy of mathematics curriculum standards,this paper conducts an empirical study on the level and effective achievement of high school students' data analysis literacy.The ideas and methods of this study: First,compare and analyze the research status of mathematical core literacy and data analysis literacy.According to curriculum standards and PISA assessment theory,content,process,situation and emotional attitude values are used as four dimensions of data analysis literacy measurement and evaluation.Based on the SOLO classification theory,this paper establishes the content dimension level division standard,and establishes a high school student data analysis literacy assessment system.The data analysis literacy test papers and questionnaires of high school students are compiled.The study selects 149 students from three classes at different levels in a third-grade high school in GX District,GZ City,JX Province as a sample for evaluation.The data is analyzed by Excel2016 and SPSS21.0 for overall analysis,correlation analysis,difference analysis and analysis of each measurement dimension.Evaluation and research results indicate:(1)The overall scores of high school students' data analysis literacy assessments are on average,and the test scores based on content,process,and context are lower than the pass level.(2)High school students have a significant correlation between the performance of data analysis literacy content,context,process dimensions and the performance of emotional attitude values.There is no significant difference in data analysis literacy of students of different genders.The data analysis literacy of students with different class types and daily math scores is significantly different.(3)Content dimension,the performance of the four elements of the basic methods and concepts,statistical charts,sample estimation population,and paired data of most students reach the multi-point structure level.The mastery of the sampling unit stays at the level of the single point structure.About one-third of the students' performance in the one-dimensional linear regression model unit reach the multi-point structure level,and most students achieve multi-point structure level in the 2×2 contingency.(4)Students perform well in the formation of mathematical processes,perform relatively poorly in applied mathematics and explaining mathematical processes;perform well in social and scientific situations,and perform relatively poorly in personal and professional situations.(5)Most students have good data analysis literacy,attitudes and values,and are very positive about the value of data analysis in real life,science,technology,medical and engineering.Based on the above evaluation and research results,we recommend:(1)The preparation of teaching materials is to cultivate students' data analysis literacy as the core goal of textbook writing,and to increase the number of big data analysis cases to attract students' interest.(2)The target of the statistical module examination is the level of the student's data analysis literacy,and the test proposition produces a certain amount of open questions.(3)The teacher himself strengthens the study of the data analysis literacy theory in the curriculum standards,and strengthens the mastery of statistical professional knowledge such as big data analysis.(4)In the process of teacher teaching,the cultivation of high school students' data analysis literacy is the core goal of statistical content teaching.Teachers strengthen students' understanding of concepts and methods related to data analysis.Based on the actual situation as the background,teachers teach the related content about the data analysis.Through statistical activities,students can experience the whole process of data analysis,and combine information technology to improve students' data analysis literacy.