Research On The Measurement And Evaluation Of Data Analysis Literacy Of Junior High School Students

Data analysis literacy has become one of the six core mathematical literacy in middle school,its importance is self-evident.As the big data industry development planning ",big data has been promoted to national strategic level,have data analysis quality of talents is the era of big data needed,and in the international middle school students in our country related data analysis on the quality of test performance is not good,so it is very urgent to promote students' literacy in data analysis in our country.Therefore,studies the measurement and evaluation of data analysis in junior high school students literacy has important practical significance,the research on the measurement and evaluation of data analysis in junior high school students literacy clear data analysis can not only guide line teachers training,master the depth and breadth of data analysis literacy teaching,make the evaluation more accurately reflect the requirements of personnel training,and can provide reference for the revision of the compulsory education curriculum.This study on how to measure the core problem of data analysis in junior high school students literacy,junior middle school students based on literature research and data analysis of assessment framework,according to the data analysis of literacy assessment framework establishment data analysis literacy assessment tools,use of assessment tools for four schools in chongqing ninth graders were tested,using the method of combining quantitative analysis and qualitative analysis on the overall situation of ninth graders data analysis,the manifestation of various dimensions and various test projects are analyzed.The conclusions of this study are as follows :(1)the framework of junior high school students' data analysis literacy assessment consists of three dimensions: content,cognitive level and problem situation.Among them,the content dimension includes: data collection,data collation and description,data application;Cognitive dimensions include: knowledge understanding,knowledge transfer,knowledge innovation;Situation dimension includes: individual situation,educational situation,social situation.(2)in terms of content dimension,junior middle school students perform well in data collection,data collation and description,and perform relatively poorly in data application;In the context dimension,students have a certain understanding of personal,educational and social situations.Students perform well in the personal and educational situations,but poorly in the social situation dimension,indicating that the familiarity of the situation is conducive to students' problem solving.On the cognitive dimension,60% of the students can reach the level of knowledge understanding,40% can reach the level of knowledge transfer,and less than 30% can reach the level of knowledge innovation.(3)gender of junior middle school students has no significant difference in the performance of data analysis literacy,that is to say,gender is not the main factor affecting junior middle school students' data analysis literacy.However,there is a significant difference in the overall performance of data analysis literacy between junior middle school students in private schools and junior middle school students in public schools.As a whole,the data analysis literacy of students in private schools is higher than that of students in public schools,especially in the ability to use data,which enables them to extract data more effectively for analysis and decision-making.(4)the current situation of junior middle school students' data analysis literacy is not optimistic,especially the students' performance on the level of knowledge innovation is not ideal,the analysis of the main reasons are: students' thinking set is serious;Lack of awareness to analyze data from multiple perspectives and methods;Students lack the habit of reasoning based on data.In view of the above research conclusions,this study proposes to deepen the teaching of statistical understanding and pay attention to the connection between concept and reality.In the teaching process,let students experience the whole process of data analysis,pay attention to guide students to analyze data from multiple angles,as much as possible to obtain useful information;Reduce some routine questions appropriately,increase the flexibility and openness of the topic of the exercise intensity and other Suggestions.