Research On The Status Quo And Training Strategies Of Students' Data Analysis Ability In The Second Semester

In the information age,people collect and collate useful data from complex information,and make judgments and decisions based on the data.They need to have certain data analysis ability.Data analysis,as the core of statistics,plays an important role in mathematics learning in compulsory education stage.Through reviewing the current research situation of data analysis ability,this study compiles a paper-and-pencil test paper based on M3ST framework of Monet's statistical thinking to investigate the current situation of students'?data analysis ability in the second period.By means of student questionnaires,teacher interviews,classroom observation and case analysis,this study analyses the factors affecting students' data analysis ability in the second period,and seeks to cultivate students' data analysis ability.Based on the existing literature and the relevant content of the compulsory education mathematics curriculum standard promulgated in 2011,this research divides the data analysis ability into five dimensions:the ability to collect data,the ability to organize data,the ability to describe data,the ability to infer data,and the ability to experience randomness.At the same time,according to M3ST framework,the data analysis capability level is divided into four levels:specific level,transition level,quantitative level and analysis level.According to the data collected from the survey,it is concluded that the data analysis ability of the students in the second section of C primary school in Gulou District of Nanjing has significant grade differences.Although the data analysis ability of the students in the second section shows an upward trend with the increase of grade,the overall level is low and is in a transitional level.Subsequently,the study conducted a questionnaire survey on students,interviewed teachers in three areas,observed the classroom,analyzed cases,and excavated the reasons for the low level of data analysis ability of students in the second stage.We can find that there are many problems in the current primary school mathematics classroom,such as unclear conceptual awareness,unclear positioning of teaching efforts,lack of application of knowledge methods and so on.Through the specific analysis of each dimension level of students' data analysis ability in the second period,combined with the problems found in questionnaires,interviews and classroom observation,this paper puts forward corresponding training strategies for the five dimensions of data analysis ability.Firstly,the training of data collection ability should pay attention to the value of statistics,experience the process of data collection,and infiltrate the idea of sampling.Secondly,the cultivation of the ability to collate data should start from three aspects:stimulating interest in the situation to learning classification;operating to mastering methods;paying attention to differences,and clever analogy.Thirdly,the training of describing data ability includes the teaching of statistical graphs and the teaching of averages.Among them,the teaching of statistical graphs should produce learning needs in solving problems,highlight essential characteristics in comparative analysis,establish extensive connections in looking at cartographic drawings,and make use of geometric intuition to make it easy to teach averages,use extreme value thought to experience features and use specific problems to explain meanings.Fourthly,the training of inferential data ability suggests that students interact with each other,collide with thinking sparks,review process,cultivate reflective habits,project learning,and build application platforms.Fifthly,the training of experiential randomness can estimate probability through "unequal possible events",infer game fairness through experiments,and experience randomness through small probability events.