{"title":"数据素养影响因素的实证研究","authors":"R. nath, J. Kirby","doi":"10.33847/2686-8296.4.1_1","DOIUrl":null,"url":null,"abstract":"To fully leverage the abundance of data and how data enhances decision-making, people must be data literate. Data literacy (DL) encompasses a set of interrelated skills in data management, data analysis, and the ability to interpret and communicate the results. Measuring an individual's DL level is an important first step toward designing and developing educational programs to improve one's DL skills. This paper considers a DL measurement scale referred to as the Global Data Literacy Benchmark survey and then explores the underlying constructs of this instrument. Data gathered from 311 university students across five universities in the United States is analyzed to identify and interpret the underlying factors of this DL scale. Also, the differences in DL scores among various subgroups of the students are investigated. The results show the existence of three DL factors. Also, the DL scores vary considerably among students depending upon the study areas and the comfort levels with data and analytics.","PeriodicalId":235278,"journal":{"name":"Journal of Digital Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Empirical Examination of the Factors of Data Literacy\",\"authors\":\"R. nath, J. Kirby\",\"doi\":\"10.33847/2686-8296.4.1_1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To fully leverage the abundance of data and how data enhances decision-making, people must be data literate. Data literacy (DL) encompasses a set of interrelated skills in data management, data analysis, and the ability to interpret and communicate the results. Measuring an individual's DL level is an important first step toward designing and developing educational programs to improve one's DL skills. This paper considers a DL measurement scale referred to as the Global Data Literacy Benchmark survey and then explores the underlying constructs of this instrument. Data gathered from 311 university students across five universities in the United States is analyzed to identify and interpret the underlying factors of this DL scale. Also, the differences in DL scores among various subgroups of the students are investigated. The results show the existence of three DL factors. Also, the DL scores vary considerably among students depending upon the study areas and the comfort levels with data and analytics.\",\"PeriodicalId\":235278,\"journal\":{\"name\":\"Journal of Digital Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Digital Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33847/2686-8296.4.1_1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Digital Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33847/2686-8296.4.1_1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Empirical Examination of the Factors of Data Literacy
To fully leverage the abundance of data and how data enhances decision-making, people must be data literate. Data literacy (DL) encompasses a set of interrelated skills in data management, data analysis, and the ability to interpret and communicate the results. Measuring an individual's DL level is an important first step toward designing and developing educational programs to improve one's DL skills. This paper considers a DL measurement scale referred to as the Global Data Literacy Benchmark survey and then explores the underlying constructs of this instrument. Data gathered from 311 university students across five universities in the United States is analyzed to identify and interpret the underlying factors of this DL scale. Also, the differences in DL scores among various subgroups of the students are investigated. The results show the existence of three DL factors. Also, the DL scores vary considerably among students depending upon the study areas and the comfort levels with data and analytics.