{"title":"在教育研究中使用强定量方法论的主要挑战和指导","authors":"R. Henson, Genéa K. Stewart, Lee A. Bedford","doi":"10.21423/JUME-V13I2A382","DOIUrl":null,"url":null,"abstract":"The current article reviews several common areas of focus in quantitative methods with the hope of providing Journal of Urban Mathematics Education (JUME) readers and researchers with some guidance on conducting and reporting quantitative analyses. After providing some background for the discussion, the methodological nature of recent JUME articles is reviewed, followed by commentary on key challenges and recommendations for strong practice in quantitative methodology. The review addresses causal inferences, measurement issues, handling missing data, testing for assumptions, dealing with nested data, and providing evidence for outcomes. Enhanced quantitative training and resources for doctoral students, authors, reviewers, and editors is recommended.","PeriodicalId":36435,"journal":{"name":"Journal of Urban Mathematics Education","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Key Challenges and Some Guidance on Using Strong Quantitative Methodology in Education Research\",\"authors\":\"R. Henson, Genéa K. Stewart, Lee A. Bedford\",\"doi\":\"10.21423/JUME-V13I2A382\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The current article reviews several common areas of focus in quantitative methods with the hope of providing Journal of Urban Mathematics Education (JUME) readers and researchers with some guidance on conducting and reporting quantitative analyses. After providing some background for the discussion, the methodological nature of recent JUME articles is reviewed, followed by commentary on key challenges and recommendations for strong practice in quantitative methodology. The review addresses causal inferences, measurement issues, handling missing data, testing for assumptions, dealing with nested data, and providing evidence for outcomes. Enhanced quantitative training and resources for doctoral students, authors, reviewers, and editors is recommended.\",\"PeriodicalId\":36435,\"journal\":{\"name\":\"Journal of Urban Mathematics Education\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Urban Mathematics Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21423/JUME-V13I2A382\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Urban Mathematics Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21423/JUME-V13I2A382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
Key Challenges and Some Guidance on Using Strong Quantitative Methodology in Education Research
The current article reviews several common areas of focus in quantitative methods with the hope of providing Journal of Urban Mathematics Education (JUME) readers and researchers with some guidance on conducting and reporting quantitative analyses. After providing some background for the discussion, the methodological nature of recent JUME articles is reviewed, followed by commentary on key challenges and recommendations for strong practice in quantitative methodology. The review addresses causal inferences, measurement issues, handling missing data, testing for assumptions, dealing with nested data, and providing evidence for outcomes. Enhanced quantitative training and resources for doctoral students, authors, reviewers, and editors is recommended.