{"title":"哪些变量能更好地预测一年级小学生的音位意识?","authors":"Kerem Coskun","doi":"10.1177/00332941241291037","DOIUrl":null,"url":null,"abstract":"<p><p>The purpose of the research was to discover which variables better predict phonemic awareness. Socioeconomic status (SES), quality of parent-child interaction (PCI), screen time (DST), visual-spatial ability (VSA), and mathematical reasoning (MR) were included as independent variables in the model, while phonemic awareness (PA) was the dependent (outcome) variable. The research was designed as correlational research. A total of 556 first grade primary school students were recruited into the research sample upon approval by their parents. In the analytic procedures, supervised machine learning was adopted and data were analyzed through classification and regression trees (CART) by using rprart, rpart.plot, tidyverse, dplyr, ggplot2, and corrplot packages in R. Results of data analysis indicate that MR, PCI, and VSA can predict PA, while SES and DST are not predictors. Findings of the research were discussed along with intelligence theories and practical implications were noted for teachers and researchers.</p>","PeriodicalId":21149,"journal":{"name":"Psychological Reports","volume":" ","pages":"332941241291037"},"PeriodicalIF":1.7000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Which Variables Better Predict Phonemic Awareness of First Grade Primary School Students?\",\"authors\":\"Kerem Coskun\",\"doi\":\"10.1177/00332941241291037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The purpose of the research was to discover which variables better predict phonemic awareness. Socioeconomic status (SES), quality of parent-child interaction (PCI), screen time (DST), visual-spatial ability (VSA), and mathematical reasoning (MR) were included as independent variables in the model, while phonemic awareness (PA) was the dependent (outcome) variable. The research was designed as correlational research. A total of 556 first grade primary school students were recruited into the research sample upon approval by their parents. In the analytic procedures, supervised machine learning was adopted and data were analyzed through classification and regression trees (CART) by using rprart, rpart.plot, tidyverse, dplyr, ggplot2, and corrplot packages in R. Results of data analysis indicate that MR, PCI, and VSA can predict PA, while SES and DST are not predictors. Findings of the research were discussed along with intelligence theories and practical implications were noted for teachers and researchers.</p>\",\"PeriodicalId\":21149,\"journal\":{\"name\":\"Psychological Reports\",\"volume\":\" \",\"pages\":\"332941241291037\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Psychological Reports\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1177/00332941241291037\",\"RegionNum\":4,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PSYCHOLOGY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychological Reports","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/00332941241291037","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
摘要
研究的目的是发现哪些变量能更好地预测语音意识。社会经济地位(SES)、亲子互动质量(PCI)、屏幕时间(DST)、视觉空间能力(VSA)和数学推理能力(MR)作为自变量被纳入模型,而语音意识(PA)则是因变量(结果)。研究设计为相关研究。经家长同意后,共招募了 556 名一年级小学生作为研究样本。数据分析结果表明,MR、PCI 和 VSA 可以预测 PA,而 SES 和 DST 不能预测 PA。研究结果与智力理论一起进行了讨论,并指出了对教师和研究人员的实际意义。
Which Variables Better Predict Phonemic Awareness of First Grade Primary School Students?
The purpose of the research was to discover which variables better predict phonemic awareness. Socioeconomic status (SES), quality of parent-child interaction (PCI), screen time (DST), visual-spatial ability (VSA), and mathematical reasoning (MR) were included as independent variables in the model, while phonemic awareness (PA) was the dependent (outcome) variable. The research was designed as correlational research. A total of 556 first grade primary school students were recruited into the research sample upon approval by their parents. In the analytic procedures, supervised machine learning was adopted and data were analyzed through classification and regression trees (CART) by using rprart, rpart.plot, tidyverse, dplyr, ggplot2, and corrplot packages in R. Results of data analysis indicate that MR, PCI, and VSA can predict PA, while SES and DST are not predictors. Findings of the research were discussed along with intelligence theories and practical implications were noted for teachers and researchers.