{"title":"数学成绩高和成绩低告诉我们不同的故事:通过生态模型发现与学习动机有关的因素","authors":"Mehmet Hilmi Saglam , Talha Goktenturk","doi":"10.1016/j.lindif.2024.102513","DOIUrl":null,"url":null,"abstract":"<div><p>This study investigated how motivational factors contribute to math performance through the ecological model within exceptionally high and low achieving student populations. Using PISA 2018 data, a model including three layers of the ecological model were constructed to examine the ecological background of math performance for each group: exceptionally low & high achievers. Employing structural equation modeling, the results revealed that high math performance was ecologically associated with factors: attitudes towards competition, growth mindset, motivation to master tasks, self-efficacy, teacher enthusiasm, teacher feedback, teacher support, value of school, and parents' emotional support. However, low math performance was related to a wider range of factors, including the aforementioned variables, as well as enjoyment of reading and learning goals. This research emphasizes a practical viewpoint that suggests using different interventions to maximize the potential of students in various positions on the math ability spectrum since the factors differ in explaining mathematically high and low performance.</p></div><div><h3>Educational relevance and implications statement</h3><p>In this study, we investigated motivation related factors that affect students with both high and low achievements in mathematics. Our results indicate that the factors associated with math performance differ between high and low achievers. This highlights the significance of need for differentiated educational strategies to maximize the potential of students across the math ability spectrum. This differentiation between the two groups may help in developing a tailored approach, enabling educators to promote a learning environment that is both inclusive and effective.</p></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"114 ","pages":"Article 102513"},"PeriodicalIF":3.8000,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1041608024001067/pdfft?md5=cbc92cbf45de3a593eeff7f2c774e9c4&pid=1-s2.0-S1041608024001067-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Mathematically high and low performances tell us different stories: Uncovering motivation-related factors via the ecological model\",\"authors\":\"Mehmet Hilmi Saglam , Talha Goktenturk\",\"doi\":\"10.1016/j.lindif.2024.102513\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study investigated how motivational factors contribute to math performance through the ecological model within exceptionally high and low achieving student populations. Using PISA 2018 data, a model including three layers of the ecological model were constructed to examine the ecological background of math performance for each group: exceptionally low & high achievers. Employing structural equation modeling, the results revealed that high math performance was ecologically associated with factors: attitudes towards competition, growth mindset, motivation to master tasks, self-efficacy, teacher enthusiasm, teacher feedback, teacher support, value of school, and parents' emotional support. However, low math performance was related to a wider range of factors, including the aforementioned variables, as well as enjoyment of reading and learning goals. This research emphasizes a practical viewpoint that suggests using different interventions to maximize the potential of students in various positions on the math ability spectrum since the factors differ in explaining mathematically high and low performance.</p></div><div><h3>Educational relevance and implications statement</h3><p>In this study, we investigated motivation related factors that affect students with both high and low achievements in mathematics. Our results indicate that the factors associated with math performance differ between high and low achievers. This highlights the significance of need for differentiated educational strategies to maximize the potential of students across the math ability spectrum. This differentiation between the two groups may help in developing a tailored approach, enabling educators to promote a learning environment that is both inclusive and effective.</p></div>\",\"PeriodicalId\":48336,\"journal\":{\"name\":\"Learning and Individual Differences\",\"volume\":\"114 \",\"pages\":\"Article 102513\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1041608024001067/pdfft?md5=cbc92cbf45de3a593eeff7f2c774e9c4&pid=1-s2.0-S1041608024001067-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Learning and Individual Differences\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1041608024001067\",\"RegionNum\":1,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, EDUCATIONAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Learning and Individual Differences","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1041608024001067","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, EDUCATIONAL","Score":null,"Total":0}
Mathematically high and low performances tell us different stories: Uncovering motivation-related factors via the ecological model
This study investigated how motivational factors contribute to math performance through the ecological model within exceptionally high and low achieving student populations. Using PISA 2018 data, a model including three layers of the ecological model were constructed to examine the ecological background of math performance for each group: exceptionally low & high achievers. Employing structural equation modeling, the results revealed that high math performance was ecologically associated with factors: attitudes towards competition, growth mindset, motivation to master tasks, self-efficacy, teacher enthusiasm, teacher feedback, teacher support, value of school, and parents' emotional support. However, low math performance was related to a wider range of factors, including the aforementioned variables, as well as enjoyment of reading and learning goals. This research emphasizes a practical viewpoint that suggests using different interventions to maximize the potential of students in various positions on the math ability spectrum since the factors differ in explaining mathematically high and low performance.
Educational relevance and implications statement
In this study, we investigated motivation related factors that affect students with both high and low achievements in mathematics. Our results indicate that the factors associated with math performance differ between high and low achievers. This highlights the significance of need for differentiated educational strategies to maximize the potential of students across the math ability spectrum. This differentiation between the two groups may help in developing a tailored approach, enabling educators to promote a learning environment that is both inclusive and effective.
期刊介绍:
Learning and Individual Differences is a research journal devoted to publishing articles of individual differences as they relate to learning within an educational context. The Journal focuses on original empirical studies of high theoretical and methodological rigor that that make a substantial scientific contribution. Learning and Individual Differences publishes original research. Manuscripts should be no longer than 7500 words of primary text (not including tables, figures, references).