{"title":"为什么以及如何在教育神经科学研究中收集具有代表性的研究样本","authors":"Analia Marzoratti , Tanya M. Evans","doi":"10.1016/j.tine.2024.100231","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Educational neuroscience research, which investigates the neurobiological mechanisms of learning, has historically incorporated samples drawn mostly from white, middle-class, and/or suburban populations. However, sampling in research without attending to representation can lead to biased interpretations and results that are less generalizable to an intended target population. Prior research revealing differences in neurocognitive outcomes both within- and across-groups further suggests that such practices may obscure significant effects with practical implications.</p></div><div><h3>Barriers</h3><p>Negative attitudes among historically marginalized communities, stemming from historical mistreatment, biased research outcomes, and implicit or explicit attitudes among research teams, can hinder diverse participation. Qualities of the research process including language requirements, study locations, and time demands create additional barriers.</p></div><div><h3>Solutions</h3><p>Flexible data collection approaches, community engaugement, and transparent reporting could build trust and enhance sampling diversity. Longer-term solutions include prioritizing research questions relevant to marginalized communities, increasing workforce diversity, and detailed reporting of sample demographics. Such concerted efforts are essential for robust educational neuroscience research to maximize positive impacts broadly across learners.</p></div>","PeriodicalId":46228,"journal":{"name":"Trends in Neuroscience and Education","volume":"35 ","pages":"Article 100231"},"PeriodicalIF":3.4000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Why and how to collect representative study samples in educational neuroscience research\",\"authors\":\"Analia Marzoratti , Tanya M. Evans\",\"doi\":\"10.1016/j.tine.2024.100231\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Educational neuroscience research, which investigates the neurobiological mechanisms of learning, has historically incorporated samples drawn mostly from white, middle-class, and/or suburban populations. However, sampling in research without attending to representation can lead to biased interpretations and results that are less generalizable to an intended target population. Prior research revealing differences in neurocognitive outcomes both within- and across-groups further suggests that such practices may obscure significant effects with practical implications.</p></div><div><h3>Barriers</h3><p>Negative attitudes among historically marginalized communities, stemming from historical mistreatment, biased research outcomes, and implicit or explicit attitudes among research teams, can hinder diverse participation. Qualities of the research process including language requirements, study locations, and time demands create additional barriers.</p></div><div><h3>Solutions</h3><p>Flexible data collection approaches, community engaugement, and transparent reporting could build trust and enhance sampling diversity. Longer-term solutions include prioritizing research questions relevant to marginalized communities, increasing workforce diversity, and detailed reporting of sample demographics. Such concerted efforts are essential for robust educational neuroscience research to maximize positive impacts broadly across learners.</p></div>\",\"PeriodicalId\":46228,\"journal\":{\"name\":\"Trends in Neuroscience and Education\",\"volume\":\"35 \",\"pages\":\"Article 100231\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trends in Neuroscience and Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2211949324000127\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Neuroscience and Education","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211949324000127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Why and how to collect representative study samples in educational neuroscience research
Background
Educational neuroscience research, which investigates the neurobiological mechanisms of learning, has historically incorporated samples drawn mostly from white, middle-class, and/or suburban populations. However, sampling in research without attending to representation can lead to biased interpretations and results that are less generalizable to an intended target population. Prior research revealing differences in neurocognitive outcomes both within- and across-groups further suggests that such practices may obscure significant effects with practical implications.
Barriers
Negative attitudes among historically marginalized communities, stemming from historical mistreatment, biased research outcomes, and implicit or explicit attitudes among research teams, can hinder diverse participation. Qualities of the research process including language requirements, study locations, and time demands create additional barriers.
Solutions
Flexible data collection approaches, community engaugement, and transparent reporting could build trust and enhance sampling diversity. Longer-term solutions include prioritizing research questions relevant to marginalized communities, increasing workforce diversity, and detailed reporting of sample demographics. Such concerted efforts are essential for robust educational neuroscience research to maximize positive impacts broadly across learners.