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Applies three-level logistic regression to identify predictors of regular remote instruction, including pre-pandemic broadband access, school demographics, and district policy responses derived from public COVID-19 plans. Finds lower remote instruction likelihood for teachers in schools serving more economically disadvantaged students and in rural districts, with reduced rural opportunities linked in part to high-speed broadband access and partially mitigated by device-distribution policies.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/broadband-access-district-policy-and-student-opportunities-for-remote-learning-during-covid-19-school-closures/590089/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/broadband-access-district-policy-and-student-opportunities-for-remote-learning-during-covid-19-school-closures/590089.png","ImageObject",300,407,{"name":92,"@type":93},"Adam","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-02","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does the study examine about remote learning during COVID-19 closures?","Question",{"text":112,"@type":113},"It examines how students’ opportunities to learn remotely varied during initial school closures and whether this variation reflects differences in remote instruction delivery.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which factors are tested as predictors of regular remote instruction?",{"text":117,"@type":113},"The study tests pre-pandemic broadband access, school demographic composition, and district policy responses created from districts’ public COVID-19 plans.",{"name":119,"@type":110,"acceptedAnswer":120},"How do findings relate to rural and economically disadvantaged communities?",{"text":121,"@type":113},"Teachers in schools serving more economically disadvantaged students and in rural districts are less likely to report regular remote instruction, particularly for providing digital resources and holding virtual classes or tutoring.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},590089,1792161932,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},1374404737137,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","AERA Open  \nJanuary-December 2021, Vol. 7, No. 1, pp. 1–22 DOI: 10. 1177/23328584211064298  \nArticle reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)© The Author(s) 2021. [https://journals.sagepub.com/home/ero](https://journals.sagepub.com/home/ero)  \nBroadband Access, District Policy, and Student Opportunities for Remote Learning During COVID-19 School Closures  \nSusan Kemper Patrick  \nAmerican University  \nJason A. Grissom  \nS. Colby Woods  \nVanderbilt University  \nUrLeaka W. Newsome  \nTennessee State University  \nWe conceptualize students’ opportunities to learn remotely during the initial school closures associated with the COVID-19 pandemic. We then examine variation in remote instruction using an original statewide survey of teachers in Tennessee, deployed just a few weeks into the closures. Using three-level logistic regression models, we explore potential predictors of regular remote instruction, including prepandemic measures of broadband access, the demographic composition of schools, and measures of district policy responses created from districts’public COVID-19 plans. We find that teachers in schools serving more economically disadvantaged students and in rural districts are less likely to report regular remote instruction, especially via providing digital resources and holding virtual classes or tutoring. Fewer opportunities for Tennessee’s rural students appear driven in part by lower community access to high-speed broadband, but district policies to distribute technology may partially mitigate this gap in access.  \nKeywords: broadband access, COVID-19, district policy, opportunity to learn, remote instruction  \nSpring 2020 school closures caused by the COVID-19 pandemic forced K–12 schools to move rapidly to remote instruction. Given differences in available resources across schools and districts to organize instruction and to provide students with technology, remote instruction took different forms. Nationally, only a minority of districts provided teacher-delivered remote instruction (e.g., live online classes) or active monitoring of learning activities following school closures in spring 2020 (Gross & Opalka, 2020; Harris et al., 2020) . How districts implemented remote instruction and provided resources to ensure students’ access to that instruction are likely important factors influencing whether schools could mitigate declines in student achievement due to missed instructional time (Dorn et al., 2021; Kogan & Lavertu, 2021; Lewis et al., 2021) .  \nOf course, a precondition for remote learning is access to remote instruction (i.e., schools providing learning activities for students not physically at school and students being able to access those activities) . A long literature on students’opportunities to learn shows that students from historically marginalized backgrounds are systematically provided less  \naccess to learning opportunities at school (e.g., Carter & Welner, 2013; Duncan & Murnane, 2011) . If students in lower-income families, students in rural communities, students of color, or students with specific learning needs (e.g., students with disabilities, English learners) had systematically lower access to remote instruction—because it was not provided or because families lacked the technology or digital literacy to access it—the COVID-19 school closures would represent an extreme denial of learning opportunities that likely compounded existing inequities.  \nReports from parents and educators underscore these concerns about access to remote instruction. In two national surveys of parents conducted in spring 2020, higher-income parents reported greater internet access for their children to complete schoolwork and more frequent contact with teachers during pandemic-related school closures (Carnevale & Fasules, 2021; Vogel et al., 2020) . A nationally representative survey of educators conducted around the same time found t","cbCair4A1IjUC040","https://ap.wps.com/l/cbCair4A1IjUC040","pdf",1405341,22,"English","# Introduction\n## Remote learning and access requirements\n# Study design and research questions\n## Data sources and analytic approach\n## Research question 1\n## Research question 2","[{\"question\":\"What does the study examine about remote learning during COVID-19 closures?\",\"answer\":\"It examines how students’ opportunities to learn remotely varied during initial school closures and whether this variation reflects differences in remote instruction delivery.\"},{\"question\":\"Which factors are tested as predictors of regular remote instruction?\",\"answer\":\"The study tests pre-pandemic broadband access, school demographic composition, and district policy responses created from districts’ public COVID-19 plans.\"},{\"question\":\"How do findings relate to rural and economically disadvantaged communities?\",\"answer\":\"Teachers in schools serving more economically disadvantaged students and in rural districts are less likely to report regular remote instruction, particularly for providing digital resources and holding virtual classes or tutoring.\"}]","Broadband Access, District Policy, and Student Opportunities for Remote Learning During COVID-19 School Closures | PDF",1792068767,55]