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Using rich longitudinal observational and interview data, the research analyzes program characteristics and student attendance, estimating effects on reading and mathematics achievement for low-income students. Findings link tutor locations, formats, curriculum drivers, and provider characteristics to achievement gains, while revealing differential access by student characteristics that requires further investigation as roles expand in K–12 instruction.",{"@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/improving-access-to-quality-and-the-effectiveness-of-digital-tutoring-in-k12-education-digital-tutoring-study/602512/",{"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/improving-access-to-quality-and-the-effectiveness-of-digital-tutoring-in-k12-education-digital-tutoring-study/602512.png","ImageObject",300,407,{"name":92,"@type":93},"pixelkiddo","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":81},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What causes difficulty in assessing the impact of digital tutoring providers?","Question",{"text":112,"@type":113},"Providers vary in how they describe services, how students access them, what is delivered, and how closely offerings align with standards and district needs, complicating accurate impact assessment.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the study evaluate program characteristics and student outcomes?",{"text":117,"@type":113},"It uses a mixed-method, longitudinal design across multiple urban sites, examining characteristics from program models and studying student attendance and relationships to reading and math achievement for low-income students.",{"name":119,"@type":110,"acceptedAnswer":120},"What does the research find about access and effectiveness for different student groups?",{"text":121,"@type":113},"The findings raise concerns that some students receive tutoring types suggested as more effective, and English-language learners and students with disabilities were less likely to receive certain formats tied to improvements in math achievement.","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},602512,1792622822,{"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":81,"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},962090883892,"https://ap-avatar.wpscdn.com/avatar/e00115db34f3e0f11b?x-image-process=image/resize,m_fixed,w_180,h_180&k=1790152879550218658","Educational Evaluation and Policy Analysis March 2016, Vol. 38, No. 1, pp. 65–87 DOI: 10.3102/0162373715592706  \n© 2015 AERA. [http://eepa.aera.net](http://eepa.aera.net)  \nImproving Access to, Quality, and the Effectiveness of Digital Tutoring in K–12 Education  \nPatricia Burch  \nUniversity of Southern California  \nAnnalee Good  \nUniversity of Wisconsin-Madison  \nCarolyn Heinrich  \nUniversity of Texas at Austin  \nThere is considerable variation in how providers of digital education describe what they do, their services, how students access services, and what is delivered, complicating efforts to accurately assess its impact. We examine program characteristics of digital tutoring providers using rich, longitudinal observational and interview data and then analyze student attendance patterns and effects of digital tutoring on low-income students’ reading and mathematics achievement. We find significant associations between formats, curriculum drivers, tutor locations, and other characteristics of digital providers and their effectiveness in increasing student achievement, as well as differential access by student characteristics, that warrant further investigation as digital providers’ roles in K–12 instruction continue to expand.  \nKeywords: digital instruction, tutoring, student achievement  \nDigital instruction—using a digital platform (such as computer, netbook, or handheld device) as an integral and consistent part of an instructional delivery strategy—is rapidly becoming a commonplace component of K–12 classroom and supplemental instruction. Estimates place the current value of [the U.S. market](the U.S. market) for K–12 education software and digital content anywhere in the range of US$8 billion (Molnar & Cavanaugh, 2014) to US$21 billion per year (Burch & Good, 2014) . In the last decade, private-sector investment in K–12 education technology companies has nearly tripled, from US$146 million to US$420 million (Burch & Good, 2014) . As of 2011, 63% of districts with enrollments higher than 10,000 students contracted with an outside organization to provide  \nonline courses (Queen, Lewis, & Coopersmith, 2011) . Advances in technology have allowed digital tools to compete with features of face-toface instruction with the promise of low-cost,  \nbroad access (Richards & Struminger, 2013) .  \nIn this research, we focus on digital providers’role in out-of-school time (OST) tutoring programs, which has continued to expand, even as waivers from No Child Left Behind (NCLB) have released many districts from the requirement to offer federally funded supplemental education services. In a mixed-method, longitudinal study of OST tutoring conducted in five urban sites over 4 school years, we observed online tutoring companies reaching a student “market share” as high as 88% in one district; in another district, we observed a single digital provider  \nDigital Tutoring in K–12 Education  \ndelivering tutoring to more than 10,000 students. NCLB mandated unfettered parental choice in tutoring providers and accordingly gave providers the flexibility to try varied formats for tutoring. However, the implementation and effects of the wide range of approaches and formats that are emerging in digital tutoring are especially difficult for school districts to monitor and assess.  \nMoreover, there is considerable variation in how digital tutoring providers describe what they do, the actual services they offer, how students access these services, what is delivered, and the degree of alignment to state standards and district needs, which complicates efforts to accurately assess the effects of digital tutoring on students’academic achievement. Drawing on our 4-year mixed-methods study of federally funded OST tutoring programs, we examine key program characteristics of digital providers, as described in provider applications for state approval, recorded in district administrative data and enacted and observed in rich, longitudinal observational data. Spe","cbCaiuLzoDyB3WV0","https://ap.wps.com/l/cbCaiuLzoDyB3WV0","pdf",364937,23,"English","# Prior Research\n# Improving Access, Quality, and Effectiveness of Digital Tutoring in K–12 Education\n## Research Focus and Methods\n## Findings and Policy Implications","[{\"question\":\"What causes difficulty in assessing the impact of digital tutoring providers?\",\"answer\":\"Providers vary in how they describe services, how students access them, what is delivered, and how closely offerings align with standards and district needs, complicating accurate impact assessment.\"},{\"question\":\"How does the study evaluate program characteristics and student outcomes?\",\"answer\":\"It uses a mixed-method, longitudinal design across multiple urban sites, examining characteristics from program models and studying student attendance and relationships to reading and math achievement for low-income students.\"},{\"question\":\"What does the research find about access and effectiveness for different student groups?\",\"answer\":\"The findings raise concerns that some students receive tutoring types suggested as more effective, and English-language learners and students with disabilities were less likely to receive certain formats tied to improvements in math achievement.\"}]","Improving Access to, Quality, and the Effectiveness of Digital Tutoring in K–12 Education - Digital Tutoring Study | PDF",1792094799,58]