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Using longitudinal student data from four anonymous states, it validates three metric types—credit thresholds, math/English gateway completion, and in-high-school credential completion—against enrollment, completion by about age 24, and time to degree outcomes.",{"@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/dual-enrollment-momentum-metrics-leading-indicators-for-program-improvement/584330/",{"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/dual-enrollment-momentum-metrics-leading-indicators-for-program-improvement/584330.png","ImageObject",300,407,{"name":92,"@type":93},"Kyle","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":19},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does the report address with current dual enrollment metrics?","Question",{"text":112,"@type":113},"The report notes that established metrics are often too simplistic, usually recording whether a student takes a DE course rather than the amount or type of DE credits completed.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What “momentum metrics” does the report introduce?",{"text":117,"@type":113},"The report introduces three metric types: threshold numbers of DE credits completed, gateway course completion in math and/or English, and college credential completion while in high school.",{"name":119,"@type":110,"acceptedAnswer":120},"How does the report evaluate whether metrics predict postsecondary success?",{"text":121,"@type":113},"It validates each metric using longitudinal student data from four anonymous states, focusing on students who completed college-level courses in high school and comparing predictions across student gender, race/ethnicity, Title I status, and geographic locale.","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},584330,1792851807,{"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":19,"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":36,"preview_page_count":4},3985741905716,"https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d","RESEARCH REPORT | MAY 2026  \nDual Enrollment Momentum Metrics:  \nLeading Indicators for Program Improvement  \nBy Tatiana Velasco, Daniel Sparks, Lauren Schudde, Eliza Levin, Yuxin Lin, Wonsun Ryu, and John Fink  \nOver the last two decades, the number of high school students taking college-level dual enrollment (DE) coursework has grown steadily, reaching 2.8 million in 2023-24 (Fink, 2025c). Although DE programs are widespread nationally, they are far from uniform in terms of design and implementation. For example, a student may participate in an intensive Early College High School program or simply take a single a la carte DE course to supplement their regular high school curriculum. State policies also vary across key elements of DE, including funding for colleges and school districts (Jenkins, Steiger, & Fink, 2025), out-of-pocket costs for students—DE is provided free of charge to students in about half of states (Zinth, 2025)—and academic eligibility requirements (Jamieson et al., 2022) .  \nDespite this wide range of program designs and policy contexts, DE appears, on average, to increase students’ post–high school chances of enrolling in college and earning a college credential (Schaller et al., 2023). Yet, while postsecondary outcomes of DE students are stronger than those of nonparticipants, the magnitude of this difference varies substantially by state (Velasco et al., 2024). Furthermore, research consistently illustrates gaps in DE access among student groups already underrepresented in postsecondary education, such as low-income students and students of color (Liu et al., 2026; Sparks et al., 2025; Xu et al., 2021).  \nTo strengthen DE as an on-ramp to college and career, practitioners and policymakers need better metrics to track students’ participation and early success in DE. The established metrics currently used are relatively simplistic; they typically capture whether or not a student takes a DE course rather than the amount or type of DE credits the student completes. Some states like Texas are implementing policies that reward specific amounts of DE credits earned in high school (with, e.g. , incentives for K-12 districts when students complete 9 DE creditsand incentives for colleges when students complete 15). Yet there is limited guidance on which credit accumulation thresholds best predict postsecondary outcomes. Identifying predictive metrics can help educators choose accurate and reliable leading indicators that are the most useful for assessing DE program improvements. Timely information on likely program outcomes is particularly important for continuous improvement efforts, as it allows practitioners and policymakers to observe how programmatic changes may produce short-term effects that lead to longer-term consequences—without waiting years for long-term data.  \nDual Enrollment Momentum Metrics: Leading Indicators for Program Improvement  \nResearch on community college students without prior DE experience indicates that “early momentum metrics” capturing first-year college credit accumulation (earning 6 or 12 credits in the first term, or 15 or 30 credits in the first year) and first-year college math and English completion reliably predict subsequent student credential completion and thus function as leading indicators ofthe effectiveness of institutional reforms (Belfield et al., 2019). Despite the widespread use of early momentum metrics in community college reform efforts (Jenkins, Lahr, et al., 2025), no study has yet adapted and validated similar metrics as leading indicators to support program improvement efforts in the DE context.  \nIn this report, we introduce a set ofDE momentum metrics that mark participation and academic progress of high school DE students, and we assess how reliably these metrics predict postsecondary success. We identify and test three types of metrics: threshold numbers of DE credits completed, gateway course completion in math and/or English, and college credential com","cbCainfR9MaQl8ld","https://ap.wps.com/l/cbCainfR9MaQl8ld","pdf",331006,16,"English","# Dual Enrollment Momentum Metrics: Leading Indicators for Program Improvement\n## State-by-State Context","[{\"question\":\"What problem does the report address with current dual enrollment metrics?\",\"answer\":\"The report notes that established metrics are often too simplistic, usually recording whether a student takes a DE course rather than the amount or type of DE credits completed.\"},{\"question\":\"What “momentum metrics” does the report introduce?\",\"answer\":\"The report introduces three metric types: threshold numbers of DE credits completed, gateway course completion in math and/or English, and college credential completion while in high school.\"},{\"question\":\"How does the report evaluate whether metrics predict postsecondary success?\",\"answer\":\"It validates each metric using longitudinal student data from four anonymous states, focusing on students who completed college-level courses in high school and comparing predictions across student gender, race/ethnicity, Title I status, and geographic locale.\"}]","Dual Enrollment Momentum Metrics - Leading Indicators for Program Improvement | PDF",1792050684]