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Disaggregated data break those aggregated results into smaller units (such as by race or gender) to reveal patterns that may be hidden in the overall average.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"Why does disaggregated data matter for equity gaps in higher education?",{"text":68,"@type":64},"It helps institutions identify where inequalities exist, measure their magnitude, and establish a baseline for evaluating initiatives. This supports planning targeted interventions and directing resources where they are most needed.",{"name":70,"@type":61,"acceptedAnswer":71},"What infrastructure or limitations affect the use of disaggregated data by higher education institutions?",{"text":72,"@type":64},"Not all institutions have the infrastructure or funding to compile and store disaggregated datasets. These constraints can limit their ability to use disaggregated data for decision-making.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},584734,1792192753,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,110,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},"Healthcare",40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":112,"slug":113},8,30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":111,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":55,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":143,"read_time":144,"preview_page_count":4},137451208677,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","ATTAINMENT  FOR ALL:   \nEQUITY IN   \nPOSTSECONDARY PATHWAYS  \nAdvancing Equity Through the Use of Disaggregated Data  \n􀀟 TAB L E O F C O N T E N T S 􀀟  \n01 INTRODUCTION  \n01 WHAT ARE DISAGGREGATED DATA?  \n01 DISAGGREGATED DATA TO CLOSE EQUITY GAPS IN HIGHER EDUCATION  \n02 BEST PRACTICES IN USING DISAGGREGATED DATA  \n05 GUIDING QUESTIONS FOR POLICYMAKERS, PRACTITIONERS, AND EDUCATION LEADERS  \n05 THE NEXT GENERATION OF ATTAINMENT GOALS  \n05 ACKNOWLEDGMENTS  \nATTAINMENT FOR ALL: POSTSECONDARY PATHWAYS  \nAdvancing Equity Through the Use of Disaggregated Data  \n􀀟 INTRODUCTION  \nFrom Fall 2019 through Spring 2020, The Hunt Institute released a series of policy briefs, Attainment for All: Postsecondary Pathways, that highlighted scalable state-level strategies to boost postsecondary attainment rates among specific student subpopulations including high school graduates, first-generation students, and adult learners. Building upon the momentum of this series, the higher education team at The Hunt Institute has created a follow-up series of briefs that further explore the intersection between equity and efforts to raise postsecondary attainment rates.  \nThis is the last brief of the three-part Attainment for All: Equity in Postsecondary Pathways series. The first  brief explored the idea of embedding equity in postsecondary attainment, identified barriers to achieving equity, and included examples of states’ work to ensure equity in all aspects of postsecondary attainment. The second brief examined the importance of student wraparound services that provide equitable support to students. This third and final brief brings the discussion on equity full circle by examining the use of disaggregated data to narrow equity gaps in postsecondary education.  \nNote: Throughout this issue brief, various terms are used to refer to different racial and ethnic groups. The use of different terms is intended to accurately reflect the framing used in the methodologies of the various underlying studies cited.  \n􀀟 WHAT ARE DISAGGREGATED DATA?  \nData have been a part of education since the inception of public education. Data simply refers to facts and statistics that are collected to reference or analyze. In education, data includes test scores, attendance, grades, student growth, and numerous other variables. Over the past several decades the amount and availability of data has exponentially increased as technology has advanced. As more data were collected from multiple sources or assessments, education leaders realized these data could be combined to provide amore complete picture. Aggregated data refers to data that are collected from multiple sources or measures and are compiled into a larger summary for reporting and/or analysis. Aggregated data have provided education leaders the ability to analyze broader trends in student populations and make data-informed institutional and policy decisions.  \nAggregated data have proved useful in many facets but combining data may have the unintentional consequence of hiding some patterns that only apply to a specific subgroup of students. Disaggregated data refers to taking aggregated data and breaking it down into smaller units for analysis. For example, the aggregate graduation rate for a school may be high but dividing that graduation rate out by race or gender may show that one subpopulation of students is graduating at a lower rate than their peers.  \n􀀟 DISAGGREGATED DATA TO CLOSE EQUITY GAPS IN HIGHER EDUCATION  \nWhile disaggregated data are used across the education continuum, higher education has seen an increase in the use of disaggregated data in recent years. Institutions of Higher Education (IHEs) now spend a tremendous amount of money to gather data from multiple sources. Departments such as Institutional Research and Analysis, Student Affairs, Academic Affairs, Admissions, and Information Technology all collect data, and these data points are traditionally compiled within a larger data base. In turn","cbCaikxlxQrTeGuX","https://ap.wps.com/l/cbCaikxlxQrTeGuX","pdf",872500,"English","# INTRODUCTION\n## WHAT ARE DISAGGREGATED DATA?\n## DISAGGREGATED DATA TO CLOSE EQUITY GAPS IN HIGHER EDUCATION\n## BEST PRACTICES IN USING DISAGGREGATED DATA\n## GUIDING QUESTIONS FOR POLICYMAKERS, PRACTITIONERS, AND EDUCATION LEADERS\n## THE NEXT GENERATION OF ATTAINMENT GOALS","[{\"question\":\"What are disaggregated data and how do they differ from aggregated data?\",\"answer\":\"Aggregated data compile multiple sources into a larger summary. Disaggregated data break those aggregated results into smaller units (such as by race or gender) to reveal patterns that may be hidden in the overall average.\"},{\"question\":\"Why does disaggregated data matter for equity gaps in higher education?\",\"answer\":\"It helps institutions identify where inequalities exist, measure their magnitude, and establish a baseline for evaluating initiatives. This supports planning targeted interventions and directing resources where they are most needed.\"},{\"question\":\"What infrastructure or limitations affect the use of disaggregated data by higher education institutions?\",\"answer\":\"Not all institutions have the infrastructure or funding to compile and store disaggregated datasets. These constraints can limit their ability to use disaggregated data for decision-making.\"}]","ATTAINMENT FOR ALL: POSTSECONDARY PATHWAYS - INTRODUCTION - Advancing Equity Through the Use of Disaggregated Data | PDF",1792052091,18]