[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-206558-105":59,"doc-detail-206558-en":125},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":118,"head_meta":120,"extra_data":122,"updated_unix":124},105,"en","a-multilevel-modelling-approach-to-investigating-ucas-predicted-vs-achieved-grades-key-findings","A multilevel modelling approach to investigating UCAS predicted vs achieved grades - Key findings","","The research investigates how the gap between UCAS predicted and achieved A level grades varies across applicant groups in the 2019 admissions cycle. Using a contextual effects multilevel model with applicants nested within schools, it identifies differences at both applicant and school levels. Applicant-level effects include variation by ethnicity, sex and school type, disadvantage (IDACI), and prior attainment. Strong school contextual effects remain after adjustment, with additional nontrivial differences persisting, supported by model respecifications.",{"@graph":69,"@context":117},[70,84,100],{"@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/a-multilevel-modelling-approach-to-investigating-ucas-predicted-vs-achieved-grades-key-findings/206558/",{"url":83,"name":65,"@type":85,"author":86,"headline":65,"publisher":89,"fileFormat":92,"inLanguage":63,"description":67,"dateModified":93,"datePublished":94,"encodingFormat":92,"isAccessibleForFree":95,"interactionStatistic":96},"DigitalDocument",{"name":87,"@type":88},"Seraphina","Person",{"url":74,"name":90,"@type":91},"DocShare","Organization","application/pdf","2026-09-08","2026-09-05",true,{"@type":97,"interactionType":98,"userInteractionCount":8},"InteractionCounter",{"@type":99},"ViewAction",{"@type":101,"mainEntity":102},"FAQPage",[103,109,113],{"name":104,"@type":105,"acceptedAnswer":106},"What does the study mean by the “predicted-achieved gap”?","Question",{"text":107,"@type":108},"The term describes the difference between UCAS predicted grades and achieved grades. Larger negative differences indicate a larger predicted-achieved gap.","Answer",{"name":110,"@type":105,"acceptedAnswer":111},"Which applicant groups show larger predicted-achieved gaps?",{"text":112,"@type":108},"Applicants from Asian, Black, and Other ethnic groups, female applicants, and males from single sex schools achieve further below predicted grades than their respective peers. Disadvantaged applicants also show larger gaps, while higher prior attainment is associated with smaller gaps.",{"name":114,"@type":105,"acceptedAnswer":115},"What contextual school effects does the model identify?",{"text":116,"@type":108},"Schools with lower prior attainment at GCSE are linked to larger gaps. Additional school factors include HE choices with lower entry requirements relative to predicted grades and higher average disadvantage. Sixth form colleges show closer alignment with predicted grades than other school types.","https://schema.org",{"og:url":83,"og:type":119,"og:title":65,"og:site_name":90,"og:description":67},"article",{"robots":121,"canonical":83},"index,follow",{"doc_id":123,"site_id":62},206558,1788594826,{"code":4,"msg":5,"data":126},{"doc_id":123,"user_id":127,"nickname":87,"user_avatar":128,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":129,"file_id":130,"file_url":131,"file_type":132,"file_size":133,"view_count":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":134,"language":135,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":136,"faqs":137,"seo_title":138,"seo_description":67,"update_tm":124,"read_time":139},962075114101,"https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165","A multilevel modelling ApproAch to investigAting ucAs predicted vs Achieved grAdes  \nKey points  \nX This research explores how the gap between UCAS predicted and achieved A level grades differs between applicant groups. It focuses on the largest homogeneous subgroup:18-year-old applicants from England applying in the 2019 admissions cycle with three predicted A levels.  \nX A contextual effects model identified differences at both applicant and school level.  \n􀂃 Applicant level differences included:  \n» Applicants from Asian, Black, and Other ethnic groups achieve further below UCAS predicted grades than their peers from the White ethnic group.  \n» Female applicants, and male applicants from single sex schools1 achieved further below UCAS predicted grades than male applicants from mixed schools.  \n» Disadvantaged applicants (defined using IDACI score) achieved further below UCAS predicted grades than advantaged applicants.  \n» Students with higher prior attainment (included as a statistical control) achieved closer to UCAS predicted grades.  \n􀂃 School contextual effects included:  \n» Applicants attending schools with lower prior attainment at GCSE achieved further below UCAS predicted grades. This was the strongest contextual effect.  \n» Applicants in schools with HE choices with lower entry requirements (relative to UCAS predicted grades) and higher average disadvantage achieved further below UCAS predicted grades.  \n» Those attending sixth form colleges achieved closer to UCAS predicted grades than those attending other school types.  \nX Nontrivial school differences remained after adjustment for model factors.  \nPredicted-achieved gap  \nThroughout this report, for brevity, the term‘predicted-achieved gap’ is used to describe the difference between UCAS predicted grades and achieved grades. Achieved grades that are further below UCAS predicted grades are described as having a larger ‘predicted-achieved gap’.  \n1 Defined as schools with only male applicants in the modelling sample. Consequently, some schools described as ‘single sex’ may have included both male and female pupils in the wider population.  \ncontents  \n Key points 2  \n Introduction 3  \nBackground 3  \nRole of UCAS predicted grades in UK HE admissions 3  \nUCAS predicted grades are generally higher than achieved results 3  \nWhat does this research provide? 3  \nModelling sample 4  \nDependent variable 5  \nModelling approach 6  \nFixed effects included in the model 7  \n Results 9  \nOverview 9  \nModel estimates 9  \nUnderstanding applicant  \nlevel effects 11  \nUnderstanding school level effects 12  \nRelative importance of fixed effects 14  \nNontrivial school differences remained after adjustment for fixed effects 14  \nCeiling effects 14  \nConclusions were broadly consistent with various model respecifications 15  \n Acknowledgement 16  \n References 16  \nintroduction  \nBackground  \nUCAS predicted grades, made by teachers and other advisers for applicants with pending qualifications, area feature of the current United Kingdom (UK) Higher Education (HE) admissions process. Their use in the admissions process, and the weight placed on them, varies across courses and institution. This research provides new insight into differences between applicant groups in achievement relative to UCAS predicted grades.  \nRole of UCAS predicted grades in UK HE admissions  \nMost 18-year-old applicants from the UK apply to HE with UCAS predicted grades. These relate to ‘pending qualifications’ -those due to be awarded after the application is submitted-and are submitted by referees in applicants’ schools.  \nUCAS predicted grades are used by universities and colleges to understand an applicant’s potential. They are defined as “the grade of qualification an applicant’s school or college believes they’re likely to achieve in positive circumstances.” They support a flexible admissions process allowing those with achieved qualifications to apply alongside those still studying.  \nUCAS predicted grades","cbCaikiYSRagC4M1","https://ap.wps.com/l/cbCaikiYSRagC4M1","pdf",334864,17,"English","# Key points\n# Predicted-achieved gap\n# Introduction\n## Background\n## Role of UCAS predicted grades in UK HE admissions\n## UCAS predicted grades are generally higher than achieved results\n## What does this research provide?\n# Analysis\n## Modelling sample\n## Dependent variable\n## Modelling approach\n## Fixed effects included in the model\n# Results\n## Overview\n## Model estimates\n## Understanding applicant level effects\n## Understanding school level effects\n## Relative importance of fixed effects\n## Nontrivial school differences remained after adjustment for fixed effects\n## Ceiling effects\n# Conclusions\n## Acknowledgement\n## References","[{\"question\":\"What does the study mean by the “predicted-achieved gap”?\",\"answer\":\"The term describes the difference between UCAS predicted grades and achieved grades. Larger negative differences indicate a larger predicted-achieved gap.\"},{\"question\":\"Which applicant groups show larger predicted-achieved gaps?\",\"answer\":\"Applicants from Asian, Black, and Other ethnic groups, female applicants, and males from single sex schools achieve further below predicted grades than their respective peers. Disadvantaged applicants also show larger gaps, while higher prior attainment is associated with smaller gaps.\"},{\"question\":\"What contextual school effects does the model identify?\",\"answer\":\"Schools with lower prior attainment at GCSE are linked to larger gaps. Additional school factors include HE choices with lower entry requirements relative to predicted grades and higher average disadvantage. Sixth form colleges show closer alignment with predicted grades than other school types.\"}]","A multilevel modelling approach to investigating UCAS predicted vs achieved grades - Key findings | PDF",43]