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The study examines gender-imbalanced enrollment in engineering and health sciences CTE using High School Longitudinal Study of 2009 data and decomposition techniques. Results show student occupational expectations as the largest contributor to gender gaps across content areas, highlighting where disparities emerge and how they shape STEMM pathways.",{"@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/explaining-course-enrollment-gaps-in-high-school-examination-of-gender-imbalance-in-the-applied-sciences/603159/",{"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/explaining-course-enrollment-gaps-in-high-school-examination-of-gender-imbalance-in-the-applied-sciences/603159.png","ImageObject",300,407,{"name":92,"@type":93},"MrHarris58","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-03","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":24},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does the study focus on?","Question",{"text":112,"@type":113},"It focuses on gender-imbalanced enrollment in STEMM-focused career and technical education (CTE) courses, especially in engineering and health sciences.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which data source and method are used to analyze enrollment gaps?",{"text":117,"@type":113},"The analysis uses data from the High School Longitudinal Study of 2009 and decomposition techniques to identify factors linked to gender gaps.",{"name":119,"@type":110,"acceptedAnswer":120},"What factor contributes most to gender gaps across content areas?",{"text":121,"@type":113},"Student occupational expectations are identified as the largest contributor to gender gaps across STEMM-focused CTE content areas.","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},603159,1792191257,{"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":24,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":36,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144},687212988360,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Explaining Course Enrollment Gaps in High School: Examination of Gender-Imbalance in the Applied Sciences  \nEducational Policy 2024, Vol. 38(4) 897–936 © The Author(s) 2023  \nArticle reuse guidelines:  \n[sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)[DOI: 10.1177/08959048231174884](DOI: 10.1177/08959048231174884)[ ](DOI: 10.1177/08959048231174884)[journals.sagepub.com/home/epx](journals.sagepub.com/home/epx)  \nJennifer A. Freeman 1, Michael A. Gottfried 1, and Taylor K. Odle2  \nAbstract  \nFederal policy in the United States has urged high schools to expand offeringsin career and technical education (CTE) coursework to address persistent gender inequities in science, technology, engineering, mathematics, and medical (STEMM) fields. Unfortunately, gender composition in engineering and health sciences CTE enrollment is highly imbalanced and reflects postsecondary and labor market trends. Using data from the High School Longitudinal Study of 2009, we use decomposition techniques to examine which student, family, and school factors explain gender-imbalanced enrollment in STEMM-focused CTE courses. The results indicate student occupational expectations were the largest contributor to gender gaps across content areas.  \nKeywords  \ngender gaps, STEMM, decomposition, high school, career and technical education  \n1 University of Pennsylvania, Philadelphia, USA 2University of Wisconsin-Madison, USA  \nCorresponding Author:  \nJennifer A. Freeman, Graduate School of Education, University of Pennsylvania, 3700 Walnut Street, Philadelphia, PA 19104-6216, USA.  \nEmail: [jafree@upenn.edu](jafree@upenn.edu)  \nCareers in science, technology, engineering, mathematics, and the medical or health sciences (STEMM) represent approximately one quarter (23%) of the U.S. workforce (Okrent & Burke, 2021) . Jobs in these fields have long been regarded as well-paying and stable, with median annual wages more than double those of non-STEMM occupations and unemployment rates at nearly half that of other professions (Bureau of Labor Statistics, 2020; Okrent & Burke, 2021) . However, STEMM fields are also highly gender imbalanced. While women represent nearly half (48%) of all American workers, they only represent 27% of those employed in STEMM overall, 25% of those employed in computer-related occupations, and 15% of those in engineering (Martinez & Christnacht, 2021) . Conversely, women are overrepresented in STEMM health services occupations, where men instead represent only 25% of workers (Bureau of Labor Statistics, 2021) . These wide gaps in gendered participation begin early along students’ educational pathways into STEMM.  \nFrom as early as elementary school, girls are less likely to be placed in accelerated math courses (Hemelt & Lenard, 2020), and by high school, girls report lower interest in math and sciences courses and earn substantially fewer credits in STEMM-related fields (Cunningham et al., 2015) . These gaps persist into college, through degree attainment, and into the workforce (Cimpian et al., 2020), where girls are most often sorted into predominantly female and lower-paying fields, like medical assisting (Institute for Women’s Policy Research, 2013; Malin et al., 2014) and boys are sorted into higherpaying, more mathematically intensive fields like computer science and engineering (Committee on Equal Opportunities in Science and Engineering, 2013; Toglia, 2013) .  \nTo combat this gender sorting, educational policy has focused on ways to prepare female students for workforce participation in STEMM fields before college begins. One noteworthy example is the federal Perkins legislation (i.e., the Carl D. Perkins Strengthening Career and Technical Education for the 21st Century Act, most recently authorized in 2006 as Perkins IV and in 2018 as Perkins V), which governs and provides funding for secondary and postsecondary career and technical education (CTE) programing. Highschool CTE co","cbCaisCbaNpzHMrF","https://ap.wps.com/l/cbCaisCbaNpzHMrF","pdf",735128,"English","# Abstract\n## Federal policy and gender inequities\n## STEMM representation and enrollment gaps\n## Data and decomposition approach\n## Key findings","[{\"question\":\"What problem does the study focus on?\",\"answer\":\"It focuses on gender-imbalanced enrollment in STEMM-focused career and technical education (CTE) courses, especially in engineering and health sciences.\"},{\"question\":\"Which data source and method are used to analyze enrollment gaps?\",\"answer\":\"The analysis uses data from the High School Longitudinal Study of 2009 and decomposition techniques to identify factors linked to gender gaps.\"},{\"question\":\"What factor contributes most to gender gaps across content areas?\",\"answer\":\"Student occupational expectations are identified as the largest contributor to gender gaps across STEMM-focused CTE content areas.\"}]","Explaining Course Enrollment Gaps in High School - Examination of Gender-Imbalance in the Applied Sciences | PDF",1792095814,101]