Research on the prediction of the number of scholarships won by college students based on the RF-LightGBM model

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Abstract With the increasing number of university graduates every year, college students are facing serious employment challenges. Good academic performance and a higher number of scholarships are conducive to enhancing students' competitiveness, however, they lack the ability to plan their academic life reasonably. In order to guide them to plan their study life reasonably and efficiently to promote better employment, this study proposes the RF-LightGBM model for predicting the number of scholarships awarded to students and analysing the important factors affecting the number of academic scholarships awarded. The experimental results show that the accuracy of the model reaches 83.1%, which is higher than other models, and can predict the number of scholarships awarded more accurately. The key features affecting the number of scholarships awarded are the grades of professional courses, and the scores assigned to the behavioural performance in school, so it is suggested that students should pay attention to the study of professional courses, and take an active part in professional competitions, volunteer activities, etc., so as to improve the comprehensive quality of the individual. This study provides a feasible reference for students on how to better obtain academic scholarships, which will help them plan their study life and enhance their competitiveness so that they can better cope with the challenges of employment.
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Research on the prediction of the number of scholarships won by college students based on the RF-LightGBM model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Research on the prediction of the number of scholarships won by college students based on the RF-LightGBM model Xin Xie, Yanmin Niu, Yan Ma This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5127710/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract With the increasing number of university graduates every year, college students are facing serious employment challenges. Good academic performance and a higher number of scholarships are conducive to enhancing students' competitiveness, however, they lack the ability to plan their academic life reasonably. In order to guide them to plan their study life reasonably and efficiently to promote better employment, this study proposes the RF-LightGBM model for predicting the number of scholarships awarded to students and analysing the important factors affecting the number of academic scholarships awarded. The experimental results show that the accuracy of the model reaches 83.1%, which is higher than other models, and can predict the number of scholarships awarded more accurately. The key features affecting the number of scholarships awarded are the grades of professional courses, and the scores assigned to the behavioural performance in school, so it is suggested that students should pay attention to the study of professional courses, and take an active part in professional competitions, volunteer activities, etc., so as to improve the comprehensive quality of the individual. This study provides a feasible reference for students on how to better obtain academic scholarships, which will help them plan their study life and enhance their competitiveness so that they can better cope with the challenges of employment. Physical sciences/Mathematics and computing Physical sciences/Mathematics and computing/Computer science academic scholarships RF-LightGBM educational data mining predictive models Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5127710","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":386975009,"identity":"5dd1bfee-1def-48ac-be32-042bc645ab66","order_by":0,"name":"Xin Xie","email":"","orcid":"","institution":"College of Computer and Information Science,Chongqing Normal University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Xie","suffix":""},{"id":386975010,"identity":"fd42e9b2-b933-4334-8e0d-85b7a629fab1","order_by":1,"name":"Yanmin Niu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIiWNgGAWjYDACZhBRAeXwEK/lDElaQICxjRQt5uw8ZlI359nJbpdIYHzwto1B3pyQFstmHjPp3G3JxjtnJDAbzm1jMNzZQECLwWGwlgOJG24ksEnztjEkGBwgSsscsBb23yRoaYDYwkykFrZi65xjycYbzjxslpxzTsJwA0Et5w9vvJ1TYye74XjywQ9vymzkCdoCBCwSQIKxAYQYGCQIqwcC5g8QLaNgFIyCUTAKcAAA5rQ9dogtPDcAAAAASUVORK5CYII=","orcid":"","institution":"College of Computer and Information Science,Chongqing Normal University","correspondingAuthor":true,"prefix":"","firstName":"Yanmin","middleName":"","lastName":"Niu","suffix":""},{"id":386975011,"identity":"0f506dec-a621-4f4f-95da-ea73ec0fed60","order_by":2,"name":"Yan Ma","email":"","orcid":"","institution":"College of Computer and Information Science,Chongqing Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Ma","suffix":""}],"badges":[],"createdAt":"2024-09-21 08:51:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5127710/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5127710/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73897029,"identity":"bb594c55-d778-4b32-a1bf-269511773374","added_by":"auto","created_at":"2025-01-15 16:38:52","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":636464,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5127710/v1_covered_3de9e318-66fa-4c8d-814b-6715d55b5158.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on the prediction of the number of scholarships won by college students based on the RF-LightGBM model","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"academic scholarships, RF-LightGBM, educational data mining, predictive models","lastPublishedDoi":"10.21203/rs.3.rs-5127710/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5127710/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWith the increasing number of university graduates every year, college students are facing serious employment challenges. 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