Assessing Blended Learning Competencies Using Multimodal Data and Dual Regression

Assessing Blended Learning Competencies Using Multimodal Data and Dual Regression | 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 Research Article Assessing Blended Learning Competencies Using Multimodal Data and Dual Regression Jie Wu, Han Wei This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7167294/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract In the digital era, the educational sector is experiencing a profound transformation driven by the potential of digital technologies to enhance personalized learning, improve educational efficiency, and promote equity. However, the use of multimodal data for competency assessment remains underexplored, particularly in the context of integrating online and offline learning activities. This study proposes a multimodal data-based competency assessment model that integrates online and offline learning activities within a four-tier evaluation framework. Using ridge regression and support vector machine (SVR), this study demonstrates how multimodal data can improve the scientific rigor and effectiveness of competency assessments. Key findings emphasize the importance of rational supervision mechanisms for assessment validity and the role of foundational skills in fostering student innovation. These insights contribute to the intelligentization of educational evaluation and offer practical implications for teaching management. Multimodal Data Human‒Machine Collaboration Competency Assessment Ridge Regression Support Vector Machine Regression (SVR) Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 27 Sep, 2025 Reviews received at journal 19 Sep, 2025 Reviews received at journal 16 Sep, 2025 Reviewers agreed at journal 11 Sep, 2025 Reviewers agreed at journal 11 Sep, 2025 Reviewers invited by journal 11 Sep, 2025 Editor assigned by journal 25 Aug, 2025 Submission checks completed at journal 08 Aug, 2025 First submitted to journal 08 Aug, 2025 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-7167294","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":516207443,"identity":"a9736111-f639-4f0f-b329-ab65574e3607","order_by":0,"name":"Jie Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYBACfvnnxz8kGLDJ2R9vIFKLZENOGsODCj5jhjMHiNRicCDBjPHBGbnEhhsJxLrswIG0B4ltZomNMx9vvMFQYxNNUAdjY+Nxg8S2NONm6bRiC4ZjabkNhLQwMzMkSCS2HZNtk84xk2BsOExYCxsbgwFQy3/GHskzRGrh4WEwk0g4w6Y4Q4KHSC0SEjzJBgkVbMYGPEC/JBDjF/sb7Acf/gBGpQH74Y03PtTYENaCDAwkEkhRDtFCqo5RMApGwSgYGQAAGv8/zQwPwU4AAAAASUVORK5CYII=","orcid":"","institution":"Kunming University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Jie","middleName":"","lastName":"Wu","suffix":""},{"id":516207444,"identity":"07de887a-a3c5-4fef-9d6c-f405faa0c4ac","order_by":1,"name":"Han Wei","email":"","orcid":"","institution":"Kunming University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Han","middleName":"","lastName":"Wei","suffix":""}],"badges":[],"createdAt":"2025-07-20 03:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7167294/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7167294/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91647646,"identity":"e2cbb538-b364-4dc3-811d-0317da54801b","added_by":"auto","created_at":"2025-09-18 16:14:01","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":646898,"visible":true,"origin":"","legend":"","description":"","filename":"AssessingBlendedLearningCompetenciesUsingMultimodalDataandDualRegression.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7167294/v1_covered_588d4b3e-0c8f-4f6e-9c52-fe8e67f5daf5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing Blended Learning Competencies Using Multimodal Data and Dual Regression","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"discover-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diedu","sideBox":"Learn more about [Discover Education](https://www.springer.com/journal/44217)","snPcode":"44217","submissionUrl":"https://submission.nature.com/new-submission/44217/3","title":"Discover Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Multimodal Data, Human‒Machine Collaboration, Competency Assessment, Ridge Regression, Support Vector Machine Regression (SVR)","lastPublishedDoi":"10.21203/rs.3.rs-7167294/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7167294/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the digital era, the educational sector is experiencing a profound transformation driven by the potential of digital technologies to enhance personalized learning, improve educational efficiency, and promote equity. However, the use of multimodal data for competency assessment remains underexplored, particularly in the context of integrating online and offline learning activities. This study proposes a multimodal data-based competency assessment model that integrates online and offline learning activities within a four-tier evaluation framework. Using ridge regression and support vector machine (SVR), this study demonstrates how multimodal data can improve the scientific rigor and effectiveness of competency assessments. Key findings emphasize the importance of rational supervision mechanisms for assessment validity and the role of foundational skills in fostering student innovation. These insights contribute to the intelligentization of educational evaluation and offer practical implications for teaching management.\u003c/p\u003e","manuscriptTitle":"Assessing Blended Learning Competencies Using Multimodal Data and Dual Regression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-18 15:49:56","doi":"10.21203/rs.3.rs-7167294/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-27T15:01:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-19T13:52:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-17T02:03:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38967633913705041930956413626852626726","date":"2025-09-11T15:26:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303044183888961280559285303882657171445","date":"2025-09-11T11:37:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-11T10:23:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-25T07:17:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-08T08:08:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Education","date":"2025-08-08T08:05:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diedu","sideBox":"Learn more about [Discover Education](https://www.springer.com/journal/44217)","snPcode":"44217","submissionUrl":"https://submission.nature.com/new-submission/44217/3","title":"Discover Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1f35c949-241f-4c84-962e-7e32e4340483","owner":[],"postedDate":"September 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T18:08:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-18 15:49:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7167294","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7167294","identity":"rs-7167294","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}