Integrating educational Psychology into AI-Driven Instructional Support: Modeling and Analysis of Student Learning Behavior Patterns

Integrating educational Psychology into AI-Driven Instructional Support: Modeling and Analysis of Student Learning Behavior Patterns | 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 Integrating educational Psychology into AI-Driven Instructional Support: Modeling and Analysis of Student Learning Behavior Patterns Ruizhi Ji This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6462451/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 In the realm of medical education, the swift advancement of artificial intelligence (AI) technology has led to its increasingly widespread application in teaching. This paper aims to investigate the use of AI in facilitating teaching behaviors within medical educational psychology, with a particular focus on the construction of models depicting student learning behaviors. By delving into the ways AI technology affects teaching interactions, student learning motivation, and behavioral patterns, the paper seeks to uncover the underlying medical educational psychological mechanisms of AI-assisted teaching. A three-party evolutionary game model has been developed, encompassing three primary entities: AI, teachers, and students. Through the establishment and resolution of this model, comprehensive analyses of the equilibrium strategies for each party are conducted. Additionally, the paper provides a thorough examination of the evolution trajectory of equilibrium stable points and investigates the influence of various parameters on the game states of the parties, particularly the impacts of spillover and moral sentiment parameters. medical educational psychology AI Assisted Role individual interest replication dynamic equation psychological cognitive parameters material incentive coupling 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. 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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-6462451","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":454522173,"identity":"93d479b8-102a-4fd2-8bdd-61f5e373f801","order_by":0,"name":"Ruizhi Ji","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYBACxmYgkcBwgIcfwmcDkxJEaZFsYAZrkSCoBQoOMBgcYEZYgFcLczvvM4kHf+7IGJ8/f0yCsY2vDqj34G0eBrs83A5jN5NI4HnGY3YjGeioM2wSBgfYkq15GJKLcWthY5NIkDgM1MIM1FIB0sJjJs3DcCCxAa8Wg8M8xv2HgVoMQFr4vxGhJeEwjwFDMtwWNkJamC0SDhzmkbiRbGyRcIZNcuZhNmPLOQbJOLUY9h9jvPnjz2F7/v6DD298bDvGz3e8+eGNNxV2uLWgSCQwHAOGO4hlgEM9EMij8WtwKx0Fo2AUjIIRCwBsvEoU9hMccAAAAABJRU5ErkJggg==","orcid":"","institution":"Xi'an Jiaotong University","correspondingAuthor":true,"prefix":"","firstName":"Ruizhi","middleName":"","lastName":"Ji","suffix":""}],"badges":[],"createdAt":"2025-04-16 10:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6462451/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6462451/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83896803,"identity":"f6818d19-21d9-4eeb-835e-ac664b3b4932","added_by":"auto","created_at":"2025-06-04 08:54:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":806726,"visible":true,"origin":"","legend":"","description":"","filename":"IntegratingEducationalPsychologyintoAIDrivenInstructionalSupportModelingandAnalysisofStudentLearningBehaviorPatterns.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6462451/v1_covered_2f7019e2-ddd7-486a-8350-1dc8ab9de482.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrating educational Psychology into AI-Driven Instructional Support: Modeling and Analysis of Student Learning Behavior Patterns","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":"medical educational psychology, AI Assisted Role, individual interest, replication dynamic equation, psychological cognitive parameters, material incentive coupling","lastPublishedDoi":"10.21203/rs.3.rs-6462451/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6462451/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eIn the realm of medical education, the swift advancement of artificial intelligence (AI) technology has led to its increasingly widespread application in teaching. 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