Optimizing University Course Timetabling for Metaverse Integration: A Human-Centered Decision Model in Medical Education

Optimizing University Course Timetabling for Metaverse Integration: A Human-Centered Decision Model in Medical Education | 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 Optimizing University Course Timetabling for Metaverse Integration: A Human-Centered Decision Model in Medical Education Seckin Damar, Gulsah Hancerliogullari Koksalmis This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8021917/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background University Course Timetabling Problems (UCTTP) in medical schools have become more complex with the integration of metaverse technologies such as virtual and augmented reality. These immersive environments enhance medical education but also introduce new scheduling constraints involving specialized hardware, virtual classrooms, and simulation sessions. Addressing this need, the present study develops a human-centered optimization framework that aligns scheduling decisions with instructors’ behavioral intentions to adopt metaverse-based teaching methods. Methods A binary integer linear programming model was formulated to jointly assign regular and metaverse courses while satisfying institutional constraints. Professor-specific behavioral intention weights were derived using the Analytic Hierarchy Process (AHP) informed by constructs identified through Structural Equation Modeling (SEM). Two heuristic approaches—the Greedy Reassignment and Assignment for Professor Equity (GRAPE) and Simulated Annealing (SA)—were developed to solve the model. The parameters of SA were optimized using the Taguchi Design of Experiments method. Computational experiments were conducted on 45 synthetically generated instances of varying sizes. Results The results show that the GRAPE algorithm provides rapid feasible solutions, whereas the SA algorithm yields higher solution quality, particularly for large and complex problem instances. The Taguchi analysis indicated that the cooling rate and number of iterations significantly influence performance, achieving an excellent model fit (R² = 0.998). Overall, the SA method consistently produced near-optimal schedules with low relative error values while maintaining reasonable computation times. Conclusions This study introduces the first optimization framework that integrates behavioral intention modeling into course timetabling for metaverse-based education. The proposed approach enables institutions to allocate metaverse courses to instructors who demonstrate higher readiness to adopt immersive teaching technologies. These findings support the design of adaptive, human-centered scheduling systems that align pedagogical readiness with technological innovation in medical education. University course timetabling Educational technology integration Metaverse in medical education Integer linear programming Analytic hierarchy process Simulated annealing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 26 Jan, 2026 Reviews received at journal 26 Jan, 2026 Reviewers agreed at journal 08 Jan, 2026 Reviewers agreed at journal 08 Jan, 2026 Reviews received at journal 17 Dec, 2025 Reviews received at journal 14 Dec, 2025 Reviewers agreed at journal 14 Dec, 2025 Reviewers agreed at journal 08 Dec, 2025 Reviewers invited by journal 04 Dec, 2025 Editor invited by journal 11 Nov, 2025 Editor assigned by journal 08 Nov, 2025 Submission checks completed at journal 08 Nov, 2025 First submitted to journal 03 Nov, 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. 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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-8021917","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":556233532,"identity":"4f040ef1-fc96-4086-80d3-f3c9be7347c2","order_by":0,"name":"Seckin 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These immersive environments enhance medical education but also introduce new scheduling constraints involving specialized hardware, virtual classrooms, and simulation sessions. Addressing this need, the present study develops a human-centered optimization framework that aligns scheduling decisions with instructors\u0026rsquo; behavioral intentions to adopt metaverse-based teaching methods.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA binary integer linear programming model was formulated to jointly assign regular and metaverse courses while satisfying institutional constraints. Professor-specific behavioral intention weights were derived using the Analytic Hierarchy Process (AHP) informed by constructs identified through Structural Equation Modeling (SEM). Two heuristic approaches\u0026mdash;the Greedy Reassignment and Assignment for Professor Equity (GRAPE) and Simulated Annealing (SA)\u0026mdash;were developed to solve the model. The parameters of SA were optimized using the Taguchi Design of Experiments method. Computational experiments were conducted on 45 synthetically generated instances of varying sizes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe results show that the GRAPE algorithm provides rapid feasible solutions, whereas the SA algorithm yields higher solution quality, particularly for large and complex problem instances. The Taguchi analysis indicated that the cooling rate and number of iterations significantly influence performance, achieving an excellent model fit (R\u0026sup2; = 0.998). Overall, the SA method consistently produced near-optimal schedules with low relative error values while maintaining reasonable computation times.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study introduces the first optimization framework that integrates behavioral intention modeling into course timetabling for metaverse-based education. The proposed approach enables institutions to allocate metaverse courses to instructors who demonstrate higher readiness to adopt immersive teaching technologies. These findings support the design of adaptive, human-centered scheduling systems that align pedagogical readiness with technological innovation in medical education.\u003c/p\u003e","manuscriptTitle":"Optimizing University Course Timetabling for Metaverse Integration: A Human-Centered Decision Model in Medical Education","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-08 13:29:09","doi":"10.21203/rs.3.rs-8021917/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-26T12:05:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-26T06:55:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70418451060491264230862616690958487368","date":"2026-01-08T11:27:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"156721601243603661498550043701056311866","date":"2026-01-08T11:22:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-17T15:16:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-15T03:27:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"27810918383709600233421325708068975028","date":"2025-12-15T01:46:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13418963690737628737932143303776657270","date":"2025-12-08T16:55:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-04T12:59:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-11T07:07:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-08T07:28:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-08T07:28:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2025-11-03T18:25:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"63415eea-9551-4cf0-87fe-ee900df55a4f","owner":[],"postedDate":"December 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T08:55:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-08 13:29:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8021917","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8021917","identity":"rs-8021917","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}