Effects of Different AI-driven Chatbot Feedback on Learning Outcomes and Brain Activity

Effects of Different AI-driven Chatbot Feedback on Learning Outcomes and Brain Activity | 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 Effects of Different AI-driven Chatbot Feedback on Learning Outcomes and Brain Activity Yi Hu, Jiaqi Yin, Haoxin Xu, Yafeng Pan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4649720/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Apr, 2025 Read the published version in npj Science of Learning → Version 1 posted 10 You are reading this latest preprint version Abstract Artificial intelligence (AI)-driven chatbots provide instant feedback to support learning. Yet, the impacts of different feedback on behavior and brain activation remain underexplored. We investigated how metacognitive, affective, and neutral feedback from an educational chatbot affected learning outcomes and brain activity through functional near-infrared spectroscopy technique. Students receiving metacognitive feedback showed higher transfer scores and metacognitive sensitivity, brain activation in the frontopolar area and middle temporal gyrus than other feedback types. Such activation correlated with metacognitive sensitivity. Students receiving affective feedback showed better retention scores than those receiving neutral feedback and higher activation in the supramarginal gyrus. Students receiving neutral feedback exhibited higher activation in the frontal eye fields and dorsolateral prefrontal cortex than other feedback types. The machine learning model outputs key brain regions that predict transfer scores. These findings underscore the potential of diverse feedback types in enhancing learning via human-chatbot interaction. Biological sciences/Psychology/Human behaviour Scientific community and society/Social sciences/Education Full Text Additional Declarations (Not answered) Cite Share Download PDF Status: Published Journal Publication published 15 Apr, 2025 Read the published version in npj Science of Learning → Version 1 posted Editorial decision: revise 18 Oct, 2024 Review # 2 received at journal 05 Oct, 2024 Review # 1 received at journal 19 Sep, 2024 Reviewer # 2 agreed at journal 17 Sep, 2024 Reviewer # 1 agreed at journal 03 Sep, 2024 Reviewers invited by journal 03 Sep, 2024 Submission checks completed at journal 05 Jul, 2024 First submitted to journal 03 Jul, 2024 Unknown event 03 Jul, 2024 Editor assigned by journal 27 Jun, 2024 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. 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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-4649720","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":348746340,"identity":"914bc1f0-5d15-4d5a-94f8-ae50a1bb2aa7","order_by":0,"name":"Yi Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYDACCQbGB0hcZqK0MBuQrIVNgjQtBrd7zKoL/hxm4Gc/e0yCocI6sYH97AH8Wu6cMbs9s+0wg2RPXpoEw5n0xAaevAT8Wm7kmN3mbTgMZPCYSTC2HU5skOAxIKilmAfoMHuwln9EamHmYQPaIgHS0kCEFskbacXSM9vSeSTO5BhbJBxLN27jycGvhe9G8sbPBX+s5fjbzxje+FBjLdvPfga/FoUD4Lho5gHzEoCYDa96IJBvAGupI6RuFIyCUTAKRjIAAORAP1wECLgHAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-0243-9060","institution":"East China Normal University","correspondingAuthor":true,"prefix":"","firstName":"Yi","middleName":"","lastName":"Hu","suffix":""},{"id":348746341,"identity":"8098d3c0-2b24-4588-851f-35ecf7d4220e","order_by":1,"name":"Jiaqi Yin","email":"","orcid":"","institution":"East China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Jiaqi","middleName":"","lastName":"Yin","suffix":""},{"id":348746342,"identity":"b207e47c-e80f-4032-b582-1c15ff539310","order_by":2,"name":"Haoxin Xu","email":"","orcid":"https://orcid.org/0000-0002-5007-509X","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Haoxin","middleName":"","lastName":"Xu","suffix":""},{"id":348746343,"identity":"d45d66cd-bb69-431d-a1ad-3de168d2edc2","order_by":3,"name":"Yafeng Pan","email":"","orcid":"https://orcid.org/0000-0002-5633-8313","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Yafeng","middleName":"","lastName":"Pan","suffix":""}],"badges":[],"createdAt":"2024-06-27 15:55:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4649720/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4649720/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41539-025-00311-8","type":"published","date":"2025-04-15T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80697996,"identity":"06ff0f94-3fab-41c6-8eba-e871ac57422c","added_by":"auto","created_at":"2025-04-16 07:09:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1072670,"visible":true,"origin":"","legend":"","description":"","filename":"Articlefile.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4649720/v1_covered_16e5d4a4-3794-4270-a436-bb681bc468a7.pdf"}],"financialInterests":"(Not answered)","formattedTitle":"Effects of Different AI-driven Chatbot Feedback on Learning Outcomes and Brain Activity","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-science-of-learning","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjscilearn","sideBox":"Learn more about [npj Science of Learning](http://www.nature.com/npjscilearn/)","snPcode":"41539","submissionUrl":"https://mts-npjscilearn.nature.com/cgi-bin/main.plex","title":"npj Science of Learning","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4649720/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4649720/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Artificial intelligence (AI)-driven chatbots provide instant feedback to support learning. 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