Generative Artificial Intelligence and the Future of Education: A Systematic Review of Trends, Trustworthiness and Technological Evaluation

Generative Artificial Intelligence and the Future of Education: A Systematic Review of Trends, Trustworthiness and Technological Evaluation | 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 Systematic Review Generative Artificial Intelligence and the Future of Education: A Systematic Review of Trends, Trustworthiness and Technological Evaluation Ravidu Suien Rammuni Silva, Ahmad Lotfi, Isibor Kennedy Ihianle, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8248369/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 This systematic review aims to investigate the current landscape of AI in Education (AIEd) through a comprehensive analysis of empirical studies related to AIEd published since 2022 and indexed in the Web of Science. Following the PRISMA 2020 guidelines and using thematic analysis, this study reviews 103 studies selected by one primary researcher based on the defined research questions, with four researchers independently verifying the selection. These research questions focus on the prevalent AIEd technologies, their reliability, evaluation frameworks, and the potential impact of AI in educational contexts, aiming to serve as a roadmap for researchers, developers, educators, and policymakers navigating the rapidly transforming landscape of AIEd. The findings highlight the prominence of classical machine learning models in published studies, while recent Generative AI (GenAI) models, such as Large Language Models (LLMs), have not been comprehensively experimented with, despite their potential. Findings show that studies utilising LLMs typically relied on more general-purpose systems, such as ChatGPT. Recognising these trends and analysing surveys on stakeholder intentions (educators and learners), the review identifies existing gaps in AIEd research, including the absence of adequate evaluation mechanisms, the lack of specialised LLM-based systems, and notable concerns about transparency, trustworthiness, and ethical implications. Based on the identified gaps, predominantly from a technical perspective, the study recommends research on specialised GenAI-based systems, the integration of AI tools into current pedagogical approaches, comprehensive ethics-aware evaluation frameworks, and addressing issues regarding the trustworthiness of AIEd systems. Artificial Intelligence and Machine Learning Educational Philosophy and Theory AI in Education Education Generative AI LLMs in Education Systematic Review (PRISMA) Full Text Additional Declarations The authors declare no competing interests. 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-8248369","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":553285647,"identity":"ecad9de7-eaf4-495b-a0ef-5e7fe23fed27","order_by":0,"name":"Ravidu Suien Rammuni Silva","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-2525-1300","institution":"Nottingham Trent University","correspondingAuthor":true,"prefix":"","firstName":"Ravidu","middleName":"Suien Rammuni","lastName":"Silva","suffix":""},{"id":553285648,"identity":"905e55ea-e26e-4ac0-a6b9-a3a38d3679a9","order_by":1,"name":"Ahmad Lotfi","email":"","orcid":"","institution":"Nottingham Trent University","correspondingAuthor":false,"prefix":"","firstName":"Ahmad","middleName":"","lastName":"Lotfi","suffix":""},{"id":553285649,"identity":"28fe4f91-3335-4c03-91c3-24d3dd7a85d7","order_by":2,"name":"Isibor Kennedy Ihianle","email":"","orcid":"","institution":"Nottingham Trent University","correspondingAuthor":false,"prefix":"","firstName":"Isibor","middleName":"Kennedy","lastName":"Ihianle","suffix":""},{"id":553285650,"identity":"2806602f-5179-4f90-84a0-65650aab3151","order_by":3,"name":"Golnaz Shahtahmassebi","email":"","orcid":"","institution":"Nottingham Trent University","correspondingAuthor":false,"prefix":"","firstName":"Golnaz","middleName":"","lastName":"Shahtahmassebi","suffix":""},{"id":553285651,"identity":"686f99d3-f3ea-4c93-95ed-dfa30b33f204","order_by":4,"name":"Jordan J. Bird","email":"","orcid":"","institution":"Nottingham Trent University","correspondingAuthor":false,"prefix":"","firstName":"Jordan","middleName":"J.","lastName":"Bird","suffix":""}],"badges":[],"createdAt":"2025-12-01 09:11:39","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8248369/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8248369/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97249770,"identity":"fc275608-1d3a-45c5-89f1-bbbf81d334f4","added_by":"auto","created_at":"2025-12-02 13:13:23","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":882014,"visible":true,"origin":"","legend":"","description":"","filename":"LRRavidu.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8248369/v1_covered_2382a21a-edde-40e7-8720-27a98f9d153e.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eGenerative Artificial Intelligence and the Future of Education: A Systematic Review of Trends, Trustworthiness and Technological Evaluation\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Nottingham Trent University","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":"AI in Education, Education, Generative AI, LLMs in Education, Systematic Review (PRISMA)","lastPublishedDoi":"10.21203/rs.3.rs-8248369/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8248369/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis systematic review aims to investigate the current landscape of AI in Education (AIEd) through a comprehensive analysis of empirical studies related to AIEd published since 2022 and indexed in the Web of Science. Following the PRISMA 2020 guidelines and using thematic analysis, this study reviews 103 studies selected by one primary researcher based on the defined research questions, with four researchers independently verifying the selection. These research questions focus on the prevalent AIEd technologies, their reliability, evaluation frameworks, and the potential impact of AI in educational contexts, aiming to serve as a roadmap for researchers, developers, educators, and policymakers navigating the rapidly transforming landscape of AIEd. The findings highlight the prominence of classical machine learning models in published studies, while recent Generative AI (GenAI) models, such as Large Language Models (LLMs), have not been comprehensively experimented with, despite their potential. Findings show that studies utilising LLMs typically relied on more general-purpose systems, such as ChatGPT. Recognising these trends and analysing surveys on stakeholder intentions (educators and learners), the review identifies existing gaps in AIEd research, including the absence of adequate evaluation mechanisms, the lack of specialised LLM-based systems, and notable concerns about transparency, trustworthiness, and ethical implications. Based on the identified gaps, predominantly from a technical perspective, the study recommends research on specialised GenAI-based systems, the integration of AI tools into current pedagogical approaches, comprehensive ethics-aware evaluation frameworks, and addressing issues regarding the trustworthiness of AIEd systems.\u003c/p\u003e","manuscriptTitle":"Generative Artificial Intelligence and the Future of Education: A Systematic Review of Trends, Trustworthiness and Technological Evaluation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 02:46:53","doi":"10.21203/rs.3.rs-8248369/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"98553a76-1ef8-4f94-b1cf-f2617e9d03f4","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58868164,"name":"Artificial Intelligence and Machine Learning"},{"id":58868165,"name":"Educational Philosophy and Theory"}],"tags":[],"updatedAt":"2025-12-02T02:46:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-02 02:46:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8248369","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8248369","identity":"rs-8248369","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}