A Conceptual Framework for Ethical Issues and their Relationships in the Use of LLMs in Education: Focusing on the Privacy Dimension

A Conceptual Framework for Ethical Issues and their Relationships in the Use of LLMs in Education: Focusing on the Privacy Dimension | 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 A Conceptual Framework for Ethical Issues and their Relationships in the Use of LLMs in Education: Focusing on the Privacy Dimension Wiem Hammami This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8443740/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 Generative Artificial Intelligence (Gen AI) technologies are widely adopted and used by both students and educational institutions that integrate them into their curricula. Large Language Models (LLMs) have become an integral part of student learning. In this context, many ethical problems concerning the sustainable use of LLMs and their impact on learning outcomes arise. This situation leads to the paramount need to systematically investigate a set of ethical criteria to derive the greatest benefit while mitigating associated risks. This paper undertakes an analysis of the existing frameworks and identifies how and why the main ethical concerns are related regarding the deployment of LLMs in educational settings. In this study, we propose a conceptual framework for analyzing and evaluating the relationships between ethical concerns related to the use of LLMs in education. The proposed framework is considered a starting point for comprehensive and measurable ethical aspects that guide institutions and policymakers in mitigating unique risks while exploiting the benefits of LLMs. The findings highlight the need to consider the interconnections among ethical implications to ultimately contribute to the more responsible integration of LLMs in education. Generative Artificial Intelligence Large Language Models Education Ethical criteria Conceptual framework Ethical relationships 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-8443740","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":565255693,"identity":"f2c993ed-d053-44eb-9f67-e6f1a17cd7c6","order_by":0,"name":"Wiem 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