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Navigating Ethical Complexities in Educational AI: A Systematic Review of Generative Chatbot Integration in Teaching and Learning

Jul 2026 · F1000Research · 0 citations · 32 references

TL;DR

The review highlights the need for transparent institutional policies, educator training, ethical AI literacy, strong data governance frameworks, and equitable digital infrastructure to support the responsible, ethical, and inclusive integration of generative AI technologies in education.

Abstract

This systematic literature review examines the ethical challenges associated with integrating generative chatbots in educational contexts. Guided by the PRISMA 2020 framework, the review synthesised peer-reviewed empirical and theoretical studies published between 2022 and 2025 and retrieved from Scopus and Web of Science. Following systematic screening and eligibility assessment, 16 studies were included in the final synthesis. The findings identified four primary ethical domains: student data privacy and protection; academic integrity and AI-assisted plagiarism; algorithmic bias and fairness; and institutional governance and policy readiness. While generative chatbots offer significant pedagogical benefits, including personalised learning, enhanced feedback, and expanded access to educational support, their unregulated use may exacerbate digital inequalities, compromise educational integrity, and reinforce existing biases. The review highlights the need for transparent institutional policies, educator training, ethical AI literacy, strong data governance frameworks, and equitable digital infrastructure. These measures are essential to support the responsible, ethical, and inclusive integration of generative AI technologies in education.

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