Publication Ethics

Publication ethics in the context of AI in education is a cornerstone for ensuring the integrity and credibility of research and innovation in this evolving field. Researchers, developers, and educators must adhere to principles such as honesty, transparency, and accountability when publishing findings or deploying AI tools. This includes accurately representing data—whether it’s student outcomes or system performance—avoiding plagiarism, and disclosing any conflicts of interest, such as funding from EdTech companies. Peer review processes should be rigorous and unbiased to validate claims about AI’s educational impact, while proper attribution must be given to all contributors, including datasets or algorithms adapted from others. Additionally, ethical considerations extend to respecting participant privacy, especially when studies involve sensitive student data, requiring informed consent and anonymization. By upholding these standards, the academic and professional community can foster trust and advance future perspectives on AI in education responsibly.