AI Cheating and Academic Integrity Session Summary скачать в хорошем качестве

AI Cheating and Academic Integrity Session Summary

This is a summary of an AI Cheating & Academic Integrity session presented by Talia R. Cotton, M.Ed., which examines the growing challenge of generative AI misuse in education and the strategies educators can employ to promote authentic student work. The session defines AI cheating, explores the limits of AI detection tools, and emphasizes instructional design as the most effective defense against academic dishonesty. It frames AI as an integral, transformative presence in classrooms and urges teachers to adapt through thoughtful assessment, AI literacy, and authenticity-centered practices. Key strategies include rethinking assessments to value process and originality, integrating authenticity indicators into rubrics, and embedding course-specific content that AI cannot replicate. Ultimately, educators can detect, understand, and reduce AI misuse not through flawed detectors but by strengthening pedagogy, transparency, and ethical AI use.