The use of AI in teaching and learning, from tutoring and feedback tools for students to marking, lesson planning and administration for teachers. Supporters see the chance of personal tutoring at scale and lighter workloads; critics worry about cheating, students skipping the thinking that builds skill, unreliable answers and data privacy. Evidence on long-term effects on learning is still limited and mixed.
Technical view
Uses include intelligent tutoring, which predates generative models, automated feedback and assessment, content generation and administration. Generative models complicate assessment, since take-home written work no longer reliably shows a student’s own ability, and AI-text detectors have proved unreliable: a 2023 Stanford study found several misclassified non-native English writing as machine-generated. The European Union’s AI Act treats systems used for admissions, evaluating learning outcomes and monitoring students during tests as high-risk, and bans emotion recognition in educational settings except for medical or safety reasons. Design choices, such as tutors that prompt rather than answer, largely decide whether a tool supports learning or substitutes for it.
Related
Part of AI Terminology Index, section: Society and Impact.