An intelligent tutoring system is software that adapts teaching materials to a learner’s progress, answers, and errors. It may choose the next exercise, adjust difficulty, and interpret free-form responses to estimate what the learner understands. In security terms, it is a decision-support system that often collects detailed behavioral data, so the risks are not only educational accuracy but also privacy, access control, and data retention.
These systems matter in cyber security because they can be targeted through manipulated input, especially when they use natural language models to read student explanations. Crafted text can confuse the learner model, produce false assessments, or trigger unsafe outputs, a form of prompt injection or model abuse. Defenders reduce risk with human review, least-privilege access, audit logs, data minimization, and clear rollback paths. In classrooms, the safest role is advisory: the system supports teachers, but people should remain responsible for final judgments.