AI detection tools work by spotting the subtle differences between human-written and AI-generated content. They analyze text for patterns in language, structure, and phrasing that are often found in machine-generated writing.

Some tools use language models to match text against known AI writing patterns, while others apply machine learning techniques to identify unique writing styles. These approaches allow them to accurately distinguish AI-generated content, even if the specific AI model hasn't been encountered before.

AI detection tools often struggle when tasked with analyzing AI-generated content that has been heavily revised by a human. Once a text undergoes significant editing, it can lose many of the telltale patterns or markers that detection tools rely on, making it much harder to flag as AI-generated.

On top of that, methods like paraphrasing or rewording can make AI-written content seem more natural and closer to something a person might write. This adds another layer of complexity for detection tools, potentially lowering their accuracy. Because of these challenges, it’s best to use such tools as just one piece of a larger approach to verifying content authenticity.

When choosing an AI detection tool for educational use, it's important to weigh factors like accuracy, ease of use, and available features. Accuracy is essential to ensure the tool can reliably spot AI-generated content while minimizing false positives. At the same time, the tool should be straightforward to use and fit smoothly into your workflow.

Pay attention to features such as similarity scores, options for adjusting sensitivity, and detailed content analysis to get a clearer picture of flagged material. Pricing and customer support are also key considerations, particularly for educators or schools working within tight budgets. Keep in mind, no tool is flawless - these tools should complement, not completely replace, your judgment when evaluating originality.