Academic Integrity Monitor
Comprehensive tools to monitor and analyze student submissions for academic integrity
Overall Accuracy
Based on our comprehensive testing across diverse writing samples
94.8%
False Positive Rate
Industry-leading low rate of incorrectly flagging human content as AI-generated
3.2%
Continuous Improvement
Accuracy improvement in the last quarter through model refinement
+1.2%
AI Detection Accuracy Comparison
Comparing StudentAIDetector to other AI detection systems
| System | Accuracy (%) | False Positive Rate (%) |
|---|---|---|
| StudentAIDetector | 94.8 | 3.2 |
| Alternative A | 54.2 | 8.1 |
| Alternative B | 50.1 | 10.5 |
Our Methodology
An overview of our AI detection process
StudentAIDetector uses a multi-layered approach to identify AI-generated content. Our system analyzes linguistic patterns, sentence structures, and statistical features that differentiate AI-generated text from human writing. We continuously update our algorithms to stay ahead of evolving AI technology.
Addressing False Positives
Our commitment to reducing false positives, especially for non-native English writers and neurodiverse students
We employ several features to minimize false positives, including sensitivity settings, detailed reports with highlighted sections, and a focus on identifying patterns rather than individual words or phrases.