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Using aggregated AI detector outcomes to eliminate false positives in STEM-student writing.

Jon-Philippe K Hyatt1, Elisa Jayne Bienenstock2, Carla M Firetto3

  • 1College of Integrative Sciences and Arts, Arizona State University, Tempe, Arizona, United States.

Advances in Physiology Education
|March 19, 2025
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Generative artificial intelligence (AI) detectors can help instructors identify AI-written work. Using multiple AI detectors together significantly reduces false positives, improving accuracy in distinguishing student versus AI-generated essays.

Keywords:
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Area of Science:

  • Educational Technology
  • Artificial Intelligence in Education
  • Academic Integrity

Background:

  • Generative artificial intelligence (AI) and large language models are increasingly accessible tools for students.
  • AI-generated writing is nearly indistinguishable from human writing, posing challenges for academic integrity.
  • Instructors currently rely on intuition and AI detection tools to differentiate between student and AI-generated work.

Purpose of the Study:

  • To evaluate the effectiveness of online AI detectors in distinguishing between human- and AI-generated essays in an undergraduate anatomy and physiology course.
  • To compare the accuracy of AI detectors with human raters in identifying the origin of written work.
  • To assess the impact of using AI detectors in aggregate on accuracy and false positive rates.

Main Methods:

  • 190 undergraduate students completed a handwritten essay and an AI-generated essay on the plasma membrane.
  • 50 essays were tested on four AI detectors, and 48 essays were reviewed by nine human raters.
  • Student perceptions of essay quality and AI use were collected via survey.

Main Results:

  • The best-performing AI detectors correctly identified essay origins with 93-98% accuracy, comparable to human raters (84-95%).
  • AI detectors had a lower false positive rate (1.3%) compared to human raters (5.0%).
  • Students generally perceived AI-generated essays as superior to their own (P < 0.01).

Conclusions:

  • AI detectors are valuable tools for instructors to identify AI-generated content.
  • Using AI detectors in aggregate significantly reduces the false positive rate, enhancing reliability.
  • Consensus-based AI detection provides a robust method to support instructors in maintaining academic integrity.