With the advent of ChatGPT and other AI chatbots, educators are turning to AI detectors to verify the authenticity of student work. These detectors are designed to identify instances where students might have used AI to complete their assignments. However, concerns have been raised as these detectors sometimes produce false positives, incorrectly flagging student work as AI-generated even when it’s not. This issue appears to be more prevalent among non-native English speakers.
To combat AI cheating, some instructors are exploring a new method inspired by criminal investigations—linguistic fingerprinting. This technique leverages linguistic analysis to determine if a text was written by a specific individual based on their unique writing style. Mike Kentz, an English teacher at Benedictine Military School in Georgia, is at the forefront of implementing this approach in education.
On this week’s EdSurge Podcast episode, Kentz discusses the benefits and drawbacks of linguistic fingerprinting in addressing AI cheating in academics. By adopting this approach, educators aim to proactively safeguard academic integrity and promote originality in student work.
For the full conversation and insights, listen to the podcast episode on Apple Podcasts or Spotify.
EdSurge: What is linguistic fingerprinting?
Mike Kentz: Linguistic fingerprinting involves analyzing an individual’s writing style to establish a unique “writing fingerprint.” This method helps to identify the author of a text based on their specific patterns and language preferences.
How is it being used in education?
In educational settings, linguistic fingerprinting is utilized to compare a student’s current work with their known writing samples. By assessing linguistic features such as syntax, word choice, and lexical density, educators can determine the likelihood of a match between the author’s fingerprints.
Challenges and Future Outlook
While linguistic fingerprinting shows promise in combating AI cheating, there are concerns regarding its accuracy and potential impact on trust within the classroom. As educators navigate the evolving landscape of technology in learning environments, discussions around AI literacy and assessment strategies are crucial for maintaining academic integrity.
Listen to the full podcast episode on EdSurge to delve deeper into the realm of linguistic fingerprinting and its role in addressing academic integrity challenges in the age of AI.
