Do teachers spot AI? Evaluating the detectability of AI-generated texts among student essays - Johanna Fleckenstein; Jennifer Meyer; Thorben Jansen; Stefan D. Keller; Olaf Köller; Jens Möller (Computers and Education: Artificial Intelligence, 2024)
The potential application of generative artificial intelligence (AI) in schools and universities poses great challenges, especially for the assessment of students’ texts. Previous research has shown that people generally have difficulty distinguishing AI-generated from human-written texts; however, the ability of teachers to identify an AI-generated text among student essays has not yet been investigated. Here we show in two experimental studies that novice (N = 89) and experienced teachers (N = 200) could not identify texts generated by ChatGPT among student-written texts. However, there are some indications that more experienced teachers made more differentiated and more accurate judgments. Furthermore, both groups were overconfident in their judgments. Effects of real and assumed source on quality assessment were heterogeneous. Our findings demonstrate that with relatively little prompting, current AI can generate texts that are not detectable for teachers, which poses a challenge to schools and universities in grading student essays. Our study provides empirical evidence for the current debate regarding exam strategies in schools and universities in light of the latest technological developments.