<p>This study investigated the prevalence and patterns of AIgiarism in academic assignments among education faculty students. The study aimed to (1) identify a suitable AI detection tool for Turkish, (2) determine AI usage rates in students’ academic assignments, and (3) explore the relationship between students’ AI usage levels, grade point averages (GPAs), and their grades in the Ethics and Morality in Education course. The study employed a quantitative approach that included naturalistic homework data and the percentage of detection tools with a sample of 162 senior-year education faculty students. Various AI detection tools were compared to assess their reliability in detecting AI-generated content in Turkish. According to the results of the determined detection tool, 79.6% of students used AI in their assignments, and 26.6% submitted assignments with 50% or more AI-generated content. Results showed that students with lower academic performance were more likely to rely on AI tools. Additionally, students who received high grades in the Ethics and Morality in Education course exhibited significantly lower AI usage rates. These findings underscore the increasing usage of AI in academic settings and highlight the need for institutional policies to promote ethical AI use, improve academic integrity awareness, and implement more reliable AI detection methods. Due to the evolution of detection tool algorithms, the findings of the study have limitations to the specific context and time period in which it was conducted.</p>

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Redefining academic integrity: patterns of assignment cheating with generative AI tools

  • Yasemin KAHYAOĞLU ERDOĞMUŞ,
  • Sebahat Sevgi UYGUR

摘要

This study investigated the prevalence and patterns of AIgiarism in academic assignments among education faculty students. The study aimed to (1) identify a suitable AI detection tool for Turkish, (2) determine AI usage rates in students’ academic assignments, and (3) explore the relationship between students’ AI usage levels, grade point averages (GPAs), and their grades in the Ethics and Morality in Education course. The study employed a quantitative approach that included naturalistic homework data and the percentage of detection tools with a sample of 162 senior-year education faculty students. Various AI detection tools were compared to assess their reliability in detecting AI-generated content in Turkish. According to the results of the determined detection tool, 79.6% of students used AI in their assignments, and 26.6% submitted assignments with 50% or more AI-generated content. Results showed that students with lower academic performance were more likely to rely on AI tools. Additionally, students who received high grades in the Ethics and Morality in Education course exhibited significantly lower AI usage rates. These findings underscore the increasing usage of AI in academic settings and highlight the need for institutional policies to promote ethical AI use, improve academic integrity awareness, and implement more reliable AI detection methods. Due to the evolution of detection tool algorithms, the findings of the study have limitations to the specific context and time period in which it was conducted.