Bildiri: Pre-service Teachers’ Perspectives on AI Detection and Policy Needs

Özet

Being deeply integrated into the education field, it has become crucial to understand AI’s dual structure as a pedagogical tool and language support, along with its complicated nature. Although AI enhances teaching via idea generation, content creation, and lesson planning, the gray area created by the non-existent official guidelines regarding AI has left pre-service teachers with uncertainty regarding its usage range and policies. As a result, the ability to detect and differentiate AI-written and human-written content emerges as a new pedagogical gap.

This study aims to measure pre-service teachers’ perspectives on AI detection and the necessity of policy needs regarding AI. The questionnaire-based study was conducted with the participation of 1st-, 2nd-, 3rd-, and 4th-year students from the English Language Department at the Faculty of Education, Isparta Süleyman Demirel University, and responses were obtained from 72 pre-service teachers. This research was carried out within the scope of the descriptive survey model, one of the quantitative research methods. Data were collected via the Google Forms platform using a questionnaire that included five-point Likert scale items, multiple-choice questions, and open-ended questions to gather in-depth qualitative insights.

Participants responded based on gender, grade level, AI usage history, and their confidence in self AI-detection abilities, the reality of their ability to detect AI, as well as their perspectives on AI policies and policy needs. The findings revealed that although many participants rated their confidence as a 3 or 4 out of 5, they mostly failed to identify the AI origin of the given sample texts. Participants mainly cited the complexity of vocabulary and the absence of personal voice as reasons for labelling a text was AI-written. This mismatch between perception and reality highlights not only the inadequacy in the ability to differentiate texts but also the importance of policy needs in the academic field. Furthermore, when it comes to policies, they often indicate confusion about what they should include, yet pre-service teachers openly support a policy shift to a more transparent, process-based assessment, such as oral defenses rather than a catch-and-punish approach, therefore underlining the importance of AI literacy training and policy frameworks.

Necibe Ebrar DOĞAN, Doç. Dr. Ahmet ÖNAL