AN EXAMINATION OF THE MOTIVATION OF TURKISH TEACHER CANDIDATES TO USE ARTIFICIAL INTELLIGENCE TOOLS
17th International “Baskent” Congresses on Social, Humanities, Administrative, and Educational Sciences | Congress Proceedings Book, Ankara, Türkiye, 12 - 14 Şubat 2026, ss.868-879, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Basıldığı Şehir: Ankara
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.868-879
- Atatürk Üniversitesi Adresli: Evet
Özet
This study aims to understand Turkish teacher candidates' motivation to use artificial intelligence (AI)
tools, the internal and external factors that fuel this motivation, and the pedagogical context of their use
through participants' experiences. The rapid proliferation of generative AI applications in education
demonstrates that teacher candidates' reasons for turning to these tools are not limited to “convenience”
alone; rather, they are shaped by a multidimensional foundation that includes time management,
workload reduction, support for academic processes, diversification of content production, and
triggering creative thinking. In this context, the research aims to determine which AI tools teacher
candidates use in their daily lives, their reasons for choosing these tools, the perceived added value, their
perceived competence in use, and their motivation for use.
The research was conducted using the phenomenology approach, one of the qualitative research designs.
The study group consisted of 9 teacher candidates studying in the Turkish Language Teaching
Department of Kazım Karabekir Faculty of Education, Atatürk University, in the 2025–2026 academic
year. Data were collected through a semi-structured interview form consisting of five open-ended
questions administered via Google Forms. The data obtained were analyzed using content analysis;
categories were created under the themes of tools used in the coding process, reasons for preference,
perceived added value, perceived adequacy, and sources of motivation. Inter-rater reliability in the
coding process was calculated using Miles and Huberman's formula, and the reliability rate was
determined to be 85%.
The findings showed that participants used AI tools in a multifaceted way and that usage was particularly
concentrated in text-based generative tools such as ChatGPT and Gemini. Functionality and practicality,
along with academic support, stood out as reasons for preference, while the most prominent perceived
added value was determined to be time/workload reduction, accompanied by the dimensions of inspiration and content diversity.
A significant portion of participants described themselves as “partially
proficient,” indicating a need to develop AI literacy. When examining sources of motivation, it was
determined that internal factors such as curiosity and desire to learn were influential, as were external
factors such as time pressure, grade/success expectations, and future anxiety; additionally, guidance
from instructors and peers was found to have a social impact.
The findings show that participants used AI tools in a multifaceted manner, with usage concentrated
particularly on text-based generative tools such as ChatGPT and Gemini. Functionality and practicality,
along with academic support, were highlighted as reasons for preference, while the most significant
perceived added value was identified as time/workload reduction, accompanied by inspiration and
content diversity. A significant portion of participants described themselves as “partially proficient,”
indicating a need for developing AI literacy.