TY  - JOUR
T1  - Üniversite Öğrencilerinin Yapay Zekâ Kullanım Düzeylerinin Belirlenmesi
TT  - Assessing Artıfıcıal Intellıgence Usage Levels Among Unıversıty Students
AU  - Çatman, Fatma Nur
AU  - Topsakal, Eda
AU  - Saatçioğlu, Özkan
PY  - 2025
DA  - November
Y2  - 2025
JF  - Necmettin Erbakan Üniversitesi Ereğli Eğitim Fakültesi Dergisi
JO  - NEEEF
PB  - Necmettin Erbakan Üniversitesi
WT  - DergiPark
SN  - 2687-1831
SP  - 317
EP  - 347
VL  - 7
IS  - Özel Sayı
LA  - tr
AB  - Bu araştırmada üniversite öğrencilerinin yapay zekâ kullanım düzeyleri farklı değişkenler açısından incelenerek mevcut durumun ortaya konulması amaçlanmıştır. Araştırmaya, Türkiye’deki üniversitelerde lisans, pedagojik formasyon, yüksek lisans ve doktora düzeyinde öğrenim gören 1402 öğrenci katılmıştır. Veri toplama sürecinde araştırmacılar tarafından geliştirilen kişisel bilgi formu ve anket kullanılmıştır. Google Form üzerinden elde edilen veriler, IBM SPSS 28.0 ve JASP istatistik programları kullanılarak analiz edilmiştir. Katılımcıların demografik özellikleri frekans ve yüzde dağılımlarıyla özetlenmiş, hipotezler ise ki-kare analizi ile test edilmiştir. Bulgulara göre öğrencilerin büyük çoğunluğu bilgi teknolojilerini ve yapay zekâyı orta ve üzeri düzeyde kullandığını belirtmiştir. Yapay zekâya yönelik ilginin ve öğrencilerin kullanım sıklığının ise yine orta düzeyin üzerinde olduğu ifade edilmiştir. Araştırmada erkek öğrencilerin yapay zekâya yönelik ilgi ve kullanım düzeylerinin kadınlara göre anlamlı şekilde daha yüksek olduğu bulunmuştur. Ancak öğrenme süresi ve kullanım sıklığında cinsiyetler arasında fark görülmemiştir. Ayrıca Mühendislik ve Sağlık Bilimleri Fakültelerindeki öğrencilerin yapay zekâ kullanımı “iyi” düzeyde, Eğitim, Fen-Edebiyat ve Hukuk Fakültelerindeki öğrencilerde ise “orta” düzeyde yaygınlaşmış ve fakülteler arasında anlamlı farklılık bulunmuştur. Öte yandan sınıf düzeyi yükseldikçe yapay zekâya yönelik ilgi ve kullanım düzeyinin arttığı belirtilmiştir. Yaş açısından ise genç öğrencilerin daha sık yapay zekâ kullandıkları, yaşça büyük öğrencilerin ise bilgi teknolojisi becerilerinde üstünlük olduğu belirlenmiştir. Son olarak akademik başarı ile yapay zekâ kullanım sıklığı arasında ilişki saptanmış ve yapay zekâyı sıklıkla kullanan öğencilerin akademik ortalamalarının daha yüksek olduğu ortaya konulmuştur. Bu sonuçlara göre öğrencilerin yapay zekâya yönelik tutum ve davranışlarının demografik ve akademik faktörlerden etkilendiği anlaşılmıştır. Bu bağlamda fakülte bazlı dijital yeterlik programlarının oluşturulması, cinsiyet, yaş gibi farklı değişkenlere yönelik destek mekanizmalarının geliştirilmesi ve öğrencilerin yapay zekâ teknolojilerini bilinçli, etik ve etkili kullanmalarının sağlanması önerilmiştir.
KW  - Yapay zeka
KW  - Üniversite öğrencileri
KW  - Yapay zeka kullanım düzeyi
KW  - Dijital yeterlik
N2  - This study aims to examine the artificial intelligence (AI) usage levels of university students in terms of various variables to reveal the current situation. The research involved 1,402 students enrolled in undergraduate, pedagogical formation, master's, and doctorate programs at universities in Türkiye. A personal information form and a survey developed by the researchers were used for data collection. Data obtained via Google Forms were analyzed using IBM SPSS 28.0 and JASP statistical software. Participants' demographic characteristics were summarized using frequency and percentage distributions, and hypotheses were tested with chi-square analysis. Findings indicate that a large majority of students reported using information technologies and AI at a medium or high level. Interest in AI and the frequency of its use were also stated to be above the medium level. The study found that male students had a significantly higher level of interest and usage in AI compared to females. However, no gender difference was observed in the learning period or frequency of use. Furthermore, AI usage was prevalent at a "good" level among students in Engineering and Health Sciences faculties, while it was at a "medium" level in Education, Arts and Sciences, and Law faculties, with a significant difference observed between faculties. Moreover, as the class level increased, so did the interest and usage levels of AI. In terms of age, younger students were found to use AI more frequently, while older students demonstrated superior information technology skills. Finally, a relationship was identified between academic achievement and the frequency of AI use, revealing that students who frequently use AI had higher grade point averages. These results suggest that students' attitudes and behaviors toward AI are influenced by demographic and academic factors. In this context, recommendations include establishing faculty-specific digital competency programs, developing support mechanisms for different variables such as gender and age, and ensuring students use AI technologies consciously, ethically, and effectively.
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