A study conducted at Koç University School of Nursing examined university students’ perceived self-efficacy in using artificial intelligence technologies. Led by Assoc. Prof. Remziye Semerci Şahin and Asst. Prof. Seda Güney, the researchers adapted the Artificial Intelligence Self-Efficacy Scale (AISES) into Turkish and evaluated its psychometric properties. The study was published in the peer-reviewed International Journal of Human–Computer Interaction.
Artificial intelligence technologies are becoming increasingly prominent in higher education. Adaptive learning platforms, intelligent tutoring systems, and automated feedback tools are now widely used in university education. Alongside this transformation, attention has shifted not only to students’ use of AI tools but also to their confidence in their ability to interact effectively with these systems.
AI self-efficacy refers to students’ confidence in their ability to use and adapt to artificial intelligence technologies effectively. The researchers note that although several scale adaptation studies have been conducted in Türkiye in areas such as AI literacy, AI anxiety, and AI acceptance, validated AI self-efficacy scales focusing specifically on university students and educational settings remain limited. The study therefore aimed to provide a reliable and valid Turkish measurement tool for assessing AI self-efficacy among university students.
The study was conducted between May and November 2025 with 284 students enrolled at public and private universities across different regions of Türkiye. Participants completed an online survey. During the adaptation process, the scale was first translated from English into Turkish, and its linguistic equivalence was evaluated through back-translation. Content validity was then assessed based on expert evaluations, followed by a pilot study.
The analyses supported a four-factor structure comprising “Assistance,” “Anthropomorphic Interaction,” “Comfort with AI,” and “Technological Skills.” This structure explained 73.69% of the total variance, while the scale demonstrated excellent internal consistency, with a Cronbach’s alpha value of 0.937. According to the researchers, these findings indicate that the Turkish version of AISES has strong validity and reliability for measuring AI self-efficacy among university students.
Most participants reported having previously used artificial intelligence technologies, but only a small proportion had received formal or online education related to AI. Nevertheless, the majority expressed an interest in receiving AI-related education. Approximately half assessed their level of AI knowledge as moderate, while a high proportion considered AI useful in their daily lives.
The study also emphasizes that AI self-efficacy is not limited to technical skills. It is also associated with students’ comfort, confidence, and emotional experiences when interacting with AI systems. The findings highlight the importance of developing structured AI literacy programs at universities to prepare students for AI-supported learning environments.
According to the researchers, the Turkish AISES could be used in future educational research to assess students’ AI self-efficacy, evaluate the impact of educational interventions, and monitor changes over time. The study also suggests that integrating AI technologies into education requires attention not only to students’ technical knowledge but also to their confidence and experiences when interacting with these technologies.