jcer Journal of Computer and Education Research 2148-2896 Tamer KUTLUCA 10.18009/jcer.1757103 Teacher Education and Professional Development of Educators Primary Education Öğretmen Eğitimi ve Eğitimcilerin Mesleki Gelişimi İlköğretim The Relationship between Prospective Classroom Teachers’ Acceptance of Generative Artificial Intelligence and their Ethical Use of Information Technologies The Relationship between Prospective Classroom Teachers’ Acceptance of Generative Artificial Intelligence and their Ethical Use of Information Technologies https://orcid.org/0000-0001-5635-7445 Taşçılar Mustafa HASAN KALYONCU ÜNİVERSİTESİ https://orcid.org/0000-0001-5626-4660 Yaşar Sağlık Zehra HASAN KALYONCU UNIVERSITY Dağdeviren Ayşenur HASAN KALYONCU ÜNİVERSİTESİ 03 30 2026 14 08 02 2025 03 23 2026 Copyright © 2013, Journal of Computer and Education Research 2013 Journal of Computer and Education Research

The rapid integration of generative artificial intelligence (GAI) tools into educational contexts has raised important questions regarding not only technology acceptance but also ethical considerations in technology use. In this context, the present study aims to examine the relationship between pre-service classroom teachers’ levels of ethical use of information and communication technologies (ICT) and their acceptance of generative artificial intelligence. Employing a quantitative correlational research design within the descriptive model, the study was conducted with 337 pre-service classroom teachers selected through convenience sampling from two universities in Gaziantep, Türkiye. Descriptive statistics, Pearson product–moment correlation analysis, and hierarchical multiple regression analysis were used to analyze the data. The results revealed that pre-service classroom teachers demonstrated high levels of both ethical ICT use and acceptance of generative AI. A positive and moderate statistically significant relationship was found between ethical ICT use and generative AI acceptance. More specifically, ethical awareness, communication and respect, and intellectual property dimensions of ethical ICT use were positively associated with generative AI acceptance, whereas the cybercrime dimension was not significantly related. Hierarchical regression analysis showed that ethical ICT use was a significant associated with generative AI acceptance even after controlling for gender, age, grade level, and AI use frequency. Ethical ICT use was significantly associated with generative AI acceptance, with the final model accounting for 25.3% of the total variance. These findings indicate that ethical orientations toward technology are closely associated with pre-service teachers’ openness to and acceptance of emerging AI technologies. This study contributes to the existing literature by empirically demonstrating that ethical ICT use is not merely a complementary skill but a key significantly associated with generative AI acceptance among future classroom teachers.

The rapid integration of generative artificial intelligence (GAI) tools into educational contexts has raised important questions regarding not only technology acceptance but also ethical considerations in technology use. In this context, the present study aims to examine the relationship between pre-service classroom teachers’ levels of ethical use of information and communication technologies (ICT) and their acceptance of generative artificial intelligence. Employing a quantitative correlational research design within the descriptive model, the study was conducted with 337 pre-service classroom teachers selected through convenience sampling from two universities in Gaziantep, Türkiye. Descriptive statistics, Pearson product–moment correlation analysis, and hierarchical multiple regression analysis were used to analyze the data. The results revealed that pre-service classroom teachers demonstrated high levels of both ethical ICT use and acceptance of generative AI. A positive and moderate statistically significant relationship was found between ethical ICT use and generative AI acceptance. More specifically, ethical awareness, communication and respect, and intellectual property dimensions of ethical ICT use were positively associated with generative AI acceptance, whereas the cybercrime dimension was not significantly related. Hierarchical regression analysis showed that ethical ICT use was a significant associated with generative AI acceptance even after controlling for gender, age, grade level, and AI use frequency. Ethical ICT use was significantly associated with generative AI acceptance, with the final model accounting for 25.3% of the total variance. These findings indicate that ethical orientations toward technology are closely associated with pre-service teachers’ openness to and acceptance of emerging AI technologies. This study contributes to the existing literature by empirically demonstrating that ethical ICT use is not merely a complementary skill but a key significantly associated with generative AI acceptance among future classroom teachers.

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