Hacettepe Üniversitesi Eğitim Fakültesi Dergisi 2536-4758 Hacettepe Üniversitesi 10.16986/hunefd.1774522 Other Fields of Education (Other) Alan Eğitimleri (Diğer) Üniversite Öğrencilerinde Yapay Zekâ Okuryazarlığı, Yapay Zekâya Yönelik Tutumlar ve Teknostres Arasındaki İlişkinin İncelenmesi Examining the Relationship Between Artificial Intelligence Literacy, Attitudes Toward Artificial Intelligence, and Technostress Among University Students https://orcid.org/0000-0001-7754-2594 Özbay Özkan ARTVİN ÇORUH ÜNİVERSİTESİ, UZAKTAN EĞİTİM UYGULAMA VE ARAŞTIRMA MERKEZİ 04 30 2026 41 2 426 439 08 30 2025 01 05 2026 Copyright © 1986, Hacettepe Üniversitesi Eğitim Fakültesi Dergisi 1986 Hacettepe Üniversitesi Eğitim Fakültesi Dergisi

Yapay zekâ (YZ) teknolojileri, öğrencilerin öğrenme süreçlerini ve dijital deneyimlerini etkileyerek eğitim ortamlarına hızla nüfuz etmiştir. Bu çalışmanın amacı, lisans öğrencilerinde yapay zekâ okuryazarlığı, yapay zekâya yönelik tutumlar ve teknostres arasındaki ilişkileri incelemektir. Araştırmada kesitsel, betimsel ve ilişkisel bir desen kullanılmıştır. Veriler, Haziran 2025’te Artvin Çoruh Üniversitesi Sağlık Bilimleri, Eğitim, Fen-Edebiyat ve Mühendislik fakültelerinde öğrenim gören 400 lisans öğrencisinden toplanmıştır. Veri toplama araçları Sosyodemografik Bilgi Formu, Yapay Zekâ Okuryazarlığı Ölçeği (AILS), Yapay Zekâya Yönelik Genel Tutumlar Ölçeği (GAAIS) ve Teknostres Ölçeği’nden oluşmaktadır. Verilerin analizinde SPSS 26.0 programı kullanılarak betimsel istatistikler, Pearson korelasyon analizi ve çoklu regresyon analizi uygulanmıştır. Elde edilen bulgular, yapay zekâya yönelik olumlu tutumların yapay zekâ okuryazarlığı ile anlamlı ve pozitif yönde ilişkili olduğunu; teknostresin ise hem olumlu tutumlar hem de yapay zekâ okuryazarlığının değerlendirme alt boyutu ile negatif yönde ilişkiler gösterdiğini ortaya koymuştur. Regresyon analizi sonuçları, akademik başarı (GNO), bilişim teknolojileri yeterliği ve olumlu tutumların yapay zekâ okuryazarlığının anlamlı yordayıcıları olduğunu; olumsuz tutumların ise yapay zekâ okuryazarlığı üzerinde azaltıcı bir etki gösterdiğini ortaya koymuştur. Buna karşın, teknostres anlamlı bir yordayıcı olarak belirlenmemiştir. Bu bulgular, yükseköğretimde yapay zekâ entegrasyonunun çok boyutlu doğasına işaret etmektedir. Çalışmanın sonuçları, yapay zekâ okuryazarlığının artırılmasının yalnızca teknik yeterliklerin gelişimiyle değil, aynı zamanda daha olumlu algıların oluşması ve teknolojiye bağlı stresin azalmasıyla da ilişkili olduğunu göstermektedir. Bu doğrultuda, eğitsel stratejilerin öğrencilerin yapay zekâ okuryazarlığını güçlendirmeye, dengeli ve bilinçli tutumlar geliştirmeye ve teknostresle başa çıkmalarını destekleyecek baş etme mekanizmaları kazandırmaya odaklanması önerilmektedir. Bu çalışma, dijital çağda öğrencilerin uyumunu ve akademik başarısını desteklemek amacıyla yapay zekâ eğitimine bilişsel, duyuşsal ve psikolojik boyutların entegre edilmesinin önemini vurgulayarak alanyazına katkı sağlamayı amaçlamaktadır.

Artificial intelligence (AI) technologies have rapidly permeated educational contexts, influencing students’ learning processes and digital experiences. This study aimed to examine the interrelationships among AI literacy, attitudes toward AI, and technostress in undergraduate students. A cross-sectional, descriptive, and correlational design was employed. Data were collected in June 2025 from 400 undergraduate students enrolled in the Faculties of Health Sciences, Education, Arts and Sciences, and Engineering at Artvin Çoruh University. Data collection instruments included a Sociodemographic Information Form, the Artificial Intelligence Literacy Scale (AILS), the General Attitudes Toward Artificial Intelligence Scale (GAAIS), and the Technostress Scale. Descriptive statistics, Pearson’s correlation, and multiple regression analyses were conducted using SPSS 26.0. The results indicated that positive attitudes toward AI were significantly and positively correlated with AI literacy, whereas technostress showed negative associations with both positive attitudes and the evaluation subdimension of AI literacy. Regression analysis further revealed that academic achievement (GPA), IT competence, and positive attitudes were significant predictors of AI literacy, while negative attitudes exerted a diminishing effect. Technostress, however, did not emerge as a significant predictor. These findings highlight the multifaceted nature of AI integration in higher education. The findings of this study indicate that enhancing AI literacy is associated not only with improved technical competence but also with more positive perceptions and reduced technology-related stress. Educational strategies should therefore focus on strengthening students’ AI literacy, promoting balanced and informed attitudes, and equipping learners with coping mechanisms to manage technostress. This study aims to contribute to the growing body of literature by emphasizing the importance of integrating cognitive, emotional, and psychological dimensions into AI education to support students’ adaptation and academic success in the digital era.

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