Algoritmik Medya İçerik Farkındalık (AMİF) Ölçeğinin Türkçe Versiyonunun Psikometrik Özellikleri

Year 2024, Volume: 5 Issue: 1, 171 - 191, 30.06.2024

Nehir Yasan Ak , Tuğba Kamalı Arslantaş

https://doi.org/10.52911/itall.1447270

Abstract

Hızlı teknolojik gelişmelerle birlikte, kullanıcıların özellikle algoritmik farkındalık alanında yeni beceriler kazanmalarına duyulan ihtiyaç giderek artmaktadır. Bu çalışma, Zarouali ve arkadaşlarının (2021) geliştirdiği Algoritmik Medya İçerik Farkındalık Ölçeği'nin (AMİF) Türkçeye uyarlanmasını ve geçerlik ile güvenirliğinin test edilmesini hedeflemektedir. Orijinal ölçek, İngilizce olarak 13 madde ve dört faktör içeren 5’li Likert tipi bir ölçektir. Araştırmaya, 2022-2023 bahar döneminde, kolay örnekleme yöntemiyle seçilen bir devlet üniversitesinin çeşitli fakültelerinden 414 lisans öğrencisi katılmıştır. Ölçeğin yapısal geçerliliğini belirlemek için doğrulayıcı faktör analizi (DFA) kullanılmış, güvenilirliğini testip etmek için ise Cronbach alfa değerleri kontrol edilmiştir. DFA sonuçları, dört faktörlü yapının iyi bir model uyumu sergilediğini göstermiştir (χ2/df = 2.902, CFI = .95, GFI = .939, TLI = .93, RMR = .035, SRMR = .047, RMSEA = .068). Güvenilirlik katsayıları, faktörlerde .74 ile .81 arasında değişirken, genel alpha .90 olarak yüksek bir güvenilirlik göstermiştir. Madde-toplam korelasyon analizi, tüm maddelerin ölçeğe önemli bir katkıda bulunduğunu göstermiştir. Ayrıca hem yakınsak hem de ayırıcı geçerlilik yeterli düzeydedir. Sonuç olarak, Türkçe AMİF ölçeği, lisans öğrencilerinin algoritmik okuryazarlığını ölçmede geçerli ve güvenilir bir araçtır ve medya okuryazarlığı araştırmalarına da katkı sunma potansiyeli vardır.

Keywords

Algoritmalar, Algoritmik farkındalık, Ölçek uyarlama, Ölçek doğrulama

Ethical Statement

3 Şubat 2023 tarihinde Etik Kurul İzni alınmıştır.

Supporting Institution

Akdeniz Üniversitesi

Project Number

571441

Thanks

Doç. Dr. Tuba Livberber'e değerli katkılarından dolayı teşekkür ederiz.

Psychometric Properties of the Turkish Version of the Algorithmic Media Content Awareness (AMCA) Scale

Abstract

Given the rapid technological advancements, there is an increasing need for users to acquire new skills, particularly in the realm of algorithmic awareness. This study aims to adapt and validate the Algorithmic Media Content Awareness Scale (AMCA), developed by Zarouali et al. (2021), to Turkish context and to test its validity and reliability. The original scale is a 5-point Likert type measure consisting of 13 items with four factors in English. Participants included 414 undergraduate students from various faculties of a state university in Türkiye, selected through convenience sampling during the spring term of 2022-2023. The study employed confirmatory factor analysis (CFA) to assess the scale's construct validity and utilized Cronbach's alpha to examine reliability. The CFA results revealed a good model fit for the proposed four-factor structure (χ2/df = 2.902, CFI = .95, GFI = .939, TLI =.93, RMR = .035, SRMR = .047, RMSEA = .068). Reliability coefficients ranged from .74 to. 81 across the factors, with an overall alpha of .90, indicating high reliability. The item-total correlation analysis revealed that all items significantly contributed to the measure. Additionally, both convergent and discriminant validity were found to be satisfactory. Consequently, all evidence suggests that the Turkish version of the AMCA scale is a valid and reliable tool for assessing algorithmic literacy among undergraduate students, contributing significantly to the field of media literacy research.

Keywords

Algorithms, algorithmic awareness, Scale adaptation, Scale validation

Ethical Statement

Ethical Committee approval was obtained on February 3, 2023.

Supporting Institution

Akdeniz University

Project Number

571441

Thanks

We would like to thank Assoc. Prof. Dr. Tuba Livberber for her valuable contributions.

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