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.