Examining the psychometric characteristics of the artificial intelligence literacy scale in Iranian society

Subject Areas :

zahra Akhavi Samarein ¹ , Saeed Khakdal ² , Maryam ghahremanloo ³

1 - Dept. of Counseling, Faculty of Education and Psychology, Mohaghegh Ardabili University, Ardabil, Iran
2 - family Counselling, M.A
3 - Counseling Department, Faculty of Psychology and Educational Sciences, Mohaghegh Ardabili University, Ardabil, Iran.

Received: 2024-11-03 Accepted : 2025-02-10 Published : 2025-04-17

Keywords: AI literacy, awareness, use, evaluation, and ethics.,

Abstract :

The present study aimed to examine the psychometric properties of the Artificial Intelligence literacy Scale within the Iranian population. The research methodology was descriptive and survey-based. The statistical population included all individuals in Iran in the year 2024 who were over 20 years old and had basic knowledge of computers and artificial intelligence. A sample of 340 individuals (137 men, 203 women) was selected using a convenience sampling method. Data were collected using the Artificial Intelligence literacy Scale Questionnaire of Artificial Intelligence Use Motives (QAIUM), and the Attitude towards Artificial Intelligence Scale – short measure (ATAI). Confirmatory factor analysis results validated four factors for the AI literacy Scale: awareness, use, evaluation, and ethics. Pearson correlation coefficients, used to assess concurrent validity (both convergent and divergent) of the AI literacy Scale, showed significant positive correlations between the subscales of the AI literacy Scale and the subscales of the QAIUM and the acceptance subscale of the ATAI scale, and a significant negative correlation with the fear of AI subscale in the ATAI scale. The internal consistency of the subscales of the AI literacy Scale was confirmed with Cronbach's alpha coefficients ranging from 0.72 to 0.82. Therefore, based on the findings of this study, it can be concluded that the AI literacy Scale possesses appropriate psychometric properties for assessing this construct in a sample of the Iranian population and can be a useful tool for researchers in studies related to AI literacy.

References:

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