Human and Information Interaction

Assessing Artificial Intelligence Literacy Among Students at Kharazmi University Based on Meta AI Literacy Scale

Document Type : Original Article

Authors

Atena Latifi 1
Mohammad Zerehsaz 2
Ali Azimi 3

1 1. MSc in Knowledge and Information Science, Kharazmi University, Tehran, Iran

2 Department of Knowledge and Information Science, Kharazmi University, Tehran, Iran

3 Kharazmi University

Abstract
Purpose: This study aimed to assess artificial intelligence (AI) literacy among students at Kharazmi University and to examine differences across components, dimensions, educational levels, and fields of study. The study conceptualized AI literacy as a multidimensional competency encompassing not only knowledge and tool use but also self-efficacy, self-management, ethical awareness, and the ability to engage critically with AI systems.
Method: The study employed an applied descriptive survey design. The final sample consisted of 335 undergraduates, master’s, and doctoral students selected through proportional stratified sampling with accessibility considerations. Data were collected using the Meta AI Literacy Scale (MAILS). Because the Persian version had been validated in previous Iranian studies, only qualitative face validity was examined in the present study through feedback on item clarity and comprehensibility. Reliability was assessed using Cronbach’s alpha. Data were analyzed in SPSS 27 using descriptive statistics, one-sample t-test, Friedman test, one-way ANOVA, Tukey post hoc test, and Kruskal–Wallis test.

Findings: The mean overall AI literacy score was 5.83 out of 10 and was significantly above the theoretical midpoint (t = 11.02, p < .001). Seventy-three percent of students were classified at a desirable level. Use and application had the highest mean, whereas creation had the lowest. Significant differences were found among components and dimensions. No significant differences were observed across educational levels; however, AI literacy differed significantly across fields of study, and computer science and engineering students reported the highest scores.

Conclusion: Although students’ perceived AI literacy was generally desirable, the gap between using ready-made tools and creating, evaluating, and solving problems with AI indicates a need for systematic, discipline-sensitive, and ethically grounded education. Future research should combine self-report measures with performance-based, longitudinal, and experimental assessments.

Keywords

Artificial intelligence literacy
Data literacy
Meta AI Literacy Scale
Students
Kharazmi University
Privacy awareness
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Human and Information Interaction
Volume 12, Issue 4
Autumn 2025
Pages 1-21