Identifying the Dimensions of Artificial Intelligence Literacy and Proposing a Conceptual Framework for Its Instruction: A Systematic Review

Document Type : Research َ Article

Author

Ph.D. in KIS, Department of Knowledge and Information Science, Kharazmi University, Tehran, Iran

10.30484/nastinfo.2025.3833.2341

Abstract

Purpose: In the era of rapidly expanding artificial intelligence (AI) technologies, AI literacy has emerged as a critical necessity of the 21st century. Research emphasizes the importance of equipping citizens- especially non-experts- with the knowledge, skills, and values needed to interact with AI technologies in an informed, effective, and ethical manner. The present study aims to identify the dimensions of AI literacy and to propose a conceptual framework for its Instruction through a systematic review of the literature.
Method: This applied research was conducted using a systematic literature review methodology based on the framework proposed by Kitchenham and Charters. The review process included three main stages: planning the review, conducting the review, and reporting the findings. A citation-based search strategy was applied in the Scopus database to retrieve comprehensive and relevant sources. After applying inclusion and exclusion criteria and validating the sources, 60 full-text studies published between 2020 and 2025 were selected. Reliability checks were conducted to ensure the validity of the extracted codes and their categorization.
Findings: Ten core dimensions of AI literacy were identified: understanding the structure and functioning of AI technologies, practical skills in using AI tools, critical evaluation and interpretation of AI outputs, ethical literacy in AI usage, socio-cultural and political awareness of AI implications, career readiness and professional responsibility in the AI era, computational and algorithmic thinking, inquiry-based learning and research with AI, metacognition and higher-order thinking in AI interaction, and self-efficacy and motivation in engaging with AI. The proposed educational framework is structured into four layers. The first layer, Cognitive-Technical, forms the foundation for users’ technical and theoretical understanding of AI. The second layer, Analytical-Functional, emphasizes practical empowerment through the use of AI tools, problem-solving, and computational thinking. The third layer, Ethical-Social, strengthens cultural awareness, ethical responsibility, and critical sensitivity to algorithmic bias and social consequences. The fourth layer, Metacognitive-Developmental, focuses on self-assessment, lifelong learning, inquiry-driven engagement, career-oriented future thinking, and sustained motivation to adapt to ongoing developments in AI.
Conclusion: The findings indicate that AI literacy is a multidimensional concept that goes beyond technical understanding. Each layer of the proposed framework addresses distinct aspects—from foundational knowledge and practical skills to ethical awareness and self-directed learning. While prior research has addressed these dimensions individually, a cohesive, pedagogically grounded, multilayered, and adaptable framework has been lacking. The proposed model integrates cognitive, functional, ethical, social, metacognitive, and motivational elements and offers adaptability across educational levels, cultural contexts, and professional domains. It serves as both a theoretical foundation and a practical tool for designing AI literacy programs in schools, universities, and public education. This framework supports a more inclusive and future-oriented approach to AI education by addressing the needs of diverse learners. Future studies are recommended to evaluate the framework’s pedagogical impact, develop assessment instruments for each dimension, and explore its effectiveness in various educational systems and learning environments.

Keywords

References

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History

  • Receive Date: 27 June 2025
  • Revise Date: 15 October 2025
  • Accept Date: 31 October 2025
  • Publish Date: 12 May 2026

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