عنوان مقاله English
نویسندگان English
Objective: This conceptual, design-oriented study seeks to define what “artificial intelligence literacy” entails for academic librarians in Iran. It aims to determine how this literacy can be conceptualized, assessed, and effectively taught, specifically considering the challenges of constrained access environments.
Method: The study utilized a non-empirical, design-based approach consisting of three analytical phases: 1. Comparative Analysis: Evaluation of six existing international competency frameworks; 2. Narrative Synthesis: A structured review of empirical studies on librarian competencies published between 2020 and 2026; and 3. Design-Based Construction: Development of a comprehensive framework (the “Simorgh” framework), an assessment instrument, a curriculum, and an implementation roadmap.
Results: The analysis reveals that while existing frameworks converge on four competency clusters knowledge, evaluation, application, and ethics they systematically overlook two capabilities critical to constrained settings: pedagogical capability (the ability to teach others) and infrastructural capability (the ability to work productively when access is restricted or unstable).
The proposed “Simorgh” framework integrates these missing dimensions, resulting in six total domains spanning three proficiency levels and eighteen competency blocks with role-differentiated targets.
Conclusions: The study provides a complete toolkit for implementation, including a behaviorally anchored self-assessment instrument, a computable gap index, a 62-hour, four tier curriculum, and a 24-month national roadmap, alongside the necessary validation protocols. Ultimately, the study argues that AI literacy in libraries should be viewed as a distributed institutional capability rather than merely an individual attribute.
کلیدواژهها English
