Educational Priorities of Iranian Knowledge Organization Practitioners

Abstract

Purpose:Knowledge organization is a socio-cultural process through which knowledge produced in scientific, professional, and cultural communities is systematically structured, classified, indexed, and made accessible. This study aims to identify and prioritize the educational needs of knowledge organization practitioners in Iran, enabling the Knowledge Organization Committee of the Iranian Library and Information Science Association to design targeted training programs based on criteria such as academic discipline, degree level, occupation, and type of employing institution.

Methodology:This applied research employs a descriptive-survey design.Data were collected via a researcher-developed questionnaire. Content validity was established through the expert judgment of five specialists in knowledge organization, and reliability was confirmed using Cronbach’s alpha coefficient.The online questionnaire was disseminated through email groups and social media networks of the Iranian Library and Information Science community.No formal sampling method was applied; thus, all 140 respondents participated voluntarily. Data were analyzed using inferential statistics in SPSS.

Findings:“Artificial intelligence and emerging technologies related to knowledge organization” emerged as the highest overall training priority. This preference was particularly pronounced among students, library staff, individuals with degrees in Library and Information Science (LIS), and those holding associate, master’s, or doctoral degrees. In contrast, faculty members and library managers prioritized knowledge organization software and integrated library systems. At the bachelor’s level, programming languages and extensible markup languages (e.g., XML) were identified as the primary educational need.

Conclusion and: The findings indicate a fundamental shift in educational demands—from traditional competencies toward digital, data-driven, and future-oriented skills in knowledge organization. The study recommends revising both formal and in-service training curricula and implementing specialized courses in artificial intelligence, knowledge organization software, programming, and machine learning, aligned with international knowledge organization standards. Additionally, adopting flexible training models can effectively address the diverse organizational needs of practitioners and better prepare them for evolving roles in a knowledge-based society.