MANAGING THE DEVELOPMENT OF LECTURERS' ARTIFICIAL INTELLIGENCE COMPETENCE IN DISTANCE EDUCATION

Abstract

This study aims to establish a scientific basis and propose management directions for developing lecturers' artificial intelligence (AI) proficiency in distance education, thereby meeting the demands of educational innovation and digital transformation in higher education. It addresses a research gap: while existing literature largely focuses on digital literacy, AI proficiency, and the application of technology in teaching, the management of this specific competency development among lecturers in distance education environments has not yet been systematically studied. The study employs document analysis and synthesis combined with expert consultations to identify relevant competency components and management aspects. The findings reveal that lecturers' AI proficiency comprises six components and identify six key management areas: defining competency standards, assessing needs, planning development, organizing training, establishing a supportive environment, and evaluating outcomes. Based on these findings, the study proposes a management model based on a cycle linking competency standards, professional development, practical support, and evaluation. These results offer valuable insights for higher education institutions and distance education providers in formulating policies, training programs, and support mechanisms to enable lecturers to use AI effectively and responsibly.