Development of Core Competencies for AI-Based Image Information Processing Education

In the era of digital transformation, advancements in artificial intelligence (AI) technologies are accelerating changes in industrial structures and societal systems, making the cultivation of AI-capable talent a national and global priority. In particular, there is a growing demand for competency-based AI education that fosters practical problem-solving skills rather than focusing solely on theoretical knowledge. This study aims to identify and validate the core competencies required for advanced AI education, with a focus on computer vision—a domain characterized by high industrial applicability, interdisciplinary relevance, and accessibility for learners. To achieve this, a comprehensive literature review was conducted, and text mining techniques using TF-IDF were applied to extract key keywords related to AI-based image information processing. Based on this analysis, eight core competencies and 24 detailed competencies were initially derived. A two-round Delphi study involving experts in AI and computer education was then conducted to review and refine these competencies. As a result, eight core competencies and 21 detailed competencies were finalized. These validated competencies span technical, mathematical, communicative, and ethical dimensions, offering a structured and balanced framework for designing AI-intensive curricula. The findings of this study provide practical implications for developing advanced, problem-solving-oriented AI education programs at both secondary and higher education levels. Furthermore, they contribute to the broader effort of nurturing future professionals who can responsibly, creatively, and effectively apply AI technologies in diverse real-world contexts.