KJCKorea
Journal Central

The purpose of this study is to examine how audience perceptions were constructed and transformed within Korean dance criticism during the 1990s. Using a qualitative literature analysis, this study investigates dance criticism texts published in Munye Yeongam, Choom, and Yesul Segye between 1990 and 1999. The findings indicate that audiences were initially regarded as passive recipients who confirmed the aesthetic value and communicative effects of performances. However, with the expansion of dance popularization, audience development, and experimental performance practices, audiences gradually came to be recognized as active participants in performance experience and meaning-making processes. This shift reflects a broader transformation in Korean dance criticism from formal and aesthetic evaluation toward social, cultural, and communicative perspectives. The study suggests that the repositioning of audiences in dance criticism provided an important foundation for later discussions on audience participation and audience literacy in Korean dance discourse.

This study analyzes the research trends in dance participation among middle-aged adults and explores the potential for expanding the discourse on pre-seniors within the context of life cycle changes. A systematic literature review was conducted on 45 studies published in Korean academic journals between 2010 and March 2026. The studies were analyzed according to research period, participants, methodologies, and research topics. The findings showed that research increased after 2015, focusingmainly on women and broadly defined middle-aged groups. In addition, research trends expanded from quantitative approaches toward qualitative and interdisciplinary perspectives. These findings suggest the need for more differentiated research that reflects the characteristics and cultural participation patterns of pre-seniors.

This study develops a blended dance teaching-learning model that integrates AI and human instructors through the K-Dance AI Lab platform. Unlike previous studies focused mainly on movement analysis or creative support, this study emphasizes interaction among learners, teachers, and AI. The model combines AI-based quantitative analysis with teachers’ artistic judgment, grounded in blended learning, human-AI collaboration, and dual dance assessment. K-Dance AI Lab integrates Google MediaPipe Pose analysis, large language model-based feedback, persona prompts, reference movement content, and a web-based interface for video recording and visualization. Based on this platform, the study proposes a five-stage model: preparation and design, offline learning, AI analysis and feedback, collaborative assessment, and online enrichment. Its key feature is a dual evaluation assessment that balances AI-generated data with teachers’ qualitative judgment. This study positions AI as a collaborative medium in dance education and suggests its applicability across diverse instructional contexts.