Perceptions of “Sports for All” Instructor Competence in the Republic of Korea: A Big Data Analysis Approach

Background: This study examined the perceptions regarding the competency of “sports for all” instructors using big data analysis. Given the increasing number of everyday participants in sports in the Republic of Korea, this study aimed to identify sports for all instructor competency requirements and gaps and thus help to develop and foster such instructors’ competence. Methods: This study employed big data analysis, specifically, text mining, opinion mining, term frequency–inverse document frequency analysis, and degree centrality analysis. Semantic network analysis was also performed using Textom and UCINET 6’s NetDraw program. The data collection period was from 1 January 2016 to 31 December 2020. This five-year study was initiated following the reorganization of the sports for all instructor qualification system in the Republic of Korea in 2015. Results: First, eight groups were formed by extracting 80 words with the highest frequency and conducting a convergence of iteration correlation analysis. Second, categorization based on the results yielded four factors: certification of sports for all instructors, coaching competency, competency education, and emotions. Conclusions: The analysis of perceptions of the competencies of sports for all instructors revealed a great deal of interest in a qualification system that can develop competencies and in education that strengthens them. To become an effective sports for all instructor, corresponding competencies are required and a qualification system to acquire and strengthen these competencies is necessary. The state should focus continuous attention and effort on the qualification system to nurture such competencies.