This study analyzes 115 academic publications related to Chinese language testing in South Korea, collected from the CNKI database between 1990 and 2025. Using CiteSpace 6.3 R1, it employs bibliometric and knowledge mapping methods to examine the field’s development across four dimensions: publication volume, author collaboration, keyword clustering, and research hotspots. The findings reveal that the research in this domain started relatively late, with low publication volume, fluctuating output, and limited collaboration, indicating the absence of a stable academic community.
Keyword analysis shows that research has primarily focused on standardized tests such as the HSK and TSC, gradually expanding to areas like College Entrance Chinese, lexical errors, and teaching assessment. The keyword evolution and burst detection suggest a shift from the early introduction of standardized testing systems to their localized adaptation, with increasing emphasis on ability-oriented and instructional integration.
Despite its initial formation, the field still faces limitations such as a narrow research scope, weak theoretical foundation, and insufficient empirical support. Future research should focus on: (1) standardizing College Entrance Chinese in alignment with curriculum frameworks; (2) integrating item analysis with measurement theory to refine assessment tools; and (3) leveraging AI and big data technologies to construct intelligent, data-driven Chinese testing systems, thereby enhancing the scientific validity and practical relevance of localized language testing.