The article examines trends and future tasks in Korean language education research using statistical analysis. It looks at how numerical data is collected and processed in these studies. The study found that out of 185 papers analyzed, most used descriptive statistics. Other common approaches included comparative studies, correlative studies, effect relationship studies, and classification studies. The research highlights the importance of using quantitative indicators in collecting data and addresses criticisms about the limitations of artificial environments in explaining complex teaching and learning conditions.