Kolmogorov complexity metrics in assessing L2 proficiency: An information-theoretic approach - Wang, Gui; Wang, Hui; Wang, Li (Frontiers in Psychology, 2022)
Based on 774 argumentative writings produced by Chinese English as a foreign language (EFL) learners, this study examined the extent to which Kolmogorov complexity metrics can distinguish the proficiency of beginner, lower-intermediate, and upper-intermediate level second language (L2) learners. Kolmogorov complexity metric is a novel holistic information-theoretic approach, which measures linguistic complexity at three levels, i.e., overall, syntactic, and morphological complexity. This new metric is compared with traditional syntactic and morphological complexity metrics as well as fine-grained syntactic complexity metrics to assess its validity. Results showed that Kolmogorov overall and syntactic complexity could significantly distinguish any adjacent pair of L2 levels, serving as the best separators explored in the present study. However, none of the other complexity metrics, including Kolmogorov morphological complexity, is capable of significantly discriminating between all pairs of adjacent levels at both the syntactic and morphological levels. Results of correlation analysis showed that Kolmogorov syntactic complexity was weakly correlated with all the fine-grained syntactic complexity metrics, indicating that they may address distinct linguistic structures and can complement each other to better predict different proficiency levels.