@article{ART003338820},
author={김정란 and Jung, YeonJoo},
title={Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis},
journal={Modern English Education},
issn={1598-0782},
year={2026},
volume={27},
pages={308-321}
TY - JOUR
AU - 김정란
AU - Jung, YeonJoo
TI - Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis
JO - Modern English Education
PY - 2026
VL - 27
IS - null
PB - The Modern English Education Society
SP - 308
EP - 321
SN - 1598-0782
AB - Readability assessment allows educators to evaluate text complexity using single numerical scores, which helps in selecting materials suited to various proficiency levels. However, accurate calibration of difficulty requires an understanding of complex linguistic features, especially in high-stakes assessments. This study explored the relationships between 26 lexical indices and readability scores across four categories of CSAT English reading items. The data included 335 reading items from high-difficulty tests (2017–2024), analyzed with CAREC and TAALES 2.0. The age of acquisition displayed systematic variation: discourse structure inference (r = 0.712), contextual inference (r = 0.674), main idea comprehension (r = 0.513), and language component analysis (r = 0.504). Linear Mixed Effects models demonstrated significant differences in explanatory power: contextual inference (R² = 63.9%) was influenced by multiple predictors, discourse structure inference (R² = 50.1%) was affected by vocabulary maturity, main idea comprehension (R² = 39.1%) was linked to processing efficiency, and language component analysis (R² = 32.8%) was related to semantic complexity. These results indicate that lexical features contribute differently to readability assessment across item categories, suggesting the need for item-type specific lexical approaches. However, findings should be considered within the CAREC framework, as the readability measure itself includes lexical features similar to those analyzed as predictors.
KW - CSAT;lexical sophistication;readability assessment;computational linguistics
DO -
UR -
ER -
김정란 and Jung, YeonJoo. (2026). Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis. Modern English Education, 27, 308-321.
김정란 and Jung, YeonJoo. 2026, "Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis", Modern English Education, vol.27, pp.308-321.
김정란, Jung, YeonJoo "Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis" Modern English Education 27 pp.308-321 (2026) : 308.
김정란, Jung, YeonJoo. Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis. 2026; 27 308-321.
김정란 and Jung, YeonJoo. "Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis" Modern English Education 27(2026) : 308-321.
김정란; Jung, YeonJoo. Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis. Modern English Education, 27, 308-321.
김정란; Jung, YeonJoo. Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis. Modern English Education. 2026; 27 308-321.
김정란, Jung, YeonJoo. Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis. 2026; 27 308-321.
김정란 and Jung, YeonJoo. "Lexical Features and Readability across Item Categories in CSAT English High-difficulty Reading Items: A Computational Analysis" Modern English Education 27(2026) : 308-321.
