2025 Heilongjiang Provincial Key Educational Science Project under the 14th Five-Year Plan, A Study on the Industry-Education Collaborative Talent Cultivation Mechanism for Foreign Affairs Interpreting in Heilongjiang’s Ice and Snow Sector in the Era of Educational Digital Intelligence (Number: GJB1425008).
Abstract
In high-stakes language examinations, the text complexity of reading input materials is a key decisive factor of test validity. However, the empirical research that follows the long-term adjustment of text difficulty in different policy periods is still not much. This quantitative research has explored the language change of 665 English reading texts from the Chinese Senior High School Entrance Examination (CSHSEE) in Shandong Province during two time periods: the Core Competency Phase (2015-2020) and the Double Reduction Phase (2021-2024). The data were evaluated by Eng-Editor across lexical, syntactic, and textual dimensions. Time-series visualization was constructed to describe the change over a long time, while the non-parametric Mann-Whitney U test was employed to find significant cross-phase variations. The analysis has found a selective moderation of linguistic dimensions. Specifically, syntactic and textual complexity have shown obvious decreases, serving as responsive focal points for the double reduction policy. On the opposite side, the lexical complexity works as a dimension that does not change, which is restricted by the word lists of the curriculum. These results indicate that macro-level policy gets put into practice mainly by way of structural simplification, not the simplification that is based on components. This study offers empirical insights into how educational changes mold assessments, pointing out the strategy that test designers navigate between policy and syllabus constraints.
References
Crossley, S. A. (2025). Developing linguistic constructs of text readability using natural language processing. Scientific Studies of Reading, 29(2), 138-160.
Crossley, S. A., Greenfield, J., & McNamara, D. S. (2008). Assessing text readability using cognitively based indices. TESOL Quarterly, 42(3), 475-493.
Jin, T., & Lu, X. (2025). Eng-Editor: An online Chinese text evaluation and adaptation system.
https://www.languagedata.net/tester/
Liu, F., Jiang, Y., Lai, C., & Jin, T. (2024). Teacher engagement with automated text simplification for differentiated instruction. Language Learning & Technology, 28(2), 163-182.
Qian, L., Cheng, Y., & Zhao, Y. (2021). Use of linguistic complexity in writing among Chinese EFL learners in high-stakes tests: Insights from a corpus of TOEFL iBT. Frontiers in Psychology, 12, 765983.
Su, Y., Liu, K., Liu, F., Lee, J., & Jin, T. (2024). Lexical complexity in exemplar EFL texts: Towards text adaptation for 12 grades of basic English curriculum in China. International Review of Applied Linguistics in Language Teaching, 62(1), 137-164.
Sun, H. (2020). Unpacking reading text complexity: A dynamic language and content approach. Studies in Applied Linguistics and TESOL, 20(2), 1-20.
Toyama, Y., Hiebert, E. H., & Pearson, P. D. (2017). An analysis of the text complexity of leveled passages in four popular classroom reading assessments. Educational Assessment, 22(3), 139-170.
Yu, X. (2021). Text complexity of reading comprehension passages in the National Matriculation English Test in China: The development from 1996 to 2020. International Journal of Language Testing, 11(2), 142-167.
How to cite this paper
Reading Text Complexity in the Chinese Senior High School Entrance Examination: A Longitudinal Study from 2015 to 2024
How to cite this paper: Xinqing Feng, Hui Dong. (2026) Reading Text Complexity in the Chinese Senior High School Entrance Examination: A Longitudinal Study from 2015 to 2024. Journal of Humanities, Arts and Social Science, 10(4), 496-500.
DOI: http://dx.doi.org/10.26855/jhass.2026.04.016