SHS Web Conf.
Volume 88, 2020International Scientific Forum “Issues of Modern Linguistics and the Study of Foreign Languages in the Era of Artificial Intelligence (dedicated to World Science Day for Peace and Development)” (LLT Forum 2020)
|Number of page(s)||8|
|Section||Conference 2 - Methodological Problems of Teaching and Learning Foreign Languages Using Computer and Network Technologies|
|Published online||24 December 2020|
Fluctuations of text complexity: the case of Basic State Examination in English
Kazan Federal University 18 Kremlyovskaya str, Kazan, 420008 Russian Federation
* Corresponding author: email@example.com
Text complexity as a research problem is equally relevant in linguistics and education since its solution provides an algorithm to match readers of certain categories to texts. Numerous studies have been conducted to identify quantitative and qualitative parameters that affect text complexity in ESOL. However, text complexity range within one proficiency level remains a research niche. The current study is aimed at identifying the range of text complexity fluctuations within one proficiency level and their appropriateness for readers. We conduct a multi-factor analysis and contrast 66 English texts for Basic State Examination (OGE) in readability, average sentence length, word length, number of verbs and nouns, cohesion and lexical diversity. The text features computed with the two online services, Text Inspector and Coh-Metrix, provide slightly different quantitative results though consistent in qualifying the range of text complexity fluctuations as high. The research findings refute the hypothesis of a linear nature of text complexity growth in the textbooks designed to increase students’ proficiency and confirm the lack of correlation between the revealed and claimed complexity of texts. The algorithm suggested by the authors can be useful for textbook writers and test developers selecting reading material for any proficiency level.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.