The work presented in this paper is a part of an ongoing project that investigates academic text features indicative of its complexity at different grade levels. In this study we examine comparative complexity of Social science texts used in Russian secondary and high schools. Based on the metrics of ten descriptive and four lexical features assessed for seven classroom textbooks we claim lexical diversity, frequency, abstractness and the number of terminological units to be statistically significant predictors of text complexity. The total size of the Corpus of over 160.000 tokens comprising two sets of textbooks ranging from the 5th to the 11th grades provides a satisfactory level of its representativeness and as such a solid foundation for statistical validity of the results. We employ RusAC, an online text analyzer, to compute lexical features of texts and the effect of the four lexical features on text complexity is confirmed with a mixed analysis of variance. The study fills a gap both in corpus linguistics as regards a systematic approach to Russian academic texts and in text complexity studies as regards the description of secondary and high school textbooks.
The parametric model of the text as a research problem is of paramount importance in modern linguistics and education, since it opens up new approaches to understanding the processes of comprehending texts of various types. In the current study, 17 Russian language textbooks for elementary school were employed to identify correlations between lexical diversity indices and other complexity predictors. The total volume of the corpus compiled for the study is 439,938 words. The two-stage research algorithm included the evaluation of the reference values of text features at the basic level (word length, sentence length, the number of unique, non-repeating words and the number of word forms), evaluation and subsequent contrasting of complexity predictors, i.e. lexical diversity and readability indices. All calculations were performed with the automatic text analyzer RuLingva. The study revealed a positive dynamic of readability and no evidence of lexical diversity increase across grades. An average level of vocabulary diversity and overlaps of every 4th word in the text are fixed. No indication of correlation between text readability and lexical diversity is found. The obtained results can be useful to researchers, textbook authors, and teachers selecting textbooks. The prospects are seen in implementing functional and epidigmatic stratification of the vocabulary of the Russian textbooks under study.
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