Towards a Taxonomy of Textbooks as a Genre: the Case of Russian Textbooks

Cover Page

Cite item

Full Text

Abstract

The project is presented in the paper initially is launched to design a functional recognition or classification model of a modern Russian school textbook as a genre. In this study we test and confirm the hypothesis that detection of domain (subject area) and complexity level of a textbook can be reduced to a limited number of quantitative linguistic parameters provided with accurately identified and verified value ranges. We outlined our approach to genre analysis as multi-dimensional, compiled a corpus of over 1 mln. tokens, measured values of 15 linguistic parameters in 19 textbooks of two different subject areas and complexity levels, revealed 7 complexity predictors, 7 subject area predictors, and one - frequency - a metaparameter able to discriminate textbooks of History and Social Studies from texts of other genres. Our findings highlight the significance of the following parameters for textbooks across the selected subject areas: incidence of nouns, verb tenses (present, past and future), local and global argument overlap, type-token ratio. Complexity classification model is ascertained to be a function of sentence length, word length, incidence of nouns in genitive case and verbs, Abstractness score, verb/noun ratio, and adjective/noun ratio. The outcomes of this analysis will be used to interpret quantitative linguistic descriptions and classify texts.

About the authors

Marina I. Solnyshkina

Kazan (Volga Region) Federal University

Author for correspondence.
Email: mesoln@yandex.ru
ORCID iD: 0000-0003-1885-3039
SPIN-code: 6480-1830
Scopus Author ID: 56429529500
ResearcherId: E-3863-2015

Ds.Dc. (Philology), Head and Chief Researcher, Text Analytics Research Laboratory, Professor of the Department of Theory and Practice of Teaching Foreign Languages, Institute of Philology and Intercultural Communication

18, Kremlevskaya str., Kazan, Russian Federation, 420008

Gulnoza N. Shoeva

Kazan (Volga Region) Federal University

Email: gnshoeva@yandex.ru
ORCID iD: 0009-0005-0438-0404

PhD student of the Department of Theory and Practice of Teaching Foreign Languages, Text Analytics Research Laboratory, Institute of Philology and Intercultural Communication

18, Kremlevskaya str., Kazan, Russian Federation, 420008

Ksenia O. Kosova

RUDN University

Email: kosova-ko@rudn.ru
ORCID iD: 0009-0007-5606-9604
SPIN-code: 2675-2106

PhD student of the Department of Foreign Languages, Faculty of Philology

6, Miklukho-Maklaya str., Moscow, Russian Federation, 117198

References

  1. Kessler, B., Nunberg, G. & Schuetze, H. (1997). Automatic Detection of Text Genre.
  2. Biber, D. (1988). Variation across Speech and Writing. Cambridge: Cambridge University Press.
  3. Biber, D. & Conrad, S. (2013). Introduction: Multi-dimensional analysis and the study of register variation. In: S. Conrad & D. Biber (Eds.) Variation in English: Multidimensional studies. Routledge. pp. 3-12.
  4. Biber, D. & Gray, B. (2016). Grammatical Complexity in Academic English: Linguistic Change in Writing. Cambridge: Cambridge University Press.
  5. Paltridge, B. (1994). Genre Analysis and the Identification of Textual Boundaries. Applied Linguistics, 15, 288-299.
  6. Raible, W. (2019). Variation in Language: How to Characterise Types of Texts and Communication Strategies between Orality and Scripturality. Answers given by Koch / Oesterreicher and by Biber. International Journal of Language and Linguistics, 6(2). https://doi.org/10.30845/ijll.v6n2p19
  7. Hyland, K. (2004). Disciplinary Discourses: Social Interactions in Academic Writing. Michigan: University of Michigan Press.
  8. Kupriyanov, R.V., Solnyshkina, M.I. & Lekhnitskaya, P.A. (2023). Parametric Taxonomy of Educational Texts. Science Journal of Volgograd State University. Linguistics, 22(6), 80- 94. https://doi.org/10.15688/jvolsu2.2023.6.6 (In Russ.).
  9. Gatiyatullina, G., Solnyshkina, M., Solovyev, V., Danilov, A., Martynova, E. & Yarmakeev, I. (2020). Computing Russian Morphological distribution patterns using RusAC Online Server Proceedings. International Conference on Developments in eSystems Engineering, DeSE 9450753. pp. 393-398. https://doi.org/10.1109/DeSE51703.2020.9450753
  10. Paraschiv, A., Dascalu, M. & Solnyshkina, M.I. (2023). Classification of Russian textbooks by grade level and topic using ReaderBench. Research Result. Theoretical and Applied Linguistics, 9(1), 50-63. https://doi.org/110.18413/2313-8912-2023-9-1-0-4
  11. Solnyshkina, M.I., Kupriyanov, R.V. & Shoeva, G.N. (2024). Linguistic profiling of text genres: adventure stories vs. textbooks. Research Result. Theoretical and Applied Linguistics, 10(1), 15-132. https://doi.org/10.18413/2313-8912-2024-10-1-0-7
  12. Swales, J.M. (1990). Genre Analysis English in Academic and Research Settings. Cambridge: Cambridge University Press.
  13. Lüdeling, A. & Kytö, M. (2009). Corpus Linguistics. An International Handbook (HSK 29.1 und 29.2). Berlin, New York: Mouton de Gruyter. https://doi.org/10.1515/zrs-2012-0019
  14. Biber, D. & Conrad, S. (2019). Register, Genre, and Style. Cambridge: Cambridge University Press.
  15. Alekseeva, L.M., Annushkin, V.I. & Bazhenova, E.A. (2003). Stilisticheskii entsiklopedicheskii slovar’ russkogo yazyka. Moscow: Nauka: Flinta. (In Russ.).
  16. Kuznetsova, J. (2015). Linguistic profiles: going from form to meaning via statistics. New York: Mouton de Gruyter. https://doi.org/10.1515/9783110361858
  17. Yakhibbaeva, L.M. (2008). Uchebnyi tekst kak osobyi vid vtorichnogo teksta i sostavlyayushchaya uchebnogo diskursa. Vestnik Bashkirskogo universiteta, 13(4), 1029-1031.
  18. Vedyakova, N.A. (2016). Uchebnyi tekst - nauchnyi tekst? Lingua mobilis, 1(54), 19-26.
  19. Plavén-Sigray, P. & Matheson, G.J., Schiffler, B.Ch. & Thompson, W.H. (2017). Research: The readability of scientific texts is decreasing over time eLife. URL: https://elifesciences.org/articles/27725#cite-this-article (accessed: 12.01.2024). https://doi.org/10.7554/eLife.27725
  20. Ember, M. & Ember, C. (1999). Cross-Language Predictors of Consonant-Vowel Syllables. American Anthropologist, 101(4), 730-742.
  21. Lyons, C. (1986). The syntax of English genitive constructions. Journal of Linguistics, 22(1), 123-143. https://doi.org/10.1017/S0022226700010586
  22. Tang, J. (2024). Variation in metadiscourse verb patterns in English academic papers from intra- and interdisciplinary analysis. Applied Mathematics and Nonlinear Sciences, 9(1).
  23. Hodošček, B. (2011). Word Class Ratios and Genres in Written Japanese: Revisiting the Modifier Verb Ratio. Acta Linguistica Asiatica, 1(2).
  24. Biber, D., Conrad, S. & Reppen, R. (1999). Corpus Linguistics: Investigating Language Structure and Use. Cambridge: Cambridge University Press.
  25. Sharoff, S., Umanskaya, E. & Wilson, J. (2013). A Frequency Dictionary of Russian: Core vocabulary for learners. Routledge.
  26. Van Dijk, T.A. (1988). News as Discourse. Lawrence Erlbaum Associates, Inc.
  27. Read, J. (2000). Assessing vocabulary. Cambridge: Cambridge University Press. https://doi. org/10.1017/CBO9780511732942
  28. Treffers-Daller, J., Parslow, P. & Williams Sh. (2018). Back to Basics: How Measures of Lexical Diversity Can Help Discriminate between CEFR Levels. Applied Linguistics, 39(3), 302-327. https://doi.org/10.1093/applin/amw009
  29. Yang, J.S., Rosvold, C. & Bernstein, R.N. (2022). Measurement of Lexical Diversity in Children’s Spoken Language: Computational and Conceptual Considerations. Front. Psychol, 13, 905789. https://doi.org/10.3389/fpsyg.2022.905789
  30. Foltz, P.W., Kintsch, W. & Landauer, T.K. (1998). The Measurement of Textual Coherence with Latent Semantic Analysis. Discourse Processes, 25 (2-3), 285-307. https://doi.org/10.1080/01638539809545029
  31. McNamara, D.S., Louwerse, M.M., McCarthy, P.M. & Graesser, A.C. (2010). Coh-Metrix: Capturing linguistic features of cohesion. Discourse Processes, 47, 292-330.
  32. Crossley, S.A. & McNamara, D.S. (2011). Text cohesion and judgments of essay quality: Models of quality and coherence. Cognition and Instruction, 29(6), 569-589.
  33. Marza, L.E. (2011). A comprehensive corpus-based study of the use of evaluative adjectives in promotional hotel websites. Odisea, 12, 97-123.

Supplementary files

Supplementary Files
Action
1. JATS XML
Download

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).