Skip to main content
Springer Nature Link
Log in

Revisiting Assessment of Text Complexity: Lexical and Syntactic Parameters Fluctuations

  • Conference paper
  • First Online:
Speech and Computer (SPECOM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14338))

Included in the following conference series:

  • 833 Accesses

Abstract

In this article we share findings on linguistic complexity fluctuations of Russian middle school textbooks. The study partially confirmed the null hypothesis that textbook syntactic complexity grows universally over the course of a single school year. The Research Corpus was compiled of 104 textbooks used in 12 subject domains in Russian middle schools. In accordance with school semesters (Fall-Spring), we divided each textbook into two parts and examined 208 texts for 47 quantitative parameters measured with RuLingva (rulingva.kpfu.ru). After considering dynamics of the values of each parameter for Fall and Spring semesters, we narrowed the parameters list down to syntactic (average word length, average sentence length, Flesch-Kincaid grade level) and lexical (lexical diversity and frequency) clusters. We identified and scrutinized three types of text complexity fluctuations: simultaneous increase of both clusters of parameters, opposite dynamics and independent fluctuations. The majority of textbooks demonstrate lexical and syntactic clusters’ “trade-off’” when the lexical complexity increase triggers the syntactic complexity decrease thus balancing the joint complexity. We also discuss the assumptions that underline the concept of complexity fluctuations and algorithms of its measurements in an effort to put the issue on the agenda of researchers and education authorities. Our findings can be useful for scholars, academicians and education policy makers at the national and regional levels.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    SIS in FKFL(SIS) stands for the initials of the formula developers, i.e. Solovyev, Ivanov, Solnyshkina [19].

References

  1. Balakrishna, S.V.: Analyzing Text Complexity and Text Simplification: Connecting Linguistics, Processing and Educational Applications. Ph.D. thesis (2015)

    Google Scholar 

  2. Biber, D.: Representativeness in corpus design. Liter. Linguist. Comput. 8(4), 243–257 (1993)

    Article  Google Scholar 

  3. Blinova, O., Tarasov, N.: Complexity metrics of Russian legal texts: selection, use, initial efficiency evaluation. In: Papers from the Annual International Conference “Dialogue” (2022), pp. 1017–1028. https://doi.org/10.28995/2075-7182-2022-21-1017-1028

  4. Botarleanu, R.-M., Dascalu, M., Watanabe, M., Crossley, S.A.: Age of exposure 2.0: estimating word complexity using iterative models of word embeddings. Behav. Res. Methods 54(1), 3015–3042 (2022). https://doi.org/10.3758/s13428-022-01797-5

  5. Churunina, A.A., Solnyshkina, M.I., Yarmakeev, I.E.: Lexical diversity as a predictor of complexity in textbooks on the Russian language. Russ. Lang. Stud. 21(2), 212–227 (2023)

    Article  Google Scholar 

  6. Crossley, S.A., Skalicky, S.: Examining lexical development in second language learners: an approximate replication of Salsbury, Crossley & McNamara (2011). Lang. Teach. 52(3), 1–21 (2017)

    Google Scholar 

  7. Elmore, J., Hiebert, E.H.: Text complexity and the early grades: the fuss and how recent research can help. Phi Delta Kappan 97(8), 60–65 (2015)

    Google Scholar 

  8. DuBay, W.H. The principles of readability. Impact Information: Costa Mesa, CA. (2004)

    Google Scholar 

  9. Flesch, R.: A new readability yardstick. J. Appl. Psychol. 32, 221–233 (1948)

    Article  Google Scholar 

  10. Fpu.edu.ru. Order of the Ministry of Education of Russia No. 254. (2020)

    Google Scholar 

  11. Gatiyatullina, G., Solnyshkina, M., Solovyev, V., Danilov, A., Martynova, E., Yarmakeev, I.: Computing Russian morphological distribution patterns using RusAC online server. In: Proceedings - International Conference on Developments in eSystems Engineering, DeSE, art. no. 9450753, pp. 393–398 (2020)

    Google Scholar 

  12. Goldman, S.R., Lee, C.D.: Text complexity. Element. School J. 115, 290–300 (2014)

    Google Scholar 

  13. Guiraud, P.: Problèmes et méthodes de la statistique linguistique. Dordrecht: Reidel, D. Harley, B., & King, M. L. Verb lexis in the written compositions of young L2 learners. Stud. Second Lang. Acquisit. 11, 415–440 (1989)

    Google Scholar 

  14. Laposhina, A.N., Lebedeva, M.Yu.: Textometr: an online tool for automated complexity level assessment of texts for Russian language learners. Russ. Lang. Stud. 19(3), 331–345 (2021)

    Google Scholar 

  15. Lina Sulieman, L., Robinson, J.R., Jackson, G.P.: Automating the classification of complexity of medical decision-making in patient-provider messaging in a patient portal. J. Surg. Res. 255, 224–232 (2020)

    Google Scholar 

  16. Lyashevskay, O.N., Sharoff, S.A.: New Russian frequency dictionary (2009). http://dict.ruslang.ru/freq.php. Accessed 28 Dec 2021

  17. Santini, M., Jönsson, A.: Pinning down text complexity - an exploratory study on the registers of the Stockholm-Umeå corpus (SUC). Regist. Stud. 2(2), 306–349 (2020)

    Article  Google Scholar 

  18. Solovyev, V., Andreeva, M., Solnyshkina, M., Zamaletdinov, R., Danilov, A., Gaynutdinova, D.: Computing concreteness ratings of Russian and English most frequent words: contrastive approach. In: Proceedings - International Conference on Developments in eSystems Engineering, DeSE, art. no. 9073272, pp. 403–408 (2019)

    Google Scholar 

  19. Solnyshkina, M., Ivanov, V., Solovyev, V.: Readability formula for Russian texts: a modified version. In: Batyrshin, I., Martínez-Villaseñor, M.L., Ponce Espinosa, H.E. (eds.) MICAI 2018. LNCS (LNAI), vol. 11289, pp. 132–145. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-04497-8_11

    Chapter  Google Scholar 

  20. Solnyshkina, M.I., Harkova, E.V., Kazachkova, M.B.: The structure of cross-linguistic differences: meaning and context of ‘readability’ and its Russian equivalent ‘chitabelnost.’ J. Lang. Educ. 6(1), 103–119 (2020)

    Article  Google Scholar 

  21. Solnyshkina, S.I., Kiselnikov, A.S.: Complexity of the text: stages of study in Russian applied linguistics. Quest. Cognit. Linguist. 1, 18–40 (2022)

    Google Scholar 

  22. Solnyshkina, M.I., Solovyev, V.D., Gafiatova, E.V., Martynova, E.V.: Text complexity as an interdisciplinary problem. Quest. Cognit. Linguist. 1, 18–40 (2022)

    Google Scholar 

  23. Solovyev, V., Solnyshkina, M., Ivanov, V., Batyrshin, I.: Prediction of reading difficulty in Russian academic texts. J. Intell. Fuzzy Syst. 36(5), 4553–4563 (2019)

    Google Scholar 

  24. Solnyshkina, M., Solovyev, V., Ivanov, V., Danilov, A.: Studying text complexity in Russian Academic Corpus with multi-level annotation. CEUR Worksh. Proc. 2303, 1–11 (2018)

    Google Scholar 

  25. Kupriyanov, R.V., Solnyshkina, M.I., Dascalu, M., Soldatkina, T.A.: Lexical and syntactic features of academic Russian texts: a discriminant analysis research result. Theor. Appl. Linguist. 8(4), 105–122 (2022)

    Google Scholar 

  26. Churunina, A.A., Solnyshkina, M.I., Yarmakeev, I.E.: Lexical diversity as a predictor of the complexity of textbooks on the Russian language. Rusistika. Russ. Stud. 21(2), 212–227 (2023)

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the Kazan Federal University Strategic Academic Leadership (Priority 2030).

Author information

Authors and Affiliations

  1. Kazan Federal University, 420008, Kazan, Russia

    Alexandra Vahrusheva, Valery Solovyev, Marina Solnyshkina & Elzara Gafiaytova

  2. Kazan National Research Technological University, Kazan, Russia

    Svetlana Akhtyamova

Authors
  1. Alexandra Vahrusheva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Valery Solovyev
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marina Solnyshkina
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Elzara Gafiaytova
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Svetlana Akhtyamova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Valery Solovyev .

Editor information

Editors and Affiliations

  1. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Alexey Karpov

  2. Koneru Lakshmaiah Education Foundation, Vaddeswaram, India

    K. Samudravijaya

  3. Indian Institute of Information Technology Dharwad, Dharwad, India

    K. T. Deepak

  4. Indian Institute of Technology Dharwad, Dharwad, India

    Rajesh M. Hegde

  5. KIIT Group of Colleges, Gurugram, India

    Shyam S. Agrawal

  6. Indian Institute of Technology Dharwad, Dharwad, India

    S. R. Mahadeva Prasanna

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Vahrusheva, A., Solovyev, V., Solnyshkina, M., Gafiaytova, E., Akhtyamova, S. (2023). Revisiting Assessment of Text Complexity: Lexical and Syntactic Parameters Fluctuations. In: Karpov, A., Samudravijaya, K., Deepak, K.T., Hegde, R.M., Agrawal, S.S., Prasanna, S.R.M. (eds) Speech and Computer. SPECOM 2023. Lecture Notes in Computer Science(), vol 14338. Springer, Cham. https://doi.org/10.1007/978-3-031-48309-7_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-48309-7_35

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48308-0

  • Online ISBN: 978-3-031-48309-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics