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Verification of the effectiveness of vocabulary learning strategies using Russian word formation based on empirical research

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Abstract

This study aims to verify the effectiveness of vocabulary learning strategies using Russian word formation through empirical research. More specifically, this study investigates whether knowledge about word formation can be used to effectively predict the meanings of unknown derived verbs with a verbal prefix v- ‘in, into’.

In the experiments, a control group and an experimental group were prepared. First, both groups underwent a pretest to predict the meanings of derived verbs with v- in context. Afterwards, only the experimental group received instruction about general word-formation rules, usage of the prefix v- and meaning prediction tasks. Subsequently, both groups took a posttest at the same level as the pretest. The author designed the pretest and posttest so that the participants in both groups were familiar with all of the words in the questions and the base words of the target derivatives. The experimental group acquired the abovementioned knowledge about word formation through the instruction. Thus, if the instruction was helpful for determining the meanings of unknown derived verbs, the posttest score of the experimental group would surpass that of the control group. The results highlight the following two points: (1) In fact, the experimental group achieved a higher score than the control group. Therefore, vocabulary learning strategies with Russian word formation can be used to effectively predict the meanings of unknown words. (2) However, unlike some other vocabulary learning strategies, using affix knowledge requires regular and numerous repetitions of tasks.

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Notes

  1. Zwier and Boers (2023, pp. 164–165) provide a synopsis of the vocabulary’s role in following influential methods and approach: Grammar-translation method, Direct method, Audio-lingual method, the Natural approach, Communicative Language Teaching.

  2. However, note that according to Paul Nation, the number of studies related to vocabulary had increased, which highlights a rise in interest in vocabulary (Nation, 2011, pp. 1–2).

  3. Table 1 is partly modified based on one in Sayama (2018). Regarding English-Russian translations in the table, the author confirmed them in the Oxford Russian-English dictionary (Wheeler et al., 2007). Other translations in this study are also cited from the same source.

  4. These prefixed verbs are as follows: (1) vpisat’ ‘indert’, (2) vypisat’ ‘write out’, (3) dopisat’ ‘finish writing’, (4) zapisat’ ‘take down in writing’, (5) ispisat’ ‘cover with writing’, (6) nadpisat’ ‘inscribe’, (7) nedopisat’ ‘not finish writing’, (8) opisat’ ‘describe’, (9) otpisat’ ‘bequeath’, (10) perepisat’ ‘rewrite’, (11) popisat’ ‘write for a while’, (12) podpisat’ ‘sign’, (13) predpisat’ ‘order’, (14) pripisat’ ‘add’, (15) propisat’ ‘register’, (16) raspisat’ ‘note down’, (17) spisat’ ‘copy from’, (18) upisat’ ‘get in’.

  5. The Brown corpus is a balanced written corpus of American English with one million running words. The lexical coverage was cited from the data by Nation (2001, p. 15). The BNC is also a balanced corpus of British English that consists of written and spoken texts and obtains approximately 100 million running words. The lexical coverage of BNC was calculated by the author using the frequency data presented by Adam Kilgarriff (URL: https://www.kilgarriff.co.uk/). For details of these corpora and balanced corpora, see McEnery and Hardie (2012).

  6. RNC-M is a written balanced corpus which was compiled referring to BNC, including 9200 million running words. The lexical coverage was gained from the frequency dictionary of RNC (Ljaševskaja & Šarov, 2009). The Internet Corpus (Sharoff et al., 2013) consists of 150 million running words and includes texts from 30,000 web pages. The text genres include reporting (newswire), fiction and popular lore, legal texts, instruction (FAQ and teaching), and discussion (blogs, forum, and so on). According to Sharoff et al. (2013, p. 5), compared with RNC-M, the Internet Corpus is more suitable for language learning due to its abundance of texts regarding personal interaction from the discussion genre.

  7. A lemma consists of a headword (or base form) and its inflected forms (cf. Nation, 2001, p. 7; Baker et al., 2006, p. 104; Schmitt & Schmitt, 2020, pp. 5–6). For example, under counting words by the lemma unit, a base form mal’čik ‘boy’ and all inflected forms such as mal’čika, mal’čiku, mal’čikom, mal’čike and so on, are counted as one lemma. As Nation (2022, p. 9) noted, the learning burden (Swenson & West, 1934) of inflected forms is significantly small once a learner has acquired the related inflection system.

  8. RNC-S is a spoken corpus containing 700,000 running words, and its frequency data was cited from Ljaševskaja and Šarov (2009).

  9. For example, in English, specialized word lists compiled according to word family units have been developed for academic study (for details see Coxhead, 2000 and Gardner & Davies, 2014).

  10. The recalculation of the lemma data by the word family unit was completed manually in the following way: first, a frequency data list was created by the author using the electronic version of Ljaševskaja and Šarov (2009) from RNC-M and RNC-S. Next, drawing on the description of Tixonov (1985), the list was reorganized using the word family unit. Finally, the frequency data (lexical coverage) in RNC-M and RNC-S was recalculated according to the word family units. In the recalculation, discrepancies in frequency data were carefully monitored using Excel’s function features to ensure accuracy.

  11. For details about other VLSs refer to Schmitt (1997, pp. 207–208).

  12. The corpus-based analysis of Sayama (2018) showed that derived words with compositional word-formation meanings hardly ever occurs among the highest frequency 5000 from RNC-M and RNC-S. These words are removed from the analysis in this study because it focuses on the effective VLSs with word formation.

  13. For example, Bauer and Nation (1993) set up the levels of inflectional and derivational affixes for vocabulary learning based on some criteria; introducing such an example of derivation as price – priceless, Zwier and Boers (2023, p. 8) noted that knowledge about certain affixes does not always guarantee correct comprehension of derived words with these affixes; Schmitt and Schmitt (2020, pp. 6, 71) also stated that the choice of members included in a certain word family depends on the learner’s proficiency and that using word parts occasionally has difficulties in meaning prediction.

  14. In the experiment concerning these meanings, the sample size was not substantial (n = 17). Therefore, careful attention is needed in assessing the results.

  15. No English translation was provided in the actual tests. This applies to the other examples.

  16. The participants of the experiment in this study did not take part in the experiments from Sayama (2022).

  17. In the following second semester, the author is going to provide the same instruction to the control group because the classes will be switched each semester.

  18. To give every participant the opportunity to answer all questions, each test was designed to consist of 15 questions.

  19. The author created a vocabulary list from the participant’s textbooks using the function Word list in Sketch Engine (URL: https://www.sketchengine.eu/). Therefore, the test condition vocabulary terms were greatly controlled. The meanings of words that may have been unfamiliar to the participants were provided as notes in the questions.

References

  • Amiantova, E. (Ed.) (2016). Leksika russkogo jazyka. Sbornik upražnenij, 8-e izd., ster. Flinta Nauka.

    Google Scholar 

  • Baker, P., Hardie, A., & McEnery, T. (2006). A glossary of corpus linguistics. Edinburgh University Press.

    Book  Google Scholar 

  • Barykina, A. N., & Dobrovol’skaja, V. V. (2015). Izučaem glagol’nye pristavki, 3-e izd. Zlatoust.

    Google Scholar 

  • Bauer, L., & Nation, I. S. P. (1993). Word families. International Journal of Lexicography, 6(4), 253–279.

    Article  Google Scholar 

  • Bloom, B. (1956). Taxonomy of educational objectives: The classification of educational goals. Longmans, Green.

    Google Scholar 

  • Buddingh, M. (2005). The effects of teaching roots and affixes on the vocabulary development of underperforming students. Master’s thesis, Sac State Scholars. https://scholars.csus.edu/esploro/outputs/graduate/The-effects-of-teaching-roots-and/99257831142701671.

  • Carver, R. P. (1994). Percentage of unknown vocabulary words in text as a function of the relative difficulty of the text: Implications for instruction. Journal of Reading Behavior, 26(4), 413–437.

    Article  Google Scholar 

  • Coxhead, A. (2000). A new academic word list. TESOL Quarterly, 34(2), 213–238.

    Article  Google Scholar 

  • Dörnyei, Z. (2003). Questionnaires in second language research: Construction, administration, and processing. Erlbaum.

    Google Scholar 

  • Efremova, T. F. (1996). Tolkovyj slovar’ slovoobrazovatel’nyx edinic russkogo jazyka. Russkij jazyk.

    Google Scholar 

  • Folse, K. S. (2004). Vocabulary myths: Applying second language research to classroom teaching. University of Michigan Press.

    Book  Google Scholar 

  • Gardner, D., & Davies, M. (2014). A new academic vocabulary list. Applied Linguistics, 35, 305–327.

    Article  Google Scholar 

  • Gu, Y., & Johnson, R. K. (1996). Vocabulary learning strategies and language learning outcome. Language Learning, 46(4), 643–679.

    Article  Google Scholar 

  • Hirsh, D., & Nation, I. S. P. (1992). What vocabulary size is needed to read unsimplified texts for pleasure? Reading in a Foreign Language, 8(2), 689–696.

    Google Scholar 

  • Hu, M., & Nation, I. S. P. (2000). Unknown vocabulary density and reading comprehension. Reading in a Foreign Language, 13(1), 403–430.

    Google Scholar 

  • Isačenko, A. V. (1960). Grammatičeskij stroj russkogo jazyka v sopostavlenii so slovackim. Morfologija., Č.2. Izdatel’stvo Slovackoj Akademii nauk.

    Google Scholar 

  • Janda, L. A., Kuznetsova, J., Lyaševskaya, O., Makarova, A., Nesset, T., & Sokolova, S. (2013). Why Russian aspectual prefixes aren’t empty: Prefixes as verb classifiers. Slavica.

    Google Scholar 

  • Janko-Trinickaja, N. A. (2001). Slovoobrazovanie v sovremennom russkom jazyke. Indrik.

    Google Scholar 

  • Karaulov, J. N. (Ed.) (1997). Russkij jazyk: Enciklopedija, 2-e izd. perer. i dop. Bol’šaja rossijskaja enciklopedija.

    Google Scholar 

  • Kiselëva, M. S. (2016). Leksika i slovoobrazovanie: Učebnoe posobie, 2-e izd., ster. Flinta.

    Google Scholar 

  • Komori, K., Mikuni, Z., & Kondo, A. (2004). Bunsyō rikai o sokushin suru goi chishiki no ryōteki sokumen – Kichigoritsu no shikīchi tansaku no kokoromi. Nihongo kyōiku, 120, 83–92.

    Google Scholar 

  • Kozlova, N. A. (2014). Učebnyj slovoobrazovatel’nyj slovar’ russkogo jazyka. Zlatoust.

    Google Scholar 

  • Laufer, B. (1989). What percentage of text-lexis is essential for comprehension? In C. Lauren & M. Nordman (Eds.), Special language: From humans thinking to thinking machines (pp. 316–323). Multilingual Matters.

    Google Scholar 

  • Laufer, B. (1997). The lexical plight in second language reading. In J. Coady & T. Huckin (Eds.), Second language vocabulary acquisition: A rationale for pedagogy (pp. 20–34). Cambridge University Press.

    Google Scholar 

  • Ljaševskaja, O. N., & Šarov, S. A. (2009). Častotnyj slovar’ sovremennogo russkogo jazyka na materialax Nacional’nogo korpusa russkogo jazyka. Azbukovnik.

    Google Scholar 

  • McEnery, T., & Hardie, A. (2012). Corpus linguistics: Method, theory and practice. Cambridge University Press.

    Google Scholar 

  • Mizumoto, A. (2006). Daigakusei no goi gakusyū sutoratejī shiyō to gakusyū seika no kankei – Jinbunkei jyoshidaisei o taisyō to shita chōsa. Kōnan jyoshidaigaku kenkyūkiyō Bungaku Bunkahen, 42, 93–107.

    Google Scholar 

  • Mizumoto, A. (2015). EMS o riyō shita kyōiku kōka no sokutei. In S. Osawa & D. Nakanishi (Eds.), E-learning ha kyōiku o kaeruka: Moodle o chūshin to shita LMS no dōnyū kara hyōka made (pp. 165–179), Kaibundo syuppan.

    Google Scholar 

  • Mochizuki, M., Aizawa, K., & Tono, Y. (2003). Eigo goi no shidō manyuaru. Taishūkan shoten.

    Google Scholar 

  • Nakayama, N. (2008). Effects of vocabulary learning using affix: Special focus on prefix. Kyōai gakuen maebashi kokusai daigaku ronshū, 8, 63–74.

    Google Scholar 

  • Nation, I. S. P. (1990). Teaching and learning vocabulary. Newbury House.

    Google Scholar 

  • Nation, I. S. P. (2001). Learning vocabulary in another language. Cambridge University Press.

    Book  Google Scholar 

  • Nation, I. S. P. (2006). How large a vocabulary is needed for reading and listening? The Canadian Modern Language Review, 63, 59–82.

    Article  Google Scholar 

  • Nation, I. S. P. (2008). Teaching vocabulary - strategies and techniques. Heinle Cengage Learning.

    Google Scholar 

  • Nation, I. S. P. (2011). Vocabulary research into practice. Language Teaching, 44(4), 1–11.

    Article  Google Scholar 

  • Nation, I. S. P. (2022). Learning vocabulary in another language (3rd ed.). Cambridge University Press.

    Book  Google Scholar 

  • Nation, I. S. P., & Laufer, B. (2012). Vocabulary. In S. Gass & A. Mackey (Eds.), The Routledge handbook of second language acquisition (pp. 163–176). Routledge.

    Google Scholar 

  • Nishikawa, M. (2006). Eigo setsuji kenkyū. Kaitakusha.

    Google Scholar 

  • Oxford, R. L. (1990). Language learner strategies: What every teacher should know. Newbury House.

    Google Scholar 

  • Sasao, Y., & Webb, S. (2017). The word part levels test. Language Teaching Research, 21(1), 12–30.

    Article  Google Scholar 

  • Sayama, G. (2018). Hasei setsuji o mochiita roshiago no kōritsuteki na goi gakushūhō no kento – Kopasu ga teiji suru hindo deta no gengogakuteki na bunseki ni motozuite, Doctoral dissertation, TUFS Prometheus Academic Collections System. http://repository.tufs.ac.jp/handle/10108/92268.

  • Sayama, G. (2022). Setsuji o mothiita roshiago no goi gakusyū sutoratejī ― Jissyō kenkyū ni okeru jizen jigo tesuto no kouka kakunin ni motozuite. Rosiago kyōiku kenkyū, 1, 1–22.

    Google Scholar 

  • Schmitt, N. (1997). Vocabulary learning strategies. In D. N. Schmitt & M. McCarthy (Eds.), Vocabulary: Description, acquisition and pedagogy (pp. 199–227). Cambridge University Press.

    Google Scholar 

  • Schmitt, N., & Schmitt, D. (2020). Vocabulary in language teaching: Second edition. Cambridge University Press.

    Book  Google Scholar 

  • Sharoff, S., Umanskaya, E., & Wilson, J. (2013). A frequency dictionary of Russian: Core vocabulary for learners (Routledge frequency dictionaries). Routledge.

    Google Scholar 

  • Švedova, N. J. (Ed.) (1980). Russkaja grammatika (Tom I). Akademija nauk SSSR.

    Google Scholar 

  • Swenson, E., & West, M. (1934). On the counting of new words in textbooks for teaching foreign languages (No. 1). University of Toronto.

    Google Scholar 

  • Tixonov, A. N. (1985). Slovoobrazovatel’nyj slovar’ russkogo jazyka, v dvux tomax, okolo 145000 slov. Russkij jazyk.

    Google Scholar 

  • Tono, Y. (1997). Eigo goi shūtokuron: Bokyaburarī gakushū o kagaku suru. Kagensya.

    Google Scholar 

  • Uluxanov, I. S. (1996). Edinicy slovoobrazovatel’noj sistemy russkogo jazyka i ix leksičeskaja realizacija. Astrasem’.

    Google Scholar 

  • Wade, T. (2011). A comprehensive Russian grammar, revised and updated (3rd ed.). Blackwell Publishers.

    Google Scholar 

  • Ward, J., & Chuenjundaeng, J. (2009). Suffix knowledge: Acquisition and applications. System, 37, 461–469.

    Article  Google Scholar 

  • Webb, S., & Nation, I. S. P. (2017). How vocabulary is learned. Oxford University Press.

    Google Scholar 

  • Wheeler, M., Unbegaun, B., & Falla, P. (Eds.) (2007). Oxford Russian dictionary: Russian-English / English-Russian. Oxford University Press.

    Google Scholar 

  • Wilkins, D. A. (1972). Linguistics in language teaching. Arnold.

    Google Scholar 

  • Xinjie, L. (2011). A study of acquiring L2 vocabulary through using word part strategy. Master’s thesis, Diva portal. https://www.diva-portal.org/smash/get/diva2:427946/fulltext01.pdf.

  • Zemskaja, E. A. (1973). Sovremennyj russkij jazyk: Slovoobrazovanie. Prosveŝenie.

    Google Scholar 

  • Zwier, L. J., & Boers, F. (2023). English L2 vocabulary learning and teaching: Concepts, principles, and pedagogy. Routledge.

    Google Scholar 

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Funding

This study was supported by JSPS KAKENHI Grant Number ‘23K12238’.

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  1. Department of Russian Studies, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-8554, Japan

    Gota Sayama

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  1. Gota Sayama
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Appendices

Appendix 1

Table 9 Frequency date of prefixes and quantity of derivational words with these prefixes based on 5000 high-frequency words from RNC-M and RNC-S (in frequency order)
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Appendix 2

A fragment to be used in instruction about the abundance of derived words in Russian (the original one was provided in Russian and Japanese)

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Sayama, G. Verification of the effectiveness of vocabulary learning strategies using Russian word formation based on empirical research. Russ Linguist 48, 8 (2024). https://doi.org/10.1007/s11185-024-09292-5

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